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A critical review of methods for assessing cancer survival disparities in indigenous population
Accepted Manuscript A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Population Diana R. Withrow, C. Sarai Racey, Sehar Jamal PII:
S1047-2797(16)30166-1
DOI:
10.1016/j.annepidem.2016.06.007
Reference:
AEP 7967
To appear in:
Annals of Epidemiology
Received Date: 24 March 2016 Revised Date:
27 May 2016
Accepted Date: 6 June 2016
Please cite this article as: Withrow DR, Racey CS, Jamal S, A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Population, Annals of Epidemiology (2016), doi: 10.1016/ j.annepidem.2016.06.007. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Authors: Diana R. Withrow1,2, C. Sarai Racey2, Sehar Jamal1
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A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Populations
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Affiliations: 1 Aboriginal Cancer Control Unit, Cancer Care Ontario, Toronto, Ontario 2 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario
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Running title: Review of cancer survival studies in indigenous populations Financial support: Diana Withrow was supported by a Canadian Institutes of Health Research Doctoral Award (Code 201110DQU-265978-206086)
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Corresponding author: Diana R. Withrow Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics National Cancer Institute, National Institutes of Health 9609 Medical Center Drive, Room 7E590 Rockville, MD 20850 Email: [email protected] Phone: 240-276-7869 Conflicts of interest: None
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Article category: Review Words: 4,405 Tables: 3 Figures: 1 References: 125
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Title: A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Population Abstract
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An increasing cancer burden among Indigenous populations has led to a growing literature about survival disparities between Indigenous and non-Indigenous persons. We aim to describe and appraise methods used to measure cancer survival in Indigenous persons in the United States, Canada, Australia and New Zealand. We searched Medline, Web of Science and EMBASE for articles published between 1990 and 2015 that estimated survival in populations Indigenous to one of these four countries. We gathered information about data sources, analytical methods, and the extent to which threats to validity were discussed. The search retrieved 83 articles. The most common approach to survival analysis was cause-specific survival (n=49). Thirty-eight articles measured all-cause survival and 11 measured excess mortality attributable to cancer (relative survival). Three sources of information bias common to all studies (ethnic misclassification, incomplete case ascertainment and incomplete death ascertainment) were acknowledged in a minority of articles. The methodological considerations we present here are shared with studies of cancer survival across other sub-populations. We urge future researchers on this and related topics to clearly describe their data sources, to justify analytic choices and to fully discuss the potential impact of those choices on the results and interpretation. Words: 196
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Keywords: Neoplasms; Survival Analysis; Indians, North American; Oceanic Ancestry Group; Health Status Disparities; Healthcare Disparities
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List of Abbreviations and Acronyms
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AI
American Indian
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AI/AN
American Indian/Alaska Native
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DCO
Death Certificate Only
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IHS
Indian Health Service
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RSR
Relative Survival Ratio
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SEER
Surveillance, Epidemiology and End Results
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Introduction
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Progress in and priorities for cancer control can be identified through a variety of metrics of
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cancer burden including incidence, mortality, prevalence, person years of life lost and survival.
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Cancer survival in particular can act as a metric of the overall effectiveness of health care
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services and the management of cancer patients. Disparities in cancer survival between
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subpopulations can illustrate the need for action and provide insight into which interventions
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might have the greatest impact for reducing the burden of cancer within those populations.
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Notable disparities in health exist between Indigenous and non-Indigenous populations with
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Indigenous persons being, on average, less healthy than their non-Indigenous peers.(1-4) The
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validity of metrics of cancer burden in these populations is threated by, among other factors, the
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varying validity of ethnic identifiers population cancer registries. Notwithstanding this limitation,
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it appears that cancer incidence was historically lower among Indigenous populations than
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among non-Indigenous populations(5-9) and that over time, incidence of and mortality from
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cancer have been increasing among Indigenous populations to meet if not exceed rates in the
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general population.(5,9-15)
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Increasing attention paid to Indigenous health(16,17) and evidence of the increasing burden of
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cancer amongst Indigenous populations has led to increasing documentation of cancer survival
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disparities between Indigenous and non-Indigenous persons. These studies aim to illustrate the
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extent of disparities, and to identify how inequalities are initiated and sustained.
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There is an extensive body of literature pertaining to the measurement and interpretation of
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cancer survival in general.(18-21) There is also an awareness that information bias can arise as a
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result of improper ascertainment or classification of cancer cases or deaths(22-24). In this
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review, we have examined the extent to which the issues raised in this more general literature are
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acknowledged and/or overcome in articles reporting on Indigenous cancer survival.
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In the absence of methodological rigor and thoughtful consideration of the implications of
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methodological choices, the findings of these articles could be biased or misinterpreted.
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Directing resources and designing programs to reduce the cancer burden in Indigenous
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populations based on biased information will be at best inefficient and at worst ineffective. We
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therefore call attention to potential sources of bias and their consequences so that future authors
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can measure and interpret survival knowledgeably and so that future readers can appraise
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methods and interpret the findings of this research critically.
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The aim of this review is to describe and critically appraise the methods used to measure cancer
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survival in Indigenous populations in the US, Canada, Australia and New Zealand. We will
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discuss barriers to methodological rigor and their consequences and will suggest some ways to
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overcome common challenges, or at the least, to diminish their effect on validity. The
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methodological challenges that we identify and discuss here are common to studies of
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Indigenous cancer survival but are not specific to them. Our recommendations can therefore be
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applied more generally to Indigenous health research that uses administrative data and to
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comparisons of survival between other subgroups in a population.
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Methods
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We systematically searched Medline, Web of Science and EMBASE for articles published in
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English from January 1st, 1990 to September 4th, 2015. A broad search strategy used keywords
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falling under three themes: cancer, survival, and Indigenousness. A detailed list of keywords,
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Medical Subject Headings and Emtree terms for each theme is provided in Appendix A. Based
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on titles and abstracts, those articles that appeared to have measured cancer survival in one of the
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target populations were retrieved in full text and assessed using the inclusion criteria described
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below.
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To be eligible for inclusion, articles had to be population-based or multi-centered and report an
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absolute or relative estimate of survival from one or more cancers in any of: American Indians
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and/or Alaska Natives (AI/AN) in the US; First Nations and/or Métis in Canada; Aboriginals
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and/or Torres Strait Islanders in Australia; or Maori in New Zealand. Indigenous populations in
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northern or arctic regions were excluded because of unique challenges to health care access and
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administrative record keeping imposed by their geographical remoteness. Alaska Natives were
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exempt from this exclusion because the Surveillance, Epidemiology and End Results (SEER)
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database, a commonly used data source in the US, does not distinguish between American
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Indians (AI) and Alaska Natives.
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If two or more articles were based on the same data (as many were due to the use of cancer
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registries), both were included if they were based on different years of diagnosis, included
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different cancers or covariates or employed different analytic approaches or survival endpoints.
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Studies that were never published as full-text articles (i.e. conference proceedings and abstracts)
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were excluded because the methods sections were insufficient.
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Once retrieved, descriptions of data sources and analytical methods were abstracted using a
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standardized data-collection form. Data were collected under three themes: descriptive
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characteristics, which included the geographical setting, the Indigenous group, the comparison
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group and the cancers included; analytic approaches, which included the methodological
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approach to survival analysis and the covariates measured; and the potential for and discussion of
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bias, which included a tally of the articles that acknowledged the potential of ethnic
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misclassification, and incomplete death or case ascertainment. If there was ambiguity on any of
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these points, the article was reviewed with a second reviewer until consensus was reached.
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Results
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The literature search identified 1503 articles, of which 402 were from MEDLINE, 697 from
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Embase and 404 from Web of Science. After removing duplicate records, titles and abstracts of
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692 unique articles were screened for eligibility. Of these, 138 full-text articles potentially met
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the inclusion criteria and were retrieved and reviewed in full text. Fifty-five articles were
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excluded for the following reasons: they did not measure absolute or relative survival in a
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candidate population, were based on a single clinical centre, measured childhood cancer survival
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only or were citing results from a previous study (see Figure 1).
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The general characteristics of the 83 articles included in this review are listed in Table 1. Articles
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on this topic are being published at an increasing frequency over time. We retrieved six articles
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meeting the inclusion criteria published between 1991 and 1995 whereas we retrieved 38 articles
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meeting the criteria published between 2011 and 2015.
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Of the 83 articles included, 40 were from the US(25-64). Articles from the US primarily covered
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regions participating in the SEER program. Three articles from Florida,(60,61,63) two articles
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from Montana,(26,35) and one article from South Dakota(58) were exceptions. Twenty-two of
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the 83 articles pertained to survival of the Maori in New Zealand,(65-86) and all but five of these
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were conducted at the national level.(65,79,83,85,86) Sixteen articles of 83 were based on
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Australian data and all but one were conducted within the boundaries of the five mainland states:
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Western Australia(87), the Northern Territory(15,88,89), New South Wales(90), Queensland(91-
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97) and South Australia(98-100). Five articles pertaining to First Nations in Canada were
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included in the review. These were published based on data from three of Ontario’s 13 provinces
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and territories: Saskatchewan(101,102), Ontario(103,104) and Alberta(105). There were not any
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articles presenting original survival estimates for more than one country.
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The mortality outcomes and statistical methods used to calculate and compare survival are
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outlined in Table 2. The most common outcome was cause-specific survival, used by 49 of 83
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articles. Thirty-eight articles used all-cause survival as a mortality outcome and 11 measured
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excess mortality attributable to cancer (relative survival).
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Fifty-six articles provided an absolute estimate of survival in an Indigenous population. Sixty-
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five articles measured survival in an Indigenous population relative to a non-Indigenous
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population, generating hazard or relative survival ratios. Articles acknowledged the potential for
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information bias to different extents, summarized in Table 3. For example, 46 of 83 articles
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touched upon the idea of potential ethnic misclassification in their data sources. A minority of
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articles alluded to case ascertainment (n=30) and death ascertainment (n=25).
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Discussion
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The approaches to measuring and comparing survival in Indigenous and non-Indigenous
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populations in the literature we reviewed varied, as did the extent to which authors
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acknowledged potential sources of information bias. It is understandable that every
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methodological consideration cannot be covered in detail in every paper. Nonetheless, it is our
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belief that analyses of cancer survival in Indigenous and non-Indigenous populations should be
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held to an epidemiologic standard consistent with the cancer survival literature in general. In this
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section, we begin by discussing the circumstances that give rise to, and potential consequences of
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information bias and the extent to which these were considered in the literature. We then
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consider the choice of survival measure and its implications for interpretation.
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Information bias
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In order to estimate and compare cancer survival within and between subgroups of a population
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without bias, all cancer cases and deaths (or all those in a representative sample of the
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population) must be ascertained and each cancer case must be correctly assigned to the subgroup
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to which they truly belong. Below, we discuss how three potential sources of information bias
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may violate these principles: ethnic misclassification, case ascertainment and death
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ascertainment.
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(i) Ethnic misclassification
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Ethnic misclassification occurs when an individual is assigned to an ethnic group to which he or
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she does not belong. Most papers (n=72) identified the source of their ethnicity data, most often
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the cancer registry, but the sources used to populate the cancer registry were poorly described.
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Many simply said that it was collected from the medical record, with no explanation as to how
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ethnicity was ascertained in the medical record.
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Ethnicity as recorded in the medical record is often based on a health provider’s subjective
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appraisal rather than self-report and, when self-report is used, patients may be hesitant to identify
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themselves as Indigenous(106-108). Errors that arise in the medical record as a result of
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subjectivity, inconsistency and/or response bias will perpetuate in the cancer registries they
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populate and typically result in an undercount of Indigenous cancer cases(36). In the Northern
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Territory of Australia, Condon et al. found that 15% of Indigenous persons were misclassified as
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non-Indigenous.(109) In New Zealand, 17% of Maori were misclassified as non-Maori upon
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cancer registration.(110) In the state of Michigan, linking Indian Health Service (IHS) records to
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the state cancer registry resulted in a 97% increase in cases classified as AI/AN and a linkage to
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a tribal register resulted in a further increase of 15%.(111)
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Ethnic misclassification results in biased estimates of survival on both the absolute scale and
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relative scale if misclassification is common (as has been described above) and those who are
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misclassified differ from those who were correctly classified in ways that are associated with
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survival. For example, a linkage of the Seattle-Puget Sound SEER registry to IHS records
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revealed that Native Americans misclassified as white by the SEER registry have better cancer
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survival compared to those that were correctly identified as Native American.(27)
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At a national level, Clegg et al. used the National Longitudinal Mortality Study to validate
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ethnicity as reported in SEER and found that survival time for AI/AN was substantially longer
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when based on self-reported AI/AN status compared to SEER classification.(112) In both these
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instances, ethnic misclassification was associated with survival and therefore introduced bias that
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had a meaningful impact on the results. Despite the evidence that ethnic misclassification occurs,
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only 46 of the 83 articles acknowledged the potential of ethnic misclassification in their studies.
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Linkage of cancer registries to databases such as the IHS or tribal registers will reduce ethnic
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misclassification and improve the validity of measures of cancer survival. Where routine linkage
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is unfeasible, further validation studies of ethnic identifiers in cancer registries could fill a
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significant gap in our understanding of the degree to which ethnic misclassification is occurring
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and provide insight into the potential consequences it has for estimation of cancer survival in
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Indigenous populations. Authors should report on the source files that populate the cancer
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registry, comment on the suspected validity of these sources and report the limitations associated
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with the use of these data sources.
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(ii) Case Ascertainment
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Case ascertainment refers to the proportion of all cancer cases resident in a registry’s catchment
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area that are captured by the registry. The completeness of case ascertainment varies by registry
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and potentially within subsets of the population covered by the registry. For example, in
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Montana, investigators used both the cancer registry and IHS medical records to find Indigenous
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cancer cases. Of the cases they found, 33% were included in the registry but absent from IHS
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records and 27% were identified based solely on IHS records(35). If the same Montana-based
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study had relied on either source exclusively, approximately one third of Indigenous cases would
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have been missed.
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Incomplete case ascertainment will result in biased estimates of survival on the absolute scale if
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survival of the ascertained cases is different than non-ascertained cases. Biased estimates of
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survival on the relative scale will arise if this error is differential across ethnicities. Of the
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articles we reviewed, just over a third (n=30) alluded to the general idea of case ascertainment
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and only 9 acknowledged that there could be differential case ascertainment by ethnicity.
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By nature of being unascertained, it is impossible for an investigator to compare survival
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between missing and included cases and determine whether bias is present. To consider this
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possibility however, like the study in Montana, investigators could use several sources to identify
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cancer cases in the Indigenous population and compare the survival of patients identified by each
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method.
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In the absence of an alternative data set, the proportion of cases identified by death certificate
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only (DCO) can act as an indicator of the completeness of case ascertainment. DCO cases are
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those cancer cases that were identified solely because cancer was listed as the underlying cause
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of death on the death certificate but would otherwise be unknown to the registry. DCO cases are
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not typically included in survival analyses because their true date of diagnosis is unknown. The
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proportion of cases within a registry that are DCO is a measure of data quality typically reported
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by the registry.
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To crudely consider the extent to which differential case ascertainment across ethnicities may
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have biased comparisons of survival, the proportion of cases that are DCO should be reported by
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ethnicity if possible (i.e. if ethnicity is known based on the death certificate).(24) While in the
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general population, the proportion of DCO cases is likely to be small due to adherence to data
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quality standards at the registry-level, the proportion of DCO cases within ethnic subgroup smay
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be substantially higher and worthy of consideration. If the proportion of DCO cases within the
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subgroup of interest is large, and these cases are being excluded as a result of unknown survival
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time, survival may be biased. The direction of the bias will depend on the follow-up and trace-
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back practices of the registry as well as the traits that are associated with being DCO in that
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setting.(113)
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(iii) Validity of Cause of Death & Death Ascertainment
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Two outcomes may be of interest in cancer survival analyses: the fact of death (did this person
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die?) and the cause of death (how?). Death ascertainment refers to the completeness of fact of
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death, and will affect all cancer survival measures. High rates of loss to follow-up (low death
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ascertainment) will lead to biased estimates of survival on the absolute scale if those who are lost
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are systematically more or less likely to survive than those who are not. As with case
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ascertainment, loss to follow-up will only cause bias in relative estimates of survival if it is
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associated with both survival and ethnicity. Of the 83 articles we reviewed, 25 touched upon the
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idea of death ascertainment and 13 acknowledged the potential for differential death
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ascertainment by ethnicity.
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A subset of US-based articles that evaluated death ascertainment found that follow-up was not
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related to ethnicity.(30,32,33) However, this consistent finding might be the result of selective
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reporting. Preliminary analyses of some unpublished Canadian data showed that deaths from
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breast cancer amongst diagnosed cases of breast cancer dropped after age 75 in Ontario First
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Nations but not in the control group, suggesting that deaths in First Nations were not being fully
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ascertained.
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Mechanisms to improve death ascertainment will differ based on the routine follow-up methods
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of the registry (i.e. active or passive) and are often beyond the control of the investigator.
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Investigators are, however, urged to consider whether the routine follow-up methods of the
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registry are likely to have less success in identifying deaths among subsets of the population, as
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this could result in spuriously high survival estimates and distort estimates of the disparities in
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survival between groups. Where possible, the completeness of death ascertainment at the cancer
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registry level should be reported and the potential for differential death ascertainment by
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ethnicity should be disclosed. If the risk of differential death ascertainment is considered high,
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results should be interpreted with greater caution.
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Misclassification of, or missing information about, the cause of death will lead to biased
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estimates of cause-specific survival on the absolute and relative scale, especially for cancers of
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poor prognosis.(18) Despite this, only 12 of the 49 articles calculating cause-specific survival
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alluded to the validity and/or completeness of cause of death data. If cause-specific survival is
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used, the suspected validity of the cause of death classification, and any differences in validity
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that might exist across subgroups, should be reported.
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Survival measures
Cancer survival is typically measured using one of three outcomes: all-cause mortality, cause-
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specific mortality and excess mortality due to cancer. Each approach aims to answer a slightly
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different question about survival and relies on different information about the mortality
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experience of cancer patients. All three methods require information about the date of death.
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Cause-specific mortality additionally requires information about the cause of death in cancer
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cases and relative survival (excess mortality) additionally requires information about the
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expected mortality in the population from which cancer cases arose. The availability of cause of
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death or expected mortality data often dictates the approach used.
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Interpreted correctly in the absence of bias, any of these approaches can generate estimates of
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survival that are useful to patients, care providers and policy makers. When estimating the
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disparity in cancer survival between two populations however, the interpretation of the ratio of
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these measures (likely a hazard ratio) is more nuanced. Each of these will be discussed in turn.
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(i)
All-cause survival
Unlike cause-specific and relative survival methods, which aim to estimate survival in a
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hypothetical world where cancer is the only cause of death, all-cause survival measures the
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observed survival of cancer patients. This information can be useful to patients, researchers and
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policy makers. Advantages to this measure are that it requires the fewest data elements, and that
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it is easily interpretable. However, a ratio of all-cause survival of Indigenous to non-Indigenous
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cancer patients is a measure not only of the disparity in cancer-specific survival, but also of the
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disparity in overall survival.
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Because Indigenous populations tend to have a lower life expectancy (higher background
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mortality), all-cause mortality ratios are likely to overestimate the cancer-related disparity. Given
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that we typically want to consider mortality associated with the cancer itself, we use cause-
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specific or excess mortality outcomes (measures of net mortality) to correct for mortality from
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other causes.(19) When data on cause of death or expected mortality are unavailable however,
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all-cause survival may be the only approach possible, which likely explains its popularity in the
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literature we reviewed.
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Cause-specific survival
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In cause-specific survival, a death due to cancer is counted as an event and a death due to any
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other cause is censored. Using this approach requires access to and confidence in cause of death
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as recorded on death certificates. As was discussed earlier, incomplete or invalid cause of death
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classification can be a source of information bias in studies using cause-specific mortality as an
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outcome.
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Cause-specific survival poses an additional challenge by requiring a clear distinction between
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cancer-related deaths and deaths independent of cancer. The magnitude of cause-specific
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survival estimates will vary according to where the line between cancer attributable and non-
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cancer deaths is drawn.(114)
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Dichotomizing deaths as “due to cancer” or “not due to cancer” can also have implications for
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estimating survival disparities between populations. If population X is less healthy at diagnosis
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than Population Y (e.g. X has more comorbidities), then Population X may have true rates of
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excess death attributable to cancer that are equal to or higher than Population Y, but will appear
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to have better cause-specific survival because their deaths were attributed to the comorbidities
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rather than to their cancers. One approach to rectify this is to broaden the definition of a cancer
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death. Howlader and colleagues have proposed such a definition, which uses an algorithm to
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classify causes of death as cancer or other-cause by taking into account site of the original cancer
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diagnosis, the tumor sequence and comorbidities (e.g. HIV/AIDS and/or site-related non-cancer
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diseases).(114)
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Of 49 articles that had cause-specific survival as an outcome, only 14 provided a definition of a
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cancer death. These ranged from death due to the cancer of interest as the primary cause of death
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to death from any cancer as a contributing cause of death. Narrower definitions of cancer death
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may overestimate net cancer survival in a single population because some excess deaths
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attributable to cancer (e.g. those where complications of treatment fatally exacerbated existing
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comorbidities, or those where deaths were attributable to cancer in a nearby organ rather than the
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primary site) will be censored as non-cancer deaths because the death certificate does not
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attribute death primarily to the initially registered cancer.(115)
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As a result, narrower definitions of cause of death may lead to underestimates of the disparities
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in net survival in populations with different profiles of comorbidities. If for example, Indigenous
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persons with cancer are more likely to have comorbidities than their non-Indigenous peers, under
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a narrow definition of cancer deaths, their net survival will be overestimated by a cause-specific
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approach compared to their peers with fewer comorbidities. To allow readers to properly
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interpret both absolute and relative estimates of survival, authors must disclose how they define a
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cancer death. Further, if one aims to quantify the disparity in net survival in two populations
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using cause-specific survival, a broader definition of a cancer death may be preferred.
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(iii)
Relative survival ratios
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Relative Survival Ratios (RSRs) are calculated by comparing the observed survival in a group of
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individuals diagnosed with cancer to the expected survival of the population to which they
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belong. RSRs overcome one of the major weaknesses of all-cause survival by taking into account 13
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differences in background mortality (and accordingly, comorbidities to the extent that they affect
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mortality) between populations. They are therefore particularly suitable for comparing survival
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between groups wherein background mortality is suspected to be different such as
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countries(116,117), socioeconomic classes(118) or races/ethnicities(119,120). Unlike cause-
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specific survival, RSRs do not rely on cause of death information, which may be unreliable or
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unavailable.
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The calculation of a valid RSR does, however, rely on valid population-specific estimates of
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mortality (life tables). Of the 11 studies that used excess mortality as an outcome, seven provided
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information about the life tables that were used to generate expected mortality. While they were
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all specific to age, sex and ethnicity, none were specific to calendar time, and the population
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used to generate the life table belonged to the same geographical region as the cancer cases in
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only two of the seven articles.
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Generating life tables tends to be straightforward at the national scale, where the population size
14
and mortality rates are readily available, but Indigenous-specific life tables can be much more
15
difficult to estimate. Indigenous-specific population counts and mortality rates may not exist, and
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if they do, legitimate barriers to their use include concerns around ethnic misclassification,
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differential death ascertainment across ethnicities and numerator-denominator bias in vital
18
statistics. One study from the US found that misclassification of ethnicity on death certificates
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led to an underestimate of mortality in AI by 21%.(120)
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If age-, sex-, ethnicity-, time period- and geography-specific life tables are available, relative
21
survival offers advantages over cause-specific and all-cause survival estimates. Given this, we
22
recommend that investigators planning analyses comparing cancer survival across ethnicities do
23
their utmost to produce or obtain the appropriate ethnic-specific life tables for their analyses.
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Authors should report on how the life tables were generated and consider the extent to which
25
bias in the expected mortality estimates may influence the results. In the absence of life tables, a
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cause-specific approach with a broad definition of cancer death may be an appropriate
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alternative. Researchers taking that approach, however, should be clear about how and why
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cause-specific survival estimates were used and what consequences that may have for
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comparability and bias.
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Limitations and Conclusions 14
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This is the first review of methods used to compare cancer survival across ethnic subgroups of
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populations that we are aware of. Articles comparing survival between Indigenous and non-
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Indigenous persons are being published at an increasing frequency making it an appropriate time
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to critically appraise methodological approaches.
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Limitations relating to the sensitivity of our literature search do deserve mention. The review
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does not include all research on this topic in the selected populations but is limited to those full-
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text articles identified in the peer-reviewed literature published within the time window of our
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search. The methodological issues we have presented are, however, likely to be common to those
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studies published more recently or in the grey literature.
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In this review, we have made suggestions for researchers who are estimating and comparing
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cancer survival in ethnic and/or racial subgroups of the population, but recognize that there is no
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single answer applicable to each situation. Each setting, population and data source poses
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particular challenges to validity and the ideal solutions are likely to be as varied as the obstacles.
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We hope, however, to have drawn attention to common sources of information bias. We have
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also provided an overview of the merits, potential pitfalls and interpretation of common
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measures of cancer survival. These are applicable not only to the study of Indigenous cancer
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survival disparities but also of Indigenous health disparities more generally, and of disparities in
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cancer survival between ethnic or other subgroups of a population.
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These studies provide the evidence required to mobilize resources and direct them to the areas
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that will have the greatest impact for reducing cancer survival disparities between Indigenous
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and non-Indigenous populations. To accomplish this, however, valid results and meaningful
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interpretations of these results are required. We urge future researchers on this and related topics
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to clearly describe their data sources, to justify their analytic choices and to fully discuss the
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potential impact of those approaches on the results and interpretation.
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Acknowledgments
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We acknowledge insightful comments on drafts of this paper from Wendy Lou, Loraine Marrett,
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Diane Nishri and Jason Pole. Caroline Cawley contributed valuable editorial expertise. Diana
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Withrow was supported by a Canadian Institutes of Health Research Doctoral Award. The funder
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had no role in the preparation of this paper.
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References 1.
RI PT
2.
Reading CL, Wien F. Health inequalities and the social determinants of Aboriginal peoples' health. National Collaborating Centre for Aboriginal Health Prince George, BC; 2009. Barnes PM, Adams PF, Powell-Griner E. Health characteristics of the American Indian or Alaska Native adult population: United States, 2004-2008. US Department of Health and Human Services; 2010. Baker MG, Barnard LT, Kvalsvig A, Verrall A, Zhang J, Keall M, et al. Increasing incidence of serious infectious diseases and inequalities in New Zealand: a national epidemiological study. Lancet. 2012 Mar;379(9821):1112–9. Robson B, Harris R. (eds). Hauora: Maori Standards of Health IV. A study of the years 2000-2005. Te Rōpū Rangahau Hauora a Eru Pōmare; 2007. Espey DK, Wu X-C, Swan J, Wiggins C, Jim MA, Ward E, et al. Annual report to the nation on the status of cancer, 1975-2004, featuring cancer in American Indians and Alaska Natives. Cancer. 2007 Nov 15;110(10):2119–52. Mahoney MC, Michalek AM. A meta-analysis of cancer incidence in United States and Canadian native populations. Int J Epidemiol. 1991 Jun;20(2):323–7. Hunter CP. Epidemiology, stage at diagnosis, and tumor biology of breast carcinoma in multiracial and multiethnic populations. Cancer. 2000 Mar 1;88(S5):1193–202. Condon JR, Armstrong BK, Barnes A, Cunningham J. Cancer in Indigenous Australians: a review. Cancer Causes Control. 2003 Mar;14(2):109–21. Shaw C, Blakely T, Sarfati D, Fawcett J, Peace J. Trends in colorectal cancer mortality by ethnicity and socio economic position in New Zealand, 1981 99: one country, many stories.Aust N Z J Public Health. 2006 Feb 1;30(1):64–70. Kelly JJ, Lanier AP, Alberts S, Wiggins CL. Differences in cancer incidence among Indians in Alaska and New Mexico and U.S. Whites, 1993-2002. Cancer Epidemiol Biomarkers Prev. 2006 Aug;15(8):1515–9. Marrett LD, Nishri ED. Cancer incidence among Registered First Nations in Ontario, 1968-2001. Toronto; 2010. Tjepkema M, Wilkins R, Senécal S, Guimond E, Penney C. Mortality of Métis and registered Indian adults in Canada: an 11-year follow-up study. Health Rep. 2009 Dec;20(4):31–51. Cunningham J, Rumbold AR, Zhang X, Condon JR. Incidence, aetiology, and outcomes of cancer in Indigenous peoples in Australia. Lancet Oncol. 2008 Jun;9(6):585–95. Supramaniam R, Grindley H, Pulver LJ. Cancer mortality in Aboriginal people in New South Wales, Australia, 1994–2002.Aust N Z J Public Health. 2006 Oct 1;30(5):453–6. Condon JR, Armstrong BK, Barnes T, Zhao Y. Cancer incidence and survival for indigenous Australians in the Northern Territory.Aust N Z J Public Health. 2005 Apr;29(2):123–8. Gracey M, King M. Indigenous health part 1: determinants and disease patterns. Lancet. 2009 Jul 4;374(9683):65–75.
3.
SC
4.
7. 8. 9.
10.
11.
AC C
12.
EP
6.
TE D
M AN U
5.
13.
14.
15.
16.
ACCEPTED MANUSCRIPT
22. 23. 24.
25.
26.
27.
28.
AC C
29.
RI PT
21.
SC
20.
M AN U
19.
TE D
18.
King M, Smith A, Gracey M. Indigenous health part 2: the underlying causes of the health gap. Lancet. 2009 Jul 4;374(9683):76–85. Sarfati D, Blakely T, Pearce N. Measuring cancer survival in populations: relative survival vs cancer-specific survival. Int J Epidemiol. 2010 Apr;39(2):598–610. Dickman PW, Adami H-O. Interpreting trends in cancer patient survival. J Intern Med. 2006 Aug;260(2):103–17. Berrino F, Micheli A, Sant M, Capocaccia R. Interpreting survival differences and trends. Tumori. 1997 Jan;83(1):9–16. Altman DG, De Stavola BL, Love SB, Stepniewska KA. Review of survival analyses published in cancer journals. Br J Cancer. 1995 Aug;72(2):511–8. Begg CB, Schrag D. Attribution of deaths following cancer treatment. J Natl Cancer Inst. 2002 Jul 17;94(14):1044–5. Welch HG, Black WC. Are deaths within 1 month of cancer-directed surgery attributed to cancer? J Natl Cancer Inst. 2002 Jul 17;94(14):1066–70. Robinson D, Sankila R, Hakulinen T, Møller H. Interpreting international comparisons of cancer survival: the effects of incomplete registration and the presence of death certificate only cases on survival estimates. Eur J Cancer. 2007 Mar;43(5):909–13. Jemal A, Clegg LX, Ward E, Ries LAG, Wu X, Jamison PM, et al. Annual report to the nation on the status of cancer, 1975-2001, with a special feature regarding survival. Cancer. 2004 Jul 1;101(1):3–27. Bleed DM, Risser DR, Sperry S, Hellhake D, Helgerson SD. Cancer incidence and survival among American Indians registered for Indian health service care in Montana, 1982-1987. J Natl Cancer Inst. 1992 Oct 7;84(19):1500–5. Sugarman JR, Dennis LK, White E. Cancer survival among American Indians in western Washington State (United States). Cancer Causes Control. 1994 Sep;5(5):440–8. Baquet CR. Native Americans' cancer rates in comparison with other peoples of color. Cancer. 1996 Oct 1;78(7 Suppl):1538–44. Frost F, Tollestrup K, Hunt WC, Gilliland F, Key CR, Urbina CE. Breast cancer survival among New Mexico Hispanic, American Indian, and non-Hispanic white women (1973-1992). Cancer Epidemiol Biomarkers Prev. 1996 Nov;5(11):861–6. Gilliland FD, Hunt WC, Key CR. Ethnic variation in prostate cancer survival in New Mexico. Cancer Epidemiol Biomarkers Prev. 1996 Apr;5(4):247–51. Schiff M, Key CR, Gilliland FD, Becker TM. Ethnic differences in uterine corpus cancer incidence and mortality in New Mexico's American Indians, Hispanics and non-Hispanic whites. Int J Epidemiol. 1997;26(2):249–55. Brown MO, Lanier AP, Becker TM. Colorectal cancer incidence and survival among Alaska Natives, 1969-1993. Int J Epidemiol. 1998 Jun;27(3):388–96. Gilliland FD, Hunt WC, Key CR. Trends in the survival of American Indian, Hispanic, and Non-Hispanic white cancer patients in New Mexico and Arizona, 1969-1994. Cancer. 1998 May 1;82(9):1769–83. Gilliland FD, Key CR. Prostate cancer in American Indians, New Mexico, 1969 to 1994. J Urol. 1998 Mar;159(3):893–7–discussion897–8.
EP
17.
30. 31.
32. 33.
34.
18
ACCEPTED MANUSCRIPT
40.
41.
42.
43. 44.
45.
AC C
46.
RI PT
39.
SC
38.
M AN U
37.
TE D
36.
Dennis TD. Cancer stage at diagnosis, treatment, and survival among American Indians and non-American Indians in Montana. Cancer. 2000 Jul 1;89(1):181–6. Clegg LX, Li FP, Hankey BF, Chu K, Edwards BK. Cancer survival among US whites and minorities: a SEER (Surveillance, Epidemiology, and End Results) Program population-based study. Arch Intern Med. 2002 Sep 23;162(17):1985–93. Li CI, Malone KE, Daling JR. Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch Intern Med. 2003 Jan 13;163(1):49–56. Biggs ML, Schwartz SM. Differences in testis cancer survival by race and ethnicity: a population-based study, 1973-1999 (United States). Cancer Causes Control. 2004 Jun;15(5):437–44. Chien C, Morimoto LM, Tom J, Li CI. Differences in colorectal carcinoma stage and survival by race and ethnicity. Cancer. 2005 Aug 1;104(3):629–39. Wampler NS, Lash TL, Silliman RA, Heeren TC. Breast cancer survival of American Indian/Alaska Native women, 1973–1996. Soz-Präventivmed. Birkhäuser-Verlag; 2005 Aug 1;50(4):230–7. Cormier JN, Xing Y, Ding M, Lee JE, Mansfield PF, Gershenwald JE, et al. Ethnic differences among patients with cutaneous melanoma. Arch Intern Med. 2006 Sep 25;166(17):1907–14. Goggins WB, Wong GK. Poor Survival for US Pacific Islander Cancer Patients: Evidence From the Surveillance, Epidemiology, and End Results Database: 1991 to 2004. J Clin Oncol. 2007 Dec 20;25(36):5738–41. Wang SJ, Fuller CD, Thomas CR. Ethnic disparities in conditional survival of patients with non-small cell lung cancer. J Thorac Oncol. 2007 Mar;2(3):180–90. Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman MC. Trends in Area-Socioeconomic and Race-Ethnic Disparities in Breast Cancer Incidence, Stage at Diagnosis, Screening, Mortality, and Survival among Women Ages 50 Years and Over (1987-2005). Cancer Epidemiol Biomarkers Prev. 2009;18(1):121–31. Tehranifar P, Neugut AI, Phelan JC, Link BG, Liao Y, Desai M, et al. Medical Advances and Racial/Ethnic Disparities in Cancer Survival. Cancer Epidemiol Biomarkers Prev. 2009 Sep 29;:1–9. Fesinmeyer MD, Goulart B, Blough DK, Buchwald D, Ramsey SD. Lung cancer histology, stage, treatment, and survival in American Indians and Alaska Natives and whites. Cancer. 2010 Jul 1;116(20):4810–6. Yu G-P, Li JC-L, Branovan D, McCormick S, Schantz SP. Thyroid cancer incidence and survival in the national cancer institute surveillance, epidemiology, and end results race/ethnicity groups. Thyroid. 2010 May;20(5):465–73. Cetin K, Ettinger DS, Hei Y, O'Malley CD. Prognostic factors by histologic subtype in stage IV non-small cell lung cancer (NSCLC): A population-based survival analysis of data from the Surveillance, Epidemiology, and End Results (SEER) Program (1988-2003). ASCO Meeting Abstracts. 2009 May 20;27(15S):11053. Cueto CV, Szeja S, Wertheim BC, Ong ES, Tsikitis VL. Disparities in Treatment and Survival of White and Native American Patients with Colorectal Cancer: A SEER Analysis. J Am Coll Surg. 2011 Oct 1;213(4):469–74. Du XL, Lin CC, Johnson NJ, Altekruse S. Effects of individual-level socioeconomic factors on racial disparities in cancer treatment and survival. Cancer. 2011 Jan
EP
35.
47.
48.
49.
50.
19
ACCEPTED MANUSCRIPT
55.
56. 57. 58.
59.
60.
RI PT
AC C
61.
SC
54.
M AN U
53.
TE D
52.
EP
51.
24;117(14):3242–51. Ooi SL, Martinez ME, Li CI. Disparities in breast cancer characteristics and outcomes by race/ethnicity. Breast Cancer Res Treat. 2011 Jun 7;127(3):729–38. Smith CB, Bonomi M, Packer S, Wisnivesky JP. Disparities in lung cancer stage, treatment and survival among American Indians and Alaskan Natives. Lung Cancer. 2011 May;72(2):160–4. Wu X-C, Eide MJ, King J, Saraiya M, Huang Y, Wiggins C, et al. Racial and ethnic variations in incidence and survival of cutaneous melanoma in the United States, 1999-2006. J Am Acad Dermatol. 2011 Nov 1;65(5):S26.e1–S26.e13. Singh GK. Rural–Urban Trends and Patterns in Cervical Cancer Mortality, Incidence, Stage, and Survival in the United States, 1950–2008. J Community Health. 2012 Feb 20;37(1):217–23. Kaya H, Peressini B, Jawed I, Martincic D, Elaimy AL, Lamoreaux WT, et al. Impact of age, race and decade of treatment on overall survival in a critical population analysis of 40,000 multiple myeloma patients. Int J Hematol. 2012 Jan 9;95(1):64–70. Kelly JJ, Alberts SR, Sacco F. Colorectal cancer in Alaska Native people, 2005– 2009. Gastrointest Cancer Res. 2012 Sept;5(5):149-54. Taghavi S, Jayarajan SN, Davey A, Willis AI. Prognostic Significance of Signet Ring Gastric Cancer. J Clin Oncol. 2012 Sep 28;30(28):3493–8. Dwojak SM, Finkelstein DM, Emerick KS, Lee JH, Petereit DG, Deschler DG. Poor Survival for American Indians with Head and Neck Squamous Cell Carcinoma. Otolaryngol Head Neck Surg. 2014 Jul 23;151(2):265–71. Dwojak SM, Sequist TD, Emerick K, Deschler DG. Survival differences among American Indians/Alaska natives with head and neck squamous cell carcinoma. Head Neck. 2012 Aug 8;35(8):1114–8. Tannenbaum SL, Koru-Sengul T, Miao F, Byrne MM. Disparities in survival after female breast cancer diagnosis: a population-based study. Cancer Causes Control. 2013 Jun 18;24(9):1705–15. Tannenbaum SL, Koru-Sengul T, Zhao W, Miao F, Byrne MM. Survival Disparities in Non–Small Cell Lung Cancer by Race, Ethnicity, and Socioeconomic Status. Cancer J Sci Am. 2014;20(4):237–45. Javid SH, Varghese TK, Morris AM, Porter MP, He H, Buchwald D, et al. Guideline-concordant cancer care and survival among American Indian/Alaskan Native patients. Cancer. 2014 Apr 7;120(14):2183–90. Lee DJ, Tannenbaum SL, Koru-Sengul T, Miao F, Zhao W, Byrne MM. Native American race, use of the Indian Health Service, and breast and lung cancer survival in Florida, 1996-2007. Prev Chronic Dis. 2014;11:E35. Mahdi H, Schlick CJ, Kowk L-L, Moslemi-Kebria M, Michener C. Endometrial cancer in Asian and American Indian/Alaskan Native women: Tumor characteristics, treatment and outcome compared to non-Hispanic white women. Gynecol Oncol. 2014 Feb 1;132(2):443–9. Lethaby AE, Mason BH, Holdaway IM, Kay RG. Age and ethnicity as prognostic factors influencing overall survival in breast cancer patients in the Auckland region. Auckland Breast Cancer Study Group. N Z Med J. 1992 Dec 9;105(947):485–8.
62.
63.
64.
65.
20
ACCEPTED MANUSCRIPT
71. 72.
73.
74.
75.
76.
AC C
77.
RI PT
70.
SC
69.
M AN U
68.
TE D
67.
Delahunt B, Bethwaite P, Nacey JN. Renal cell carcinoma in New Zealand: a national survival study. Urology. 1994 Mar;43(3):300–9. Gill AJ, Martin IG. Survival from upper gastrointestinal cancer in New Zealand: The effect of distance from a major hospital, socio-economic status, ethnicity, age and gender. ANZ J Surg. 2002;72(9):643–6. Phillips ARJ, Lawes CMM, Cooper GJS, Windsor JA. Ethnic disparity of pancreatic cancer in New Zealand. Int J Gastrointest Cancer. 2002;31(1-3):137–45. Jeffreys M, Stevanovic V, Tobias M, Lewis C, Ellison-Loschmann L, Pearce N, et al. Ethnic inequalities in cancer survival in New Zealand: linkage study. Am J Public Health. 2005;95(5):834. Haynes R, Pearce J, Barnett R. Cancer survival in New Zealand: ethnic, social and geographical inequalities. Soc Sci Med. 2008 Sep;67(6):928–37. Sneyd MJ. Ethnic differences in prostate cancer survival in New Zealand: a national study. Cancer Causes Control. 2008 Nov 14;19(9):993–9. Brewer N, Pearce N, Jeffreys M, White P, Ellison-Loschmann L. Demographic differences in stage at diagnosis and cervical cancer survival in New Zealand, 19942005. J Womens Health (Larchmt). 2009 Jul;18(7):955–63. Hill S, Sarfati D, Blakely T, Robson B, Purdie G, Chen J, et al. Survival disparities in Indigenous and non-Indigenous New Zealanders with colon cancer: the role of patient comorbidity, treatment and health service factors. J Epidemiol Community Health. 2010 Jan 7;64(2):117–23. Mcleod M, Harris R, Purdie G, Cormack D, Robson B, Sykes P, et al. Improving survival disparities in cervical cancer between Māori and non-Māori women in New Zealand: a national retrospective cohort study. Aust N Z J Public Health. 2010 Apr 1;34(2):193–9. Priest P, Sadler L, Sykes P, Marshall R, Peters J, Crengle S. Determinants of inequalities in cervical cancer stage at diagnosis and survival in New Zealand. Cancer Causes Control. 2010 Feb 22;21(2):209–14. Sammour T, Kahokehr A, Vather R, Connolly AB, Hill AG. Ethnic disparity in colonic cancer outcomes in New Zealand--biology or an access issue? Colorectal Dis. 2010 Jul;12(7 Online):e50–6. Brewer N, Borman B, Sarfati D, Jeffreys M, Fleming ST, Cheng S, et al. Does comorbidity explain the ethnic inequalities in cervical cancer survival in New Zealand? A retrospective cohort study. BMC Cancer. 2011;11(1):132. Brewer N, Zugna D, Daniel R, Borman B, Pearce N, Richiardi L. Which factors account for the ethnic inequalities in stage at diagnosis and cervical cancer survival in New Zealand? Cancer Epidemiol. 2012 Aug;36(4):e251–7. Swart EM, Sarfati D, Cunningham R, Dennett E, Signal V, Gurney J, et al. Ethnicity and rectal cancer management in New Zealand. N Z Med J. 2013 Oct 18;126(1384):42–54. Sarfati D, Gurney J, Stanley J, Koea J. A retrospective cohort study of patients with stomach and liver cancers: the impact of comorbidity and ethnicity on cancer care and outcomes. BMC Cancer. 2014 Nov 7;14(1):1–11. Campbell I, Scott N, Seneviratne S, Kollias J, Walters D, Taylor C, et al. Breast Cancer Characteristics and Survival Differences between Maori, Pacific and other
EP
66.
78.
79.
80.
81.
21
ACCEPTED MANUSCRIPT
86.
87.
88.
89.
90.
RI PT
AC C
91.
SC
85.
M AN U
84.
TE D
83.
EP
82.
New Zealand Women Included in the Quality Audit Program of Breast Surgeons of Australia and New Zealand. Asian Pac J Cancer Prev. 2015 Apr 3;16(6):2465–72. Gurney JK, Sarfati D, Stanley J. Obscure etiology, unusual disparity: the epidemiology of testicular cancer in New Zealand. Cancer Causes Control. 2015 Feb 17;26(4):561–9. Lawrenson R, Lao C, Obertová Z, Brown C, Holmes M, Tyrie L, et al. Management and characteristics of patients with metastatic prostate cancer in a cohort of New Zealand men. Oncology. 2015;88(3):157–63. Obertová Z, Scott N, Brown C, Stewart A, Lawrenson R. Survival disparities between Māori and non-Māori men with prostate cancer in New Zealand. BJU Int. 2015 Apr 1;115:24–30. Seneviratne S, Campbell I, Scott N, Shirley R, Peni T, Lawrenson R. Accuracy and completeness of the New Zealand Cancer Registry for staging of invasive breast cancer. Cancer Epidemiol. 2014 Oct 1;38(5):638–44. Signal V, Sarfati D, Cunningham R, Gurney J, Koea J, Ellison-Loschmann L. Indigenous inequities in the presentation and management of stomach cancer in New Zealand: a country with universal health care coverage. Gastric Cancer. 2015 Apr 15;18(2):1–9. Laurvick CL, Semmens JB, Holman CDJ, Leung YC. Ovarian cancer in Western Australia (1982-98): incidence, mortality and survival. Aust N Z J Public Health. 2003 Dec;27(6):588–95. Condon JR, Barnes T, Armstrong BK, Selva-Nayagam S, Elwood JM. Stage at diagnosis and cancer survival for Indigenous Australians in the Northern Territory. Med J Aust. 2005 Mar 21;182(6):277–80. Parker C, Tong SYC, Dempsey K, Condon J, Sharma SK, Chen JWC, et al. Hepatocellular carcinoma in Australia's Northern Territory: high incidence and poor outcome. Med J Aust. 2014 Oct 20;201(8):470–4. Supramaniam R, Gibberd A, Dillon A, Goldsbury DE, O'Connell DL. Increasing rates of surgical treatment and preventing comorbidities may increase breast cancer survival for Aboriginal women. BMC Cancer. 2014;14(1):163. Valery PC, Coory M, Stirling J, Green AC. Cancer diagnosis, treatment, and survival in Indigenous and non-Indigenous Australians: a matched cohort study. The Lancet. 2006;367(9525):1842–8. Coory MD, Green AC, Stirling J, Valery PC. Survival of Indigenous and nonIndigenous Queenslanders after a diagnosis of lung cancer: a matched cohort study. Med J Aust. 2008 May 19;188(10):562–6. Moore SP, Green AC, Garvey G, Coory MD, Valery PC. A study of head and neck cancer treatment and survival among indigenous and non-indigenous people in Queensland, Australia, 1998 to 2004. BMC Cancer. 2011;11(1):460. Dasgupta P, Baade PD, Aitken JF, Turrell G. Multilevel determinants of breast cancer survival: association with geographic remoteness and area-level socioeconomic disadvantage. Breast Cancer Res Treat. 2012 Apr 9;132(2):701–10. Cramb SM, Garvey G, Valery PC, Williamson JD, Baade PD. The first year counts: cancer survival among Indigenous and non-Indigenous Queenslanders, 1997–2006. Med J Aust. 2012 Mar 5;196(4):270–4.
92.
93.
94.
95.
22
ACCEPTED MANUSCRIPT
100.
101.
102.
103.
104.
RI PT
AC C
105.
SC
99.
M AN U
98.
TE D
97.
Moore SP, le C Green A, Bray F, Garvey G, Coory M, Martin J, et al. Survival disparities in Australia: an analysis of patterns of care and comorbidities among indigenous and non-indigenous cancer patients. BMC Cancer. 2014 Jul 18;14(1):1– 9. Diaz A, Moore SP, Martin JH, Green AC, Garvey G, Valery PC. Factors Associated With Cancer-Specific and Overall Survival Among Indigenous and Non-Indigenous Gynecologic Cancer Patients in Queensland, Australia: A Matched Cohort Study. Int J Gynecol Cancer. 2015 Mar 1;25(3):542–7. Cottrell J, Street J, Chong A, Roder D. Comparing cancer profiles and survival of aboriginal and non-aboriginal patients in South Australia: where are the opportunities for improving Aboriginal health? Asian Pac J Cancer Prev. 2007 Oct 1;8(4):495–501. Chong A, Roder D. Exploring differences in survival from cancer among Indigenous and non-Indigenous Australians: implications for health service delivery and research. Asian Pac J Cancer Prev. 2010;11(4):953–61. Luke C, Tracey E, Stapleton A, Roder D. Exploring contrary trends in bladder cancer incidence, mortality and survival: implications for research and cancer control. Intern Med J. 2010 May;40(5):357–62. Gillis DC, Irvine J, Tan L, Chiu S, Liu L, Robson D. Cancer incidence and survival of Saskatchewan northerners and registered Indians, 1967-1986. Arctic Med Res. 1991;Suppl:447–51. Irvine J, Gillis DC, Tan L, Chiu S, Liu L, Robson D. Lung, breast and cervical cancer incidence and survival in Saskatchewan northerners and registered Indians (1967-86). Arctic Med Res. 1991;Suppl:452–6. Sheppard AJ, Chiarelli AM, Marrett LD, Nishri ED, Trudeau ME. Stage at diagnosis and comorbidity influence breast cancer survival in First Nations women in Ontario, Canada. Cancer Epidemiol Biomarkers Prev. 2011 Oct;20(10):2160–7. Nishri ED, Sheppard AJ, Withrow DR, Marrett LD. Cancer survival among First Nations people of Ontario, Canada (1968-2007). Int J Cancer. 2014 Jun 13;136(3):639-45. Erickson B, Biron VL, Zhang H, Seikaly H, Côté DWJ. Survival outcomes of First Nations patients with oral cavity squamous cell carcinoma (Poliquin 2014). J Otolaryngol Head Neck Surg. 2015;44(1):4. Gomez SL, Le GM, West DW, Satariano WA, O'Connor L. Hospital policy and practice regarding the collection of data on race, ethnicity, and birthplace. Am J Public Health. 2003 Oct;93(10):1685–8. Robertson H, Lumley J, Berg S. How midwives identify women as aboriginal or Torres Strait Islanders. Aust Coll Midwives Inc J. 1995 Sep;8(3):26–9. Young MJ. Assessing the quality of identification of Aboriginal and Torres Strait Islander people in Western Australia Hospital Data, 2000. Health Information Occasional Paper 13. Health Department of Western Australia, Perth. Condon J, Zhao Y, Armstrong B, Barnes T. Northern Territory Cancer Register data quality, 1981-2001. NT Cancer Registry, the Cooperative Research Centre for Aboriginal Health, Charles Darwin University and the Menzies School of Health Research; 2004.
EP
96.
106.
107. 108.
109.
23
ACCEPTED MANUSCRIPT
114.
115.
116.
117.
118.
119.
RI PT
AC C
120.
SC
113.
M AN U
112.
TE D
111.
Cormack D, Robson B, Purdie G, Ratima M, Brown R. Access to cancer services for Maori: a report prepared for the Ministry of Health, Wellington School of Medicine and Health Sciences;2006. Johnson JC, Soliman AS, Tadgerson D, Copeland GE, Seefeld DA, Pingatore NL, et al. Tribal linkage and race data quality for American Indians in a state cancer registry. Am J Prev Med. 2009 Jun;36(6):549–54. Clegg LX, Reichman ME, Hankey BF, Miller BA, Lin YD, Johnson NJ, et al. Quality of race, Hispanic ethnicity, and immigrant status in population-based cancer registry data: implications for health disparity studies. Cancer Causes Control. 2007 Mar;18(2):177–87. Berrino F. The EUROCARE Study: strengths, limitations and perspectives of population-based, comparative survival studies. Ann Oncol. 2003 Dec 1;14(suppl 5):v9–v13. Howlader N, Ries LAG, Mariotto AB, Reichman ME, Ruhl J, Cronin KA. Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010 Oct 20;102(20):1584–98. German RR, Fink AK, Heron M, Stewart SL, Johnson CJ, Finch JL, Yin D, Accuracy of Cancer Mortality Study Group. The accuracy of cancer mortality statistics based on death certificates in the United States. Cancer Epidemiol. 2011 Apr 30; 35(2):126-31. Coleman MP, Quaresma M, Berrino F, Lutz J-M, De Angelis R, Capocaccia R, et al. Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol. 2008 Aug;9(8):730–56. Coleman MP, Forman D, Bryant H, Butler J, Rachet B, Maringe C, et al. Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995–2007 (the International Cancer Benchmarking Partnership): an analysis of populationbased cancer registry data. The Lancet. 2011 Jan 8;377(9760):127–38. Coleman MP, Rachet B, Woods LM, Mitry E, Riga M, Cooper N, et al. Trends and socioeconomic inequalities in cancer survival in England and Wales up to 2001. Br J Cancer. 2004 Apr 5;90(7):1367–73. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA: A Cancer Journal for Clinicians. 2012 Jan 4;62(1):10–29. Rosenberg HM, Maurer JD, Sorlie PD, Johnson NJ, MacDorman MF, Hoyert DL, et al. Quality of Death Rates by Race and Hispanic Origin: A summary of Current Research, 1999. Vital Health Stat 2. 1999 Sep 24;128:1–20. Condon JR, Zhang X, Baade P, Griffiths K. Cancer survival for Aboriginal and Torres Strait Islander Australians: a national study of survival rates and excess mortality. Popul Health Metr. 2014 Jan 31;12(1). Hill S, Sarfati D, Blakely T, Robson B, Purdie G, Dennett E, et al. Ethnicity and management of colon cancer in New Zealand: do indigenous patients get a worse deal? Cancer. 2010 Jul 1;116(13):3205–14. Seneviratne S. Impact of mammographic screening on ethnic and socioeconomic inequities in breast cancer stage at diagnosis and survival in New Zealand: a cohort study. BMC Public Health. 2015 Feb 2;15(46):1–10. Cetin K, Ettinger DS, Hei Y-J, O’Malley CD. Survival by histologic subtype in
EP
110.
121.
122.
123.
124.
24
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
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stage IV nonsmall cell lung cancer based on data from the Surveillance, Epidemiology and End Results Program. Clin Epidemiol. 2011;3(1):139–48. Lee DJ, Tannenbaum SL, Koru-Sengul T, Miao F, Zhao W, Byrne MM. Native American Race, Use of the Indian Health Service, and Breast and Lung Cancer Survival in Florida, 1996–2007. Prev Chronic Dis. 2014 Mar 6;11:130162–6.
25
ACCEPTED MANUSCRIPT
RI PT
Tables Table 1. Basic characteristics of reviewed articles, listed chronologically by country (n=83). Region
Indigenous groupa
Years of diagnosis
2003
Western Australia
Aboriginal
1982-1998
Condon, JR(15)
2005
Northern Territory
Indigenous
1991-2001
Condon, JR(88) Valery, PC(91) Cottrell, J(98) Coory, MD(92)
2005 2006 2007 2008
Northern Territory Queensland South Australia Queensland
Indigenous Indigenous Aboriginal Indigenous
1991-2000 1997-2002 1977-2003 1997-2002
Chong, A(99)
2010
South Australia
Indigenous
1977-2007
Luke, C(100) Moore, SP(93) Dasgupta, P(94) Cramb, S(95)
2010 2011 2012 2012
South Australia Queensland Queensland Queensland
Aboriginal Indigenous Indigenous Indigenous
1980-2004 1998-2004 1997-2006 1997-2006
Condon, JR(121)
2014
National
Indigenous
1991-2005
Moore, SP(96)
2014
Queensland
Parker, C(89)
2014
Supramaniam, R(90) Diaz, A(97) Canada Gillis, DC(101) Irvine, J(102) Sheppard, AJ(103)
M AN U
TE D
EP
AC C
Cancer(s)
Ovary Breast, cervix, colon and rectum, esophagus, leukemia, liver, lung, lymphoma, nasopharyngeal, pancreas, thyroid, uterus Breast, cervix, colon and rectum, lung, NHL All cancers combined All cancers combined Lung All cancers combined, breast, cervix, colon and rectum, lung, unknown primary site Bladder Head and neck Breast All cancers combined All cancers combined, anus, bladder, breast, cervix, colorectal, head and neck, Hodgkin lymphoma, kidney, leukemia, liver, lung, melanoma, NHL, ovary, pancreas, prostate, stomach, testis, thyroid, unknown primary site, uterus All cancers combined, breast, central nervous system, cervix, colorectal and small intestine, corpus uteri, esophagus, head and neck, liver, lung and bronchus, lymphoma and leukemia, melanoma, ovary, pancreas, prostate, renal tract, stomach, thyroid, unknown primary site
SC
Publication year
First author Australia Laurvick, CL(87)
Indigenous
1998-2004
Indigenous
2000-2011
Liver
2014 2015
Northern Territory (Top End) New South Wales Queensland
Aboriginal Indigenous
2001-2007 1998-2004
Breast Cervix, other gynecological, ovary, corpus uteri
1991 1991 2011
Saskatchewan Saskatchewan Ontario
Registered Indians Registered Indians First Nations
1967-1986 1967-1986 1995-2004
All cancers combined Breast, cervix, lung Breast
ACCEPTED MANUSCRIPT
Indigenous groupa First Nations First Nations
Years of diagnosis 1968-2001 1998-2009
1992 1994
Auckland National
Maori Maori
1976-1985 1976-1986
Gill, AJ(67)
2002
National
Maori
1995-1997
Phillips, ARJ(68)
2002
National
Maori
1988-1997
Jeffreys, M(69)
2005
National
Maori
1994-2002
Haynes, R(70) Sneyd, MJ(71) Brewer, N(72) Hill, S(122) McLeod, M(74) Priest, P(75) Sammour, T(76) Brewer, N(77) Brewer, N(78) Swart, EM(79) Sarfati, L(80) Campbell, ID(81) Gurney, JK(82) Lawrenson, R(83) Obertova, Z(84) Seneviratne, S(123) Signal, V(86) United States
2008 2008 2009 2010 2010 2010 2010 2011 2012 2013 2014 2014 2015 2015 2015 2015 2015
National National National National National National National National National North Island National National National Midland National Waikato North Island
Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori
Bleed, DM(26)
1992
Montana
Sugarman, JR(27)
1994
Baquet, C(28)
1996
Frost, F(29)
1996
M AN U
TE D
EP
AC C
Seattle-Puget Sound New Mexico/Arizona New Mexico/Arizona
Cancer(s) Breast, cervix, colorectal, lung, prostate Oral cavity squamous cell carcinoma
RI PT
Region Ontario Alberta
Breast Kidney Esophagus, liver, pancreas, stomach, upper gastrointestinal tract, biliary tree Pancreas Bladder, brain, breast, cervix, colon and rectum, esophagus, liver, lung, melanoma, ovary, pancreas, prostate, thyroid, uterus Breast, colon and rectum, lung, melanoma, prostate Prostate Cervix Colon and rectum Cervix Cervix Colon and rectum Cervix Cervix Rectal Stomach and liver combined Breast Testis Prostate Prostate Breast Stomach
SC
Publication year 2014 2015
First author Nishri, ED(104) Erickson, B(105) New Zealand Lethaby, AE(65) Delahunt, B(66)
1994-2004 1996-1999 1994-2005 1996-2003 1996-2006 2000-2002 1996-2003 1994-2005 1994-2005 2006-2008 2006-2008 1998-2010 2000-2011 2009-2012 1996-2010 1999-2012 2006-2008
American Indians
1982-1987
All cancers combined, breast, cervix, gallbladder, lung, prostate
American Indians
1974-1989
Breast, cervix, colon and rectum, lung, prostate
American Indians
1975-1984
Breast, colon and rectum, gallbladder, kidney, liver, lung, NHL, pancreas, prostate, stomach
American Indians
1973-1992
Breast 27
ACCEPTED MANUSCRIPT
Years of diagnosis 1983-1992 1969-1992 1969-1993
1998
New Mexico/Arizona
American Indians
1969-1994
Gilliland, FD(34)
1998
New Mexico
American Indians
1969-1994
Dennis, TD(35)
2000
Montana
American Indians
1984-1993
Clegg, L(36)
2002
9 SEER Registries
AI/AN
Li, CI(37) Biggs, ML(38)
2003 2004
11 SEER Registries 12 SEER Registries
American Indians AI/AN
1992-1998 1973-1999
Jemal, A(25)
2004
12 SEER Registries
AI/AN
1992-2000
Chien, C(39) Wampler, NS(40) Cormier, JN(41) Goggins, WB(42) Wang, SJ(43) Harper, S(44) Tehranifar, P(45) Fesinmeyer, MD(46) Yu, G(47) Cetin, K(124) Cueto, CV(49)
2005 2005 2006 2007 2007 2009 2009 2010 2010 2011 2011
11 SEER Registries 11 SEER Registries 11 SEER Registries 17 SEER Registries 13 SEER Registries 13 SEER Registries 12 SEER Registries 17 SEER Registries 13 SEER Registries 9 SEER Registries 17 SEER Registries
Du, X(50)
2011
Ooi, SL(51) Smith, CB(52) Wu, X(53) Singh, GK(54)
2011 2011 2011 2012
M AN U
TE D
Gilliland, FD(33)
Cancer(s) Prostate Uterus Colon and rectum Bladder, brain, breast, cervix, colon and rectum, esophagus, gallbladder, head and neck, Hodgkins lymphoma, kidney, larynx, leukemia, liver, lung, melanoma, NHL, ovary, pancreas, prostate, stomach, testis, thyroid, uterus Prostate All cancers combined, breast, colon and rectum, lung, prostate All cancers combined, breast, colon and rectum, lung, prostate Breast Testis All cancers combined, bladder, buccal cavity and pharynx, brain, breast, cervix, colon and rectum, esophagus, gallbladder, kidney, larynx, leukemia, liver, lung, melanoma, myeloma, NHL, ovary, pancreas, prostate, stomach, thyroid, uterus Colon and rectum Breast Melanoma Breast, colon and rectum, liver, lung, prostate, stomach Lung Breast All cancers combined Lung Thyroid Lung Colon and rectum Bladder, breast, cervix and uterus, colon and rectum, lung, melanoma, ovary, prostate Breast Lung Melanoma Cervix
RI PT
Indigenous groupa American Indians AI/AN Alaska Natives
SC
Region New Mexico New Mexico Alaska
1975-1997
AI/AN AI/AN AI/AN AI/AN AI/AN AI/AN AI/AN AI/AN American Indians AI/AN AI/AN
1988-2000 1973-1996 1992-2002 1991-2003 1988-1995 1992-2003 1995-1999 1973-2006 1992-2004 1988-2001 1992-2003
15 SEER Registries
AI/AN
1973-2003
17 SEER Registries 17 SEER Registries 17 SEER Registries 17 SEER Registries
AI/AN AI/AN AI/AN AI/AN
2000-2006 1988-2006 1999-2006 2000-2007
EP
Publication year 1996 1997 1998
AC C
First author Gilliland, FD(30) Schiff, M(31) Brown, M(32)
28
ACCEPTED MANUSCRIPT
2012
Kelly, JJ(56)
2012
Taghavi, S(57) Dwojak, SM(59) Tannenbaum, SL(60) Dwojak, SM(58)
2012 2013 2013 2014
Javid, SH(62)
2014
Lee, DJ(125)
2014
Mahdi, H(64)
2014
Indigenous groupa
Years of diagnosis
AI/AN
1973-2003
Alaska Natives
2005-2009
AI/AN AI/AN Native American AI
2004-2007 1996-2007 1996-2007 1999-2009
AI/AN
1996-2005
Cancer(s)
RI PT
Kaya, M(55)
Region Unknown number of SEER Registries Alaska Tumour Registry and SEER 18 SEER Registries 17 SEER Registries Florida South Dakota Unknown number of SEER Registries Florida Unknown number of SEER Registries
Multiple myeloma
Colorectal
Signet ring carcinoma, gastric adenocarcinoma Hypopharynx and larynx, oral cavity, oropharynx Breast Head and neck squamous cell carcinoma
SC
Publication year
M AN U
First author
Breast, colon, lung, prostate
Native American
1996-2007
Breast, lung
AI/AN
1988-2009
Endometrial adenocarcinoma
AC C
EP
TE D
Tannenbaum,um, 2014 Florida Native American 1996-2007 Non-small cell lung cancer SL(61) a Using the nomenclature used in the paper, unless not specified, in which nomenclature for the Indigenous group was inferred by DW. AI/AN: American Indian/Alaska Native; NHL: non-Hodgkin lymphoma; SEER: Surveillance, Epidemiology and End Results
29
ACCEPTED MANUSCRIPT
Mortality outcome(s)
Method for relative estimate of survival
2003 2005 2005
All-cause Cause-specific Cause-specific
N/A N/A Other
Cox PH Cox PH Cox PH
Valery, PC(91)
2006
Cause-specific
N/A
Cox PH
Cottrell, J(98)
2007
All-cause
Kaplan-Meier
N/A
Coory, MD(92)
2008
Cause-specific
N/A
Chong, A(99) Luke, C(100)
2010 2010
Kaplan-Meier N/A
Moore, SP(93)
2011
Cause-specific Cause-specific All-cause, causespecific and noncancer
Dasgupta, P(94)
2012
Cause-specific
N/A
Cramb, S(95)
2012
Condon, JR(121)
2014
Actuarial Relative survival ratio
Moore, SP(96)
2014
Parker, C(89)
2014
Cause-specific Excess mortality and cause-specific All-cause, causespecific and noncancer All-cause
Supramaniam, R(90)
2014
Cause-specific
Diaz, A(97)
2015
Cause-specific and N/A all-cause
Cox PH Cox PH
Cox PH
EP
TE D
Other
Cox PH Cox PH & Poisson
Kaplan-Meier
Cox PH
Kaplan-Meier Cumulative mortality curve
Cox PH
AC C
Canada
Cox PH
N/A
Covariates
Age, histology, SES, location of residence Age, sex Age, stage Age, stage, sex, period of dx, surgery, radiotherapy, chemotherapy, place of residence, cancer site, remoteness Age, sex, cancer site Age, stage, sex, treatment, surgery, radiotherapy, histology, chemotherapy, comorbidity, rurality Age, sex, period of dx, geographic region, metropolitan vs. non Age, period of dx, SES, geographic region, birthplace
M AN U
First author Australia Laurvick, CL(87) Condon, JR(15) Condon, JR(88)
SC
Publication year
Method for absolute estimate of survival
RI PT
Table 2. Mortality outcomes, analytic approaches to survival and covariates in reviewed articles, listed chronologically by country.
Cox PH
Age, stage, sex, treatment, surgery, radiotherapy, chemotherapy, comorbidity, location of residence
Age, stage, SES, geographical remoteness, occupation, marital status Age, sex, SES, geographic remoteness, broad cancer group Age, sex, location of residence, period of dx Age, stage, sex, cancer site, location of residence, SES, comorbidity, treatment Age, sex, cirrhosis Age, period of dx, disease spread, co-morbidity, surgery, location of residence, SES
Cox PH
Stage, location of residence, SES, treatment, co-morbidity
Actuarial
N/A
Age, sex
Not stated
N/A
Sex Age, stage, period of dx, comorbidity, treatment hospital, proximity to treatment, BMI, smoking Age
Gillis, DC(101)
1991
Irvine, J(102)
1991
All-cause and cause-specific Cause-specific
Sheppard, AJ(103)
2011
All-cause
N/A
Cox PH
Nishri, ED(104)
2014
All-cause and
Actuarial
Flexible
ACCEPTED MANUSCRIPT
Mortality outcome(s) cause-specific
Erickson, B(105)
2015
All-cause and cause-specific
New Zealand Lethaby, AE(65) Delahunt, B(66) Gill, AJ(67) Phillips, ARJ(68)
1992 1994 2002 2002
Cause-specific All-cause All-cause All-cause
Jeffreys, M(69)
2005
Excess mortality
Haynes, R(70) Sneyd, MJ(71) Brewer, N(72)
2008 2008 2009
Hill, S(122)
Cox PH Cox PH N/A Cox PH N/A
All-cause Cause-specific Cause-specific
N/A Actuarial Kaplan-Meier Kaplan-Meier Relative survival ratio N/A Kaplan-Meier N/A
2010
Cause-specific
Kaplan-Meier
McLeod, M(74) Priest, P(75) Sammour, T(76) Brewer, N(77)
2010 2010 2010 2011
Cause-specific All-cause All-cause Cause-specific
Kaplan-Meier Not stated Kaplan-Meier N/A
Cox PH Cox PH Cox PH Cox PH
Brewer, N(78)
2012
Cause-specific
N/A
Cox PH
Swart, EM(79)
2013
Sarfati, L(80)
2014
Cause-specific All-cause and cause-specific
2014
Gurney, JK(82)
2015
Lawrenson, R(83)
2015
Obertova, Z(84)
2015
Cause-specific
All-cause and cause-specific All-cause All-cause and cause-specific
None stated None stated Age, sex, SES, distance to major hospital None stated
N/A
Age, stage
Cox PH Cox PH Cox PH
N/A
Cox PH
Age, stage, sex Age, Gleason score Age, stage, period of dx, rurality, grade Age, stage, sex, period of dx, surgery, chemotherapy, comorbidity, rurality, grade, smoking, emergency presentation Age, stage, treatment, surgery, radiotherapy Age, stage Age, stage, sex, subsite Age, stage, period of dx, SES, comorbidity, rurality Age, registration year, SEP, screening history, co-morbidity, travel time to nearest GP and cancer centre Age, stage, tumour grade
Kaplan-Meier
Cox PH
Age, sex, site, stage, SES, location of residence, co-morbidity
Kaplan-Meier
Cox PH
Age, remoteness, histology, tumour size, tumour grade, nodal status, estrogen and progesterone receptor status, HER-2 receptor status, phenotype, vascular invasion, tumour location, laterality, cancer foci, period of dx, referral type, annual surgeon case load
Kaplan-Meier
Cox PH
Age, stage of disease, SES, location of residence
Other
Cox PH
Age, ethnicity, androgen deprivation therapy (ADT) use
Kaplan-Meier
Cox PH
Age, period of dx, SES, location of residence
Cox PH
TE D
EP
AC C
Campbell, ID(81)
Age, stage, gender, tumour subsite, treatment, smoking
M AN U
Kaplan-Meier
RI PT
Publication year
Method for relative estimate of survival Covariates parametric survival models
SC
First author
Method for absolute estimate of survival
31
ACCEPTED MANUSCRIPT
Method for relative estimate of survival
Publication year
Seneviratne, S(123)
2015
Cause-specific
Kaplan-Meier
Cox PH
Screening, SES
Signal, V(86) United States
2015
Cause-specific
N/A
Cox PH
Age, sex, stage, tumour site, co-morbidity
Bleed, DM(26)
1992
Excess mortality
Sugarman, JR(27)
1994
All-cause
Baquet, C(28)
1996
Excess mortality
Frost, F(29)
1996
Gilliland, FD(30)
1996
All-cause, causespecific and excess mortality All-cause
Schiff, M(31)
1997
Excess mortality
Brown, M(32)
1998
All-cause
Gilliland, FD(33)
1998
Excess mortality
Gilliland, FD(34)
1998
Excess mortality
Dennis, TD(35) Clegg, L(36) Li, CI(37) Biggs, ML(38) Jemal, A(25) Chien, C(39)
2000 2002 2003 2004 2004 2005
All-cause Cause-specific All-cause Cause-specific Cause-specific Cause-specific
Wampler, NS(40)
2005
Cause-specific
Cormier, JN(41)
2006
Goggins, WB(42)
2007
Wang, SJ(43)
2007
Relative survival ratio
All-cause and cause-specific All-cause and cause-specific Excess mortality (conditional)
EP
SC
Cox PH
None stated
Age, sex, treatment, rurality
N/A
None stated
Cox PH
Stage, treatment, marital status, location of residence, treatment delay
Cox PH
Age, stage, period of dx, treatment, histology
N/A
None stated
TE D
N/A Relative survival ratio Actuarial Relative survival ratio Relative survival ratio Actuarial Kaplan-Meier N/A Kaplan-Meier Kaplan-Meier N/A
N/A
Covariates
M AN U
Relative survival ratio Other Relative survival ratio
RI PT
First author
AC C
Mortality outcome(s)
Method for absolute estimate of survival
Cox PH
Age, stage, sex, period of dx
Cox PH
Age, stage, sex, treatment
N/A
Stage
N/A Cox PH Cox PH Cox PH Cox PH Cox PH
Age, sex, period of dx, geographic region, cancer site Age, stage Age, stage, surgery, radiotherapy, registry, hormone status Age, stage, period of dx, histology, registry, marital status Age, stage Age, stage, period of dx, surgery, radiotherapy, registry Age, stage, period of dx, treatment, geographical region, marital status, tumor size, metastases, lymph node involvement Age, stage, sex, period of dx, histology, geographic region, marital status, cancer site Age, stage, sex, period of dx, histology, registry, grade, hormone status, tumor size
N/A
Cox PH
Kaplan-Meier
Cox PH
N/A
Cox PH
Relative survival ratio
N/A
Age, stage, sex, histology
32
ACCEPTED MANUSCRIPT
Covariates Age Age, stage, sex, SES, amenability to treatment Age, stage, sex, surgery, registry None stated Age, sex, period of dx, treatment, histology Age, stage, sex, period of dx, treatment, surgery, radiotherapy
Kaplan-Meier
Cox PH
Age, sex, treatment, surgery, radiotherapy, health insurance
Publication year 2009 2009 2010 2010 2011 2011
Du, X(50)
2011
Ooi, SL(51)
2011
Cause-specific
N/A
Smith, CB(52) Wu, X(53)
2011 2011
Cause-specific Cause-specific
Singh, GK(54)
2012
Excess mortality
Kaya, M(55)
2012
Not stated
Kelly, JJ(56) Taghavi, S(57) Dwojak, SM(59)
2012 2012 2013
Excess mortality Cause-specific All-cause
Kaplan-Meier Kaplan-Meier Relative survival ratio Kaplan-Meier and Other Actuarial N/A Kaplan-Meier
Tannenbaum, SL(60)
2013
All-cause
Kaplan-Meier
Dwojak, SM(58)
2014
All-cause
Javid, SH(62)
2014
Cause-specific
N/A
Extended Cox model
Lee, DJ(125)
2014
All-cause
N/A
Cox PH
Mahdi, H(64)
2014
Kaplan-Meier
Cox PH
Tannenbaum, SL(61)
2014
Kaplan-Meier
N/A
All-cause and cause-specific All-cause
M AN U
SC
First author Harper, S(44) Tehranifar, P(45) Fesinmeyer, MD(46) Yu, G(47) Cetin, K(124) Cueto, CV(49)
Cox PH N/A
Age, stage, period of dx, surgery, radiotherapy, SES, registry, hormone status Age, stage Stage, histology
N/A
None stated
Cox PH
Age, period of dx
EP
TE D
Cox PH
Not stated
RI PT
Method for relative estimate of survival N/A Cox PH Cox PH N/A Cox PH Cox PH
AC C
Mortality outcome(s) Cause-specific Cause-specific All-cause All-cause All-cause Cause-specific All-cause and cause-specific
Method for absolute estimate of survival Kaplan-Meier Kaplan-Meier Kaplan-Meier Not stated Kaplan-Meier N/A
N/A Cox PH Cox PH Cox PH
Cox PH
None stated Age, stage, surgery, radiotherapy, grade Age, sex, stage, period of dx, surgery, radiotherapy Age, stage, marital status, insurance, tobacco use, location of residence, teaching hospital and volume, grade, lymph node status, treatment, co-morbidity Age, sex, stage, location of residence, co-morbidity, alcohol, smoking, insurance, co-morbidity Age, stage, SEER registry, period of dx, co-morbidity Age, sex, stage, grade, SES, marital status, smoking, comorbidity, insurance, lymph node status, treatment, histology Age, stage, grade, histology, extent of lymphadenectomy, radiation N/A
Abbreviations: N/A: Not applicable; Cox PH: Cox Proportional Hazards; Period of dx: Period of diagnosis (e.g. calendar year); BMI: Body Mass Index; SES: Socioeconomic status
33
ACCEPTED MANUSCRIPT
Table 3. Summary of potential sources of information bias and the extent to which they were acknowledged in the included literature. n (%) 78 (100) 46 (59) 30 (38) 9 (12) 25 (32) 13 (17)
RI PT
All mortality outcomes Total Acknowledgement of potential ethnic misclassification? Acknowledgement of potential incomplete case ascertainment? Acknowledgement this could be differential by ethnicity? Acknowledgement of potential incomplete death ascertainment? Acknowledgement this could be differential by ethnicity? Cause-specific survival Total Definition provided of a cancer death?
11 (100) 7 (64) 2 (18) 0 (0)
AC C
EP
TE D
M AN U
SC
Comment on the completeness and/or validity of cause of death classification? Excess mortality Total Information provided about elements life tables were specific to? Life tables specific to geographic region of cases? Life tables specific to calendar time?
49 (100) 14 (29) 12 (24)
34
RI PT
ACCEPTED MANUSCRIPT
Figure 1. Flow diagram of literature review process for identifying studies of cancer survival in indigenous populations.
M AN U
SC
Records identified through database search n=1503 MEDLINE n=402 / Embase n=697 / Web of Science n=404
Duplicates removed n=811
Deemed ineligible n=554
EP
TE D
Title and abstract screening n=692
AC C
Full-text assessment n=138
Included in review N=83
Deemed ineligible N=55
ACCEPTED MANUSCRIPT
APPENDIX A: Search Strategy Table 1. MEDLINE search strategy. Three theme-specific searches were combined with “AND”. Indigenous autochton$.mp. OR indigenous$.mp. OR Amerind$.mp. OR (American adj1 indian).mp. OR (native adj1 canadian?).mp. OR inuit?.mp. OR exp Eskimo/ OR Eskimo?.mp. OR Inuktitut.mp. OR Nunavut?.mp. OR Nunavik.mp. OR First Nation?.mp. OR Dene.mp. OR Metis.mp. OR Indians, North American/ OR American Native Continental Ancestry Group/ OR (native adj1 american?).mp. OR ojibway.mp. OR Mohawk.mp. OR Cree.mp. OR yupik.mp. OR aleut.mp. OR (native? adj1 people?).mp. OR (American? adj1 indian?).mp. OR (Alaska? adj1 native?).mp. OR (Aboriginal? adj1 Canadian?).mp. OR (native? Adj1 Hawaii?).mp. OR “Canadian Aboriginals”.mp. OR Aborigin?.mp. OR Oceanic Ancestry Group/ OR “torres strait”.mp. OR maori?.mp. OR Koori$1.mp. OR ngunnawal.mp. OR murri.mp. OR murrdi.mp. OR nyungar.mp. OR yamatji.mp. OR wangai.mp. OR nunga.mp. OR anangu.mp. OR yapa.mp. OR yolngu.mp. OR tiwi.mp. OR anindilyakwa.mp. OR Palawan.mp. Search limited to yr="1990 -Current" where “Current” was September Week 1 2015.
RI PT
Survival Exp Disease-Free Survival/ OR exp Survival Analysis/ OR exp Survival OR exp Survival Rate/ OR survival.mp, ab, sh, ti.
M AN U
SC
Cancer Cancer*.mp. OR exp neoplasm/
Table 2. Embase search strategy. Three theme-specific searches were combined with “AND”. Survival exp event free survival/ OR exp cause specific survival/ OR exp survival/ OR exp survival time/ OR survival*.mp. exp overall survival/ OR exp cancer survival/ OR exp survival rate/ OR exp progression free survival/ OR exp disease free survival/
Indigenous autochton$.mp. OR indigenous$.mp. OR Amerind$.mp. OR (American adj1 indian).mp. OR (native adj1 canadian?).mp. OR inuit?.mp. OR exp Eskimo/ OR Eskimo?.mp. OR Inuktitut.mp. OR Nunavut?.mp. OR Nunavik.mp. OR First Nation?.mp. OR Dene.mp. OR Metis.mp. OR exp American Indian/ OR American Native Continental Ancestry Group/ OR (native adj1 american?).mp. OR ojibway.mp. OR Mohawk.mp. OR Cree.mp. OR yupik.mp. OR aleut.mp. OR (native? adj1 people?).mp. OR (American? adj1 indian?).mp. OR (Alaska? adj1 native?).mp. OR (Aboriginal? adj1 Canadian?).mp. . OR (native? Adj1 Hawaii?).mp. OR “Canadian Aboriginals”.mp. OR Aborigin?.mp. OR Oceanic Ancestry Group/ OR “torres strait”.mp. OR maori?.mp. OR Koori$1.mp. OR ngunnawal.mp. OR murri.mp. OR murrdi.mp. OR nyungar.mp. OR yamatji.mp. OR wangai.mp. OR nunga.mp. OR anangu.mp. OR yapa.mp. OR yolngu.mp. OR tiwi.mp. OR anindilyakwa.mp. OR Palawan.mp. Search limited to yr="1990 -Current" where “Current” was September Week 1 2015.
AC C
EP
TE D
Cancer Cancer*.mp. OR exp neoplasm/
ACCEPTED MANUSCRIPT
Table 3. Web of Science search strategy. Three theme-specific searches were combined with “AND”. Survival Topic=(survival) OR Title=(survival)
Indigenous Topic=(autochton*) OR Topic=(indigenous*) OR Topic=(amerind*) OR Topic=(american$ near/1 indian$) OR Topic=(native$ near/1 canadian$) OR Topic=(inuit$) OR Topic=(eskimo$) OR Topic=(inuktitut) OR Topic=(Nunavut*) OR Topic=(Nunavik) OR Topic=("First Nation$") OR Topic=(Dene) OR Topic=(M?tis) OR Topic=(native$ near/1 american$) OR Topic=(ojibway) OR Topic=(mohawk*) OR Topic=(yupik) OR Topic=(aleut) OR Topic=("native people$") OR Topic=(alaska* near/1 native$) OR Topic=(Aboriginal$ near/1 Canadian$) OR Topic=(native$ near/1 Hawaii*) OR Topic=(Aborigin*) OR Topic=("oceanic ancestry") OR Topic=("torres strait") OR Topic=(maori*) OR Topic=(Koori*) OR Topic=(Ngunnawal) OR Topic=(murri) OR Topic=(murrdi) OR Topic=(nyungar) OR Topic=(yamatji) OR Topic=(wangai) OR Topic=(nunga) OR Topic=(anangu) OR Topic=(yapa) OR Topic=(yolngu) OR Topic=(tiwi) OR Topic=(palawan) Search limited to yr="1990 -Current" where “Current” was September Week 1 2015.
AC C
EP
TE D
M AN U
SC
RI PT
Cancer Topic=(cancer*) OR Title=(cancer*)
S1047-2797(16)30166-1
DOI:
10.1016/j.annepidem.2016.06.007
Reference:
AEP 7967
To appear in:
Annals of Epidemiology
Received Date: 24 March 2016 Revised Date:
27 May 2016
Accepted Date: 6 June 2016
Please cite this article as: Withrow DR, Racey CS, Jamal S, A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Population, Annals of Epidemiology (2016), doi: 10.1016/ j.annepidem.2016.06.007. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Authors: Diana R. Withrow1,2, C. Sarai Racey2, Sehar Jamal1
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A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Populations
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Affiliations: 1 Aboriginal Cancer Control Unit, Cancer Care Ontario, Toronto, Ontario 2 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario
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Running title: Review of cancer survival studies in indigenous populations Financial support: Diana Withrow was supported by a Canadian Institutes of Health Research Doctoral Award (Code 201110DQU-265978-206086)
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Corresponding author: Diana R. Withrow Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics National Cancer Institute, National Institutes of Health 9609 Medical Center Drive, Room 7E590 Rockville, MD 20850 Email: [email protected] Phone: 240-276-7869 Conflicts of interest: None
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Article category: Review Words: 4,405 Tables: 3 Figures: 1 References: 125
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Title: A Critical Review of Methods for Assessing Cancer Survival Disparities in Indigenous Population Abstract
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An increasing cancer burden among Indigenous populations has led to a growing literature about survival disparities between Indigenous and non-Indigenous persons. We aim to describe and appraise methods used to measure cancer survival in Indigenous persons in the United States, Canada, Australia and New Zealand. We searched Medline, Web of Science and EMBASE for articles published between 1990 and 2015 that estimated survival in populations Indigenous to one of these four countries. We gathered information about data sources, analytical methods, and the extent to which threats to validity were discussed. The search retrieved 83 articles. The most common approach to survival analysis was cause-specific survival (n=49). Thirty-eight articles measured all-cause survival and 11 measured excess mortality attributable to cancer (relative survival). Three sources of information bias common to all studies (ethnic misclassification, incomplete case ascertainment and incomplete death ascertainment) were acknowledged in a minority of articles. The methodological considerations we present here are shared with studies of cancer survival across other sub-populations. We urge future researchers on this and related topics to clearly describe their data sources, to justify analytic choices and to fully discuss the potential impact of those choices on the results and interpretation. Words: 196
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Keywords: Neoplasms; Survival Analysis; Indians, North American; Oceanic Ancestry Group; Health Status Disparities; Healthcare Disparities
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List of Abbreviations and Acronyms
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AI
American Indian
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AI/AN
American Indian/Alaska Native
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DCO
Death Certificate Only
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IHS
Indian Health Service
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RSR
Relative Survival Ratio
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SEER
Surveillance, Epidemiology and End Results
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Introduction
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Progress in and priorities for cancer control can be identified through a variety of metrics of
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cancer burden including incidence, mortality, prevalence, person years of life lost and survival.
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Cancer survival in particular can act as a metric of the overall effectiveness of health care
5
services and the management of cancer patients. Disparities in cancer survival between
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subpopulations can illustrate the need for action and provide insight into which interventions
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might have the greatest impact for reducing the burden of cancer within those populations.
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Notable disparities in health exist between Indigenous and non-Indigenous populations with
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Indigenous persons being, on average, less healthy than their non-Indigenous peers.(1-4) The
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validity of metrics of cancer burden in these populations is threated by, among other factors, the
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varying validity of ethnic identifiers population cancer registries. Notwithstanding this limitation,
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it appears that cancer incidence was historically lower among Indigenous populations than
13
among non-Indigenous populations(5-9) and that over time, incidence of and mortality from
14
cancer have been increasing among Indigenous populations to meet if not exceed rates in the
15
general population.(5,9-15)
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Increasing attention paid to Indigenous health(16,17) and evidence of the increasing burden of
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cancer amongst Indigenous populations has led to increasing documentation of cancer survival
18
disparities between Indigenous and non-Indigenous persons. These studies aim to illustrate the
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extent of disparities, and to identify how inequalities are initiated and sustained.
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There is an extensive body of literature pertaining to the measurement and interpretation of
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cancer survival in general.(18-21) There is also an awareness that information bias can arise as a
22
result of improper ascertainment or classification of cancer cases or deaths(22-24). In this
23
review, we have examined the extent to which the issues raised in this more general literature are
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acknowledged and/or overcome in articles reporting on Indigenous cancer survival.
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In the absence of methodological rigor and thoughtful consideration of the implications of
26
methodological choices, the findings of these articles could be biased or misinterpreted.
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Directing resources and designing programs to reduce the cancer burden in Indigenous
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populations based on biased information will be at best inefficient and at worst ineffective. We
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therefore call attention to potential sources of bias and their consequences so that future authors
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can measure and interpret survival knowledgeably and so that future readers can appraise
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methods and interpret the findings of this research critically.
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The aim of this review is to describe and critically appraise the methods used to measure cancer
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survival in Indigenous populations in the US, Canada, Australia and New Zealand. We will
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discuss barriers to methodological rigor and their consequences and will suggest some ways to
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overcome common challenges, or at the least, to diminish their effect on validity. The
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methodological challenges that we identify and discuss here are common to studies of
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Indigenous cancer survival but are not specific to them. Our recommendations can therefore be
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applied more generally to Indigenous health research that uses administrative data and to
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comparisons of survival between other subgroups in a population.
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Methods
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We systematically searched Medline, Web of Science and EMBASE for articles published in
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English from January 1st, 1990 to September 4th, 2015. A broad search strategy used keywords
14
falling under three themes: cancer, survival, and Indigenousness. A detailed list of keywords,
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Medical Subject Headings and Emtree terms for each theme is provided in Appendix A. Based
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on titles and abstracts, those articles that appeared to have measured cancer survival in one of the
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target populations were retrieved in full text and assessed using the inclusion criteria described
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below.
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To be eligible for inclusion, articles had to be population-based or multi-centered and report an
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absolute or relative estimate of survival from one or more cancers in any of: American Indians
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and/or Alaska Natives (AI/AN) in the US; First Nations and/or Métis in Canada; Aboriginals
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and/or Torres Strait Islanders in Australia; or Maori in New Zealand. Indigenous populations in
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northern or arctic regions were excluded because of unique challenges to health care access and
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administrative record keeping imposed by their geographical remoteness. Alaska Natives were
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exempt from this exclusion because the Surveillance, Epidemiology and End Results (SEER)
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database, a commonly used data source in the US, does not distinguish between American
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Indians (AI) and Alaska Natives.
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If two or more articles were based on the same data (as many were due to the use of cancer
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registries), both were included if they were based on different years of diagnosis, included
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different cancers or covariates or employed different analytic approaches or survival endpoints.
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Studies that were never published as full-text articles (i.e. conference proceedings and abstracts)
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were excluded because the methods sections were insufficient.
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Once retrieved, descriptions of data sources and analytical methods were abstracted using a
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standardized data-collection form. Data were collected under three themes: descriptive
5
characteristics, which included the geographical setting, the Indigenous group, the comparison
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group and the cancers included; analytic approaches, which included the methodological
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approach to survival analysis and the covariates measured; and the potential for and discussion of
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bias, which included a tally of the articles that acknowledged the potential of ethnic
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misclassification, and incomplete death or case ascertainment. If there was ambiguity on any of
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these points, the article was reviewed with a second reviewer until consensus was reached.
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Results
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The literature search identified 1503 articles, of which 402 were from MEDLINE, 697 from
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Embase and 404 from Web of Science. After removing duplicate records, titles and abstracts of
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692 unique articles were screened for eligibility. Of these, 138 full-text articles potentially met
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the inclusion criteria and were retrieved and reviewed in full text. Fifty-five articles were
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excluded for the following reasons: they did not measure absolute or relative survival in a
17
candidate population, were based on a single clinical centre, measured childhood cancer survival
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only or were citing results from a previous study (see Figure 1).
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The general characteristics of the 83 articles included in this review are listed in Table 1. Articles
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on this topic are being published at an increasing frequency over time. We retrieved six articles
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meeting the inclusion criteria published between 1991 and 1995 whereas we retrieved 38 articles
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meeting the criteria published between 2011 and 2015.
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Of the 83 articles included, 40 were from the US(25-64). Articles from the US primarily covered
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regions participating in the SEER program. Three articles from Florida,(60,61,63) two articles
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from Montana,(26,35) and one article from South Dakota(58) were exceptions. Twenty-two of
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the 83 articles pertained to survival of the Maori in New Zealand,(65-86) and all but five of these
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were conducted at the national level.(65,79,83,85,86) Sixteen articles of 83 were based on
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Australian data and all but one were conducted within the boundaries of the five mainland states:
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Western Australia(87), the Northern Territory(15,88,89), New South Wales(90), Queensland(91-
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97) and South Australia(98-100). Five articles pertaining to First Nations in Canada were
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included in the review. These were published based on data from three of Ontario’s 13 provinces
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and territories: Saskatchewan(101,102), Ontario(103,104) and Alberta(105). There were not any
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articles presenting original survival estimates for more than one country.
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The mortality outcomes and statistical methods used to calculate and compare survival are
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outlined in Table 2. The most common outcome was cause-specific survival, used by 49 of 83
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articles. Thirty-eight articles used all-cause survival as a mortality outcome and 11 measured
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excess mortality attributable to cancer (relative survival).
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Fifty-six articles provided an absolute estimate of survival in an Indigenous population. Sixty-
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five articles measured survival in an Indigenous population relative to a non-Indigenous
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population, generating hazard or relative survival ratios. Articles acknowledged the potential for
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information bias to different extents, summarized in Table 3. For example, 46 of 83 articles
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touched upon the idea of potential ethnic misclassification in their data sources. A minority of
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articles alluded to case ascertainment (n=30) and death ascertainment (n=25).
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Discussion
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The approaches to measuring and comparing survival in Indigenous and non-Indigenous
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populations in the literature we reviewed varied, as did the extent to which authors
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acknowledged potential sources of information bias. It is understandable that every
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methodological consideration cannot be covered in detail in every paper. Nonetheless, it is our
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belief that analyses of cancer survival in Indigenous and non-Indigenous populations should be
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held to an epidemiologic standard consistent with the cancer survival literature in general. In this
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section, we begin by discussing the circumstances that give rise to, and potential consequences of
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information bias and the extent to which these were considered in the literature. We then
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consider the choice of survival measure and its implications for interpretation.
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Information bias
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In order to estimate and compare cancer survival within and between subgroups of a population
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without bias, all cancer cases and deaths (or all those in a representative sample of the
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population) must be ascertained and each cancer case must be correctly assigned to the subgroup
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to which they truly belong. Below, we discuss how three potential sources of information bias
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may violate these principles: ethnic misclassification, case ascertainment and death
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ascertainment.
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(i) Ethnic misclassification
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Ethnic misclassification occurs when an individual is assigned to an ethnic group to which he or
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she does not belong. Most papers (n=72) identified the source of their ethnicity data, most often
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the cancer registry, but the sources used to populate the cancer registry were poorly described.
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Many simply said that it was collected from the medical record, with no explanation as to how
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ethnicity was ascertained in the medical record.
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Ethnicity as recorded in the medical record is often based on a health provider’s subjective
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appraisal rather than self-report and, when self-report is used, patients may be hesitant to identify
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themselves as Indigenous(106-108). Errors that arise in the medical record as a result of
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subjectivity, inconsistency and/or response bias will perpetuate in the cancer registries they
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populate and typically result in an undercount of Indigenous cancer cases(36). In the Northern
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Territory of Australia, Condon et al. found that 15% of Indigenous persons were misclassified as
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non-Indigenous.(109) In New Zealand, 17% of Maori were misclassified as non-Maori upon
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cancer registration.(110) In the state of Michigan, linking Indian Health Service (IHS) records to
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the state cancer registry resulted in a 97% increase in cases classified as AI/AN and a linkage to
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a tribal register resulted in a further increase of 15%.(111)
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Ethnic misclassification results in biased estimates of survival on both the absolute scale and
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relative scale if misclassification is common (as has been described above) and those who are
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misclassified differ from those who were correctly classified in ways that are associated with
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survival. For example, a linkage of the Seattle-Puget Sound SEER registry to IHS records
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revealed that Native Americans misclassified as white by the SEER registry have better cancer
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survival compared to those that were correctly identified as Native American.(27)
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At a national level, Clegg et al. used the National Longitudinal Mortality Study to validate
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ethnicity as reported in SEER and found that survival time for AI/AN was substantially longer
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when based on self-reported AI/AN status compared to SEER classification.(112) In both these
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instances, ethnic misclassification was associated with survival and therefore introduced bias that
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had a meaningful impact on the results. Despite the evidence that ethnic misclassification occurs,
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only 46 of the 83 articles acknowledged the potential of ethnic misclassification in their studies.
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Linkage of cancer registries to databases such as the IHS or tribal registers will reduce ethnic
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misclassification and improve the validity of measures of cancer survival. Where routine linkage
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is unfeasible, further validation studies of ethnic identifiers in cancer registries could fill a
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significant gap in our understanding of the degree to which ethnic misclassification is occurring
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and provide insight into the potential consequences it has for estimation of cancer survival in
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Indigenous populations. Authors should report on the source files that populate the cancer
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registry, comment on the suspected validity of these sources and report the limitations associated
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with the use of these data sources.
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(ii) Case Ascertainment
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Case ascertainment refers to the proportion of all cancer cases resident in a registry’s catchment
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area that are captured by the registry. The completeness of case ascertainment varies by registry
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and potentially within subsets of the population covered by the registry. For example, in
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Montana, investigators used both the cancer registry and IHS medical records to find Indigenous
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cancer cases. Of the cases they found, 33% were included in the registry but absent from IHS
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records and 27% were identified based solely on IHS records(35). If the same Montana-based
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study had relied on either source exclusively, approximately one third of Indigenous cases would
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have been missed.
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Incomplete case ascertainment will result in biased estimates of survival on the absolute scale if
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survival of the ascertained cases is different than non-ascertained cases. Biased estimates of
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survival on the relative scale will arise if this error is differential across ethnicities. Of the
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articles we reviewed, just over a third (n=30) alluded to the general idea of case ascertainment
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and only 9 acknowledged that there could be differential case ascertainment by ethnicity.
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By nature of being unascertained, it is impossible for an investigator to compare survival
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between missing and included cases and determine whether bias is present. To consider this
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possibility however, like the study in Montana, investigators could use several sources to identify
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cancer cases in the Indigenous population and compare the survival of patients identified by each
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method.
28
In the absence of an alternative data set, the proportion of cases identified by death certificate
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only (DCO) can act as an indicator of the completeness of case ascertainment. DCO cases are
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those cancer cases that were identified solely because cancer was listed as the underlying cause
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of death on the death certificate but would otherwise be unknown to the registry. DCO cases are
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not typically included in survival analyses because their true date of diagnosis is unknown. The
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proportion of cases within a registry that are DCO is a measure of data quality typically reported
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by the registry.
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To crudely consider the extent to which differential case ascertainment across ethnicities may
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have biased comparisons of survival, the proportion of cases that are DCO should be reported by
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ethnicity if possible (i.e. if ethnicity is known based on the death certificate).(24) While in the
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general population, the proportion of DCO cases is likely to be small due to adherence to data
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quality standards at the registry-level, the proportion of DCO cases within ethnic subgroup smay
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be substantially higher and worthy of consideration. If the proportion of DCO cases within the
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subgroup of interest is large, and these cases are being excluded as a result of unknown survival
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time, survival may be biased. The direction of the bias will depend on the follow-up and trace-
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back practices of the registry as well as the traits that are associated with being DCO in that
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setting.(113)
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(iii) Validity of Cause of Death & Death Ascertainment
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Two outcomes may be of interest in cancer survival analyses: the fact of death (did this person
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die?) and the cause of death (how?). Death ascertainment refers to the completeness of fact of
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death, and will affect all cancer survival measures. High rates of loss to follow-up (low death
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ascertainment) will lead to biased estimates of survival on the absolute scale if those who are lost
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are systematically more or less likely to survive than those who are not. As with case
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ascertainment, loss to follow-up will only cause bias in relative estimates of survival if it is
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associated with both survival and ethnicity. Of the 83 articles we reviewed, 25 touched upon the
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idea of death ascertainment and 13 acknowledged the potential for differential death
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ascertainment by ethnicity.
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A subset of US-based articles that evaluated death ascertainment found that follow-up was not
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related to ethnicity.(30,32,33) However, this consistent finding might be the result of selective
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reporting. Preliminary analyses of some unpublished Canadian data showed that deaths from
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breast cancer amongst diagnosed cases of breast cancer dropped after age 75 in Ontario First
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Nations but not in the control group, suggesting that deaths in First Nations were not being fully
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ascertained.
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Mechanisms to improve death ascertainment will differ based on the routine follow-up methods
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of the registry (i.e. active or passive) and are often beyond the control of the investigator.
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Investigators are, however, urged to consider whether the routine follow-up methods of the
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registry are likely to have less success in identifying deaths among subsets of the population, as
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this could result in spuriously high survival estimates and distort estimates of the disparities in
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survival between groups. Where possible, the completeness of death ascertainment at the cancer
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registry level should be reported and the potential for differential death ascertainment by
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ethnicity should be disclosed. If the risk of differential death ascertainment is considered high,
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results should be interpreted with greater caution.
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Misclassification of, or missing information about, the cause of death will lead to biased
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estimates of cause-specific survival on the absolute and relative scale, especially for cancers of
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poor prognosis.(18) Despite this, only 12 of the 49 articles calculating cause-specific survival
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alluded to the validity and/or completeness of cause of death data. If cause-specific survival is
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used, the suspected validity of the cause of death classification, and any differences in validity
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that might exist across subgroups, should be reported.
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Survival measures
Cancer survival is typically measured using one of three outcomes: all-cause mortality, cause-
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specific mortality and excess mortality due to cancer. Each approach aims to answer a slightly
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different question about survival and relies on different information about the mortality
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experience of cancer patients. All three methods require information about the date of death.
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Cause-specific mortality additionally requires information about the cause of death in cancer
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cases and relative survival (excess mortality) additionally requires information about the
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expected mortality in the population from which cancer cases arose. The availability of cause of
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death or expected mortality data often dictates the approach used.
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Interpreted correctly in the absence of bias, any of these approaches can generate estimates of
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survival that are useful to patients, care providers and policy makers. When estimating the
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disparity in cancer survival between two populations however, the interpretation of the ratio of
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these measures (likely a hazard ratio) is more nuanced. Each of these will be discussed in turn.
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(i)
All-cause survival
Unlike cause-specific and relative survival methods, which aim to estimate survival in a
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hypothetical world where cancer is the only cause of death, all-cause survival measures the
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observed survival of cancer patients. This information can be useful to patients, researchers and
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policy makers. Advantages to this measure are that it requires the fewest data elements, and that
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it is easily interpretable. However, a ratio of all-cause survival of Indigenous to non-Indigenous
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cancer patients is a measure not only of the disparity in cancer-specific survival, but also of the
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disparity in overall survival.
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Because Indigenous populations tend to have a lower life expectancy (higher background
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mortality), all-cause mortality ratios are likely to overestimate the cancer-related disparity. Given
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that we typically want to consider mortality associated with the cancer itself, we use cause-
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specific or excess mortality outcomes (measures of net mortality) to correct for mortality from
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other causes.(19) When data on cause of death or expected mortality are unavailable however,
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all-cause survival may be the only approach possible, which likely explains its popularity in the
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literature we reviewed.
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Cause-specific survival
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In cause-specific survival, a death due to cancer is counted as an event and a death due to any
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other cause is censored. Using this approach requires access to and confidence in cause of death
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as recorded on death certificates. As was discussed earlier, incomplete or invalid cause of death
22
classification can be a source of information bias in studies using cause-specific mortality as an
23
outcome.
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Cause-specific survival poses an additional challenge by requiring a clear distinction between
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cancer-related deaths and deaths independent of cancer. The magnitude of cause-specific
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survival estimates will vary according to where the line between cancer attributable and non-
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cancer deaths is drawn.(114)
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Dichotomizing deaths as “due to cancer” or “not due to cancer” can also have implications for
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estimating survival disparities between populations. If population X is less healthy at diagnosis
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than Population Y (e.g. X has more comorbidities), then Population X may have true rates of
4
excess death attributable to cancer that are equal to or higher than Population Y, but will appear
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to have better cause-specific survival because their deaths were attributed to the comorbidities
6
rather than to their cancers. One approach to rectify this is to broaden the definition of a cancer
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death. Howlader and colleagues have proposed such a definition, which uses an algorithm to
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classify causes of death as cancer or other-cause by taking into account site of the original cancer
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diagnosis, the tumor sequence and comorbidities (e.g. HIV/AIDS and/or site-related non-cancer
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diseases).(114)
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Of 49 articles that had cause-specific survival as an outcome, only 14 provided a definition of a
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cancer death. These ranged from death due to the cancer of interest as the primary cause of death
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to death from any cancer as a contributing cause of death. Narrower definitions of cancer death
14
may overestimate net cancer survival in a single population because some excess deaths
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attributable to cancer (e.g. those where complications of treatment fatally exacerbated existing
16
comorbidities, or those where deaths were attributable to cancer in a nearby organ rather than the
17
primary site) will be censored as non-cancer deaths because the death certificate does not
18
attribute death primarily to the initially registered cancer.(115)
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As a result, narrower definitions of cause of death may lead to underestimates of the disparities
20
in net survival in populations with different profiles of comorbidities. If for example, Indigenous
21
persons with cancer are more likely to have comorbidities than their non-Indigenous peers, under
22
a narrow definition of cancer deaths, their net survival will be overestimated by a cause-specific
23
approach compared to their peers with fewer comorbidities. To allow readers to properly
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interpret both absolute and relative estimates of survival, authors must disclose how they define a
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cancer death. Further, if one aims to quantify the disparity in net survival in two populations
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using cause-specific survival, a broader definition of a cancer death may be preferred.
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(iii)
Relative survival ratios
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Relative Survival Ratios (RSRs) are calculated by comparing the observed survival in a group of
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individuals diagnosed with cancer to the expected survival of the population to which they
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belong. RSRs overcome one of the major weaknesses of all-cause survival by taking into account 13
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differences in background mortality (and accordingly, comorbidities to the extent that they affect
2
mortality) between populations. They are therefore particularly suitable for comparing survival
3
between groups wherein background mortality is suspected to be different such as
4
countries(116,117), socioeconomic classes(118) or races/ethnicities(119,120). Unlike cause-
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specific survival, RSRs do not rely on cause of death information, which may be unreliable or
6
unavailable.
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The calculation of a valid RSR does, however, rely on valid population-specific estimates of
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mortality (life tables). Of the 11 studies that used excess mortality as an outcome, seven provided
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information about the life tables that were used to generate expected mortality. While they were
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all specific to age, sex and ethnicity, none were specific to calendar time, and the population
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used to generate the life table belonged to the same geographical region as the cancer cases in
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only two of the seven articles.
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Generating life tables tends to be straightforward at the national scale, where the population size
14
and mortality rates are readily available, but Indigenous-specific life tables can be much more
15
difficult to estimate. Indigenous-specific population counts and mortality rates may not exist, and
16
if they do, legitimate barriers to their use include concerns around ethnic misclassification,
17
differential death ascertainment across ethnicities and numerator-denominator bias in vital
18
statistics. One study from the US found that misclassification of ethnicity on death certificates
19
led to an underestimate of mortality in AI by 21%.(120)
20
If age-, sex-, ethnicity-, time period- and geography-specific life tables are available, relative
21
survival offers advantages over cause-specific and all-cause survival estimates. Given this, we
22
recommend that investigators planning analyses comparing cancer survival across ethnicities do
23
their utmost to produce or obtain the appropriate ethnic-specific life tables for their analyses.
24
Authors should report on how the life tables were generated and consider the extent to which
25
bias in the expected mortality estimates may influence the results. In the absence of life tables, a
26
cause-specific approach with a broad definition of cancer death may be an appropriate
27
alternative. Researchers taking that approach, however, should be clear about how and why
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cause-specific survival estimates were used and what consequences that may have for
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comparability and bias.
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Limitations and Conclusions 14
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This is the first review of methods used to compare cancer survival across ethnic subgroups of
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populations that we are aware of. Articles comparing survival between Indigenous and non-
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Indigenous persons are being published at an increasing frequency making it an appropriate time
4
to critically appraise methodological approaches.
5
Limitations relating to the sensitivity of our literature search do deserve mention. The review
6
does not include all research on this topic in the selected populations but is limited to those full-
7
text articles identified in the peer-reviewed literature published within the time window of our
8
search. The methodological issues we have presented are, however, likely to be common to those
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studies published more recently or in the grey literature.
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In this review, we have made suggestions for researchers who are estimating and comparing
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cancer survival in ethnic and/or racial subgroups of the population, but recognize that there is no
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single answer applicable to each situation. Each setting, population and data source poses
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particular challenges to validity and the ideal solutions are likely to be as varied as the obstacles.
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We hope, however, to have drawn attention to common sources of information bias. We have
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also provided an overview of the merits, potential pitfalls and interpretation of common
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measures of cancer survival. These are applicable not only to the study of Indigenous cancer
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survival disparities but also of Indigenous health disparities more generally, and of disparities in
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cancer survival between ethnic or other subgroups of a population.
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These studies provide the evidence required to mobilize resources and direct them to the areas
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that will have the greatest impact for reducing cancer survival disparities between Indigenous
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and non-Indigenous populations. To accomplish this, however, valid results and meaningful
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interpretations of these results are required. We urge future researchers on this and related topics
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to clearly describe their data sources, to justify their analytic choices and to fully discuss the
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potential impact of those approaches on the results and interpretation.
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Acknowledgments
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We acknowledge insightful comments on drafts of this paper from Wendy Lou, Loraine Marrett,
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Diane Nishri and Jason Pole. Caroline Cawley contributed valuable editorial expertise. Diana
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Withrow was supported by a Canadian Institutes of Health Research Doctoral Award. The funder
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had no role in the preparation of this paper.
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References 1.
RI PT
2.
Reading CL, Wien F. Health inequalities and the social determinants of Aboriginal peoples' health. National Collaborating Centre for Aboriginal Health Prince George, BC; 2009. Barnes PM, Adams PF, Powell-Griner E. Health characteristics of the American Indian or Alaska Native adult population: United States, 2004-2008. US Department of Health and Human Services; 2010. Baker MG, Barnard LT, Kvalsvig A, Verrall A, Zhang J, Keall M, et al. Increasing incidence of serious infectious diseases and inequalities in New Zealand: a national epidemiological study. Lancet. 2012 Mar;379(9821):1112–9. Robson B, Harris R. (eds). Hauora: Maori Standards of Health IV. A study of the years 2000-2005. Te Rōpū Rangahau Hauora a Eru Pōmare; 2007. Espey DK, Wu X-C, Swan J, Wiggins C, Jim MA, Ward E, et al. Annual report to the nation on the status of cancer, 1975-2004, featuring cancer in American Indians and Alaska Natives. Cancer. 2007 Nov 15;110(10):2119–52. Mahoney MC, Michalek AM. A meta-analysis of cancer incidence in United States and Canadian native populations. Int J Epidemiol. 1991 Jun;20(2):323–7. Hunter CP. Epidemiology, stage at diagnosis, and tumor biology of breast carcinoma in multiracial and multiethnic populations. Cancer. 2000 Mar 1;88(S5):1193–202. Condon JR, Armstrong BK, Barnes A, Cunningham J. Cancer in Indigenous Australians: a review. Cancer Causes Control. 2003 Mar;14(2):109–21. Shaw C, Blakely T, Sarfati D, Fawcett J, Peace J. Trends in colorectal cancer mortality by ethnicity and socio economic position in New Zealand, 1981 99: one country, many stories.Aust N Z J Public Health. 2006 Feb 1;30(1):64–70. Kelly JJ, Lanier AP, Alberts S, Wiggins CL. Differences in cancer incidence among Indians in Alaska and New Mexico and U.S. Whites, 1993-2002. Cancer Epidemiol Biomarkers Prev. 2006 Aug;15(8):1515–9. Marrett LD, Nishri ED. Cancer incidence among Registered First Nations in Ontario, 1968-2001. Toronto; 2010. Tjepkema M, Wilkins R, Senécal S, Guimond E, Penney C. Mortality of Métis and registered Indian adults in Canada: an 11-year follow-up study. Health Rep. 2009 Dec;20(4):31–51. Cunningham J, Rumbold AR, Zhang X, Condon JR. Incidence, aetiology, and outcomes of cancer in Indigenous peoples in Australia. Lancet Oncol. 2008 Jun;9(6):585–95. Supramaniam R, Grindley H, Pulver LJ. Cancer mortality in Aboriginal people in New South Wales, Australia, 1994–2002.Aust N Z J Public Health. 2006 Oct 1;30(5):453–6. Condon JR, Armstrong BK, Barnes T, Zhao Y. Cancer incidence and survival for indigenous Australians in the Northern Territory.Aust N Z J Public Health. 2005 Apr;29(2):123–8. Gracey M, King M. Indigenous health part 1: determinants and disease patterns. Lancet. 2009 Jul 4;374(9683):65–75.
3.
SC
4.
7. 8. 9.
10.
11.
AC C
12.
EP
6.
TE D
M AN U
5.
13.
14.
15.
16.
ACCEPTED MANUSCRIPT
22. 23. 24.
25.
26.
27.
28.
AC C
29.
RI PT
21.
SC
20.
M AN U
19.
TE D
18.
King M, Smith A, Gracey M. Indigenous health part 2: the underlying causes of the health gap. Lancet. 2009 Jul 4;374(9683):76–85. Sarfati D, Blakely T, Pearce N. Measuring cancer survival in populations: relative survival vs cancer-specific survival. Int J Epidemiol. 2010 Apr;39(2):598–610. Dickman PW, Adami H-O. Interpreting trends in cancer patient survival. J Intern Med. 2006 Aug;260(2):103–17. Berrino F, Micheli A, Sant M, Capocaccia R. Interpreting survival differences and trends. Tumori. 1997 Jan;83(1):9–16. Altman DG, De Stavola BL, Love SB, Stepniewska KA. Review of survival analyses published in cancer journals. Br J Cancer. 1995 Aug;72(2):511–8. Begg CB, Schrag D. Attribution of deaths following cancer treatment. J Natl Cancer Inst. 2002 Jul 17;94(14):1044–5. Welch HG, Black WC. Are deaths within 1 month of cancer-directed surgery attributed to cancer? J Natl Cancer Inst. 2002 Jul 17;94(14):1066–70. Robinson D, Sankila R, Hakulinen T, Møller H. Interpreting international comparisons of cancer survival: the effects of incomplete registration and the presence of death certificate only cases on survival estimates. Eur J Cancer. 2007 Mar;43(5):909–13. Jemal A, Clegg LX, Ward E, Ries LAG, Wu X, Jamison PM, et al. Annual report to the nation on the status of cancer, 1975-2001, with a special feature regarding survival. Cancer. 2004 Jul 1;101(1):3–27. Bleed DM, Risser DR, Sperry S, Hellhake D, Helgerson SD. Cancer incidence and survival among American Indians registered for Indian health service care in Montana, 1982-1987. J Natl Cancer Inst. 1992 Oct 7;84(19):1500–5. Sugarman JR, Dennis LK, White E. Cancer survival among American Indians in western Washington State (United States). Cancer Causes Control. 1994 Sep;5(5):440–8. Baquet CR. Native Americans' cancer rates in comparison with other peoples of color. Cancer. 1996 Oct 1;78(7 Suppl):1538–44. Frost F, Tollestrup K, Hunt WC, Gilliland F, Key CR, Urbina CE. Breast cancer survival among New Mexico Hispanic, American Indian, and non-Hispanic white women (1973-1992). Cancer Epidemiol Biomarkers Prev. 1996 Nov;5(11):861–6. Gilliland FD, Hunt WC, Key CR. Ethnic variation in prostate cancer survival in New Mexico. Cancer Epidemiol Biomarkers Prev. 1996 Apr;5(4):247–51. Schiff M, Key CR, Gilliland FD, Becker TM. Ethnic differences in uterine corpus cancer incidence and mortality in New Mexico's American Indians, Hispanics and non-Hispanic whites. Int J Epidemiol. 1997;26(2):249–55. Brown MO, Lanier AP, Becker TM. Colorectal cancer incidence and survival among Alaska Natives, 1969-1993. Int J Epidemiol. 1998 Jun;27(3):388–96. Gilliland FD, Hunt WC, Key CR. Trends in the survival of American Indian, Hispanic, and Non-Hispanic white cancer patients in New Mexico and Arizona, 1969-1994. Cancer. 1998 May 1;82(9):1769–83. Gilliland FD, Key CR. Prostate cancer in American Indians, New Mexico, 1969 to 1994. J Urol. 1998 Mar;159(3):893–7–discussion897–8.
EP
17.
30. 31.
32. 33.
34.
18
ACCEPTED MANUSCRIPT
40.
41.
42.
43. 44.
45.
AC C
46.
RI PT
39.
SC
38.
M AN U
37.
TE D
36.
Dennis TD. Cancer stage at diagnosis, treatment, and survival among American Indians and non-American Indians in Montana. Cancer. 2000 Jul 1;89(1):181–6. Clegg LX, Li FP, Hankey BF, Chu K, Edwards BK. Cancer survival among US whites and minorities: a SEER (Surveillance, Epidemiology, and End Results) Program population-based study. Arch Intern Med. 2002 Sep 23;162(17):1985–93. Li CI, Malone KE, Daling JR. Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch Intern Med. 2003 Jan 13;163(1):49–56. Biggs ML, Schwartz SM. Differences in testis cancer survival by race and ethnicity: a population-based study, 1973-1999 (United States). Cancer Causes Control. 2004 Jun;15(5):437–44. Chien C, Morimoto LM, Tom J, Li CI. Differences in colorectal carcinoma stage and survival by race and ethnicity. Cancer. 2005 Aug 1;104(3):629–39. Wampler NS, Lash TL, Silliman RA, Heeren TC. Breast cancer survival of American Indian/Alaska Native women, 1973–1996. Soz-Präventivmed. Birkhäuser-Verlag; 2005 Aug 1;50(4):230–7. Cormier JN, Xing Y, Ding M, Lee JE, Mansfield PF, Gershenwald JE, et al. Ethnic differences among patients with cutaneous melanoma. Arch Intern Med. 2006 Sep 25;166(17):1907–14. Goggins WB, Wong GK. Poor Survival for US Pacific Islander Cancer Patients: Evidence From the Surveillance, Epidemiology, and End Results Database: 1991 to 2004. J Clin Oncol. 2007 Dec 20;25(36):5738–41. Wang SJ, Fuller CD, Thomas CR. Ethnic disparities in conditional survival of patients with non-small cell lung cancer. J Thorac Oncol. 2007 Mar;2(3):180–90. Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman MC. Trends in Area-Socioeconomic and Race-Ethnic Disparities in Breast Cancer Incidence, Stage at Diagnosis, Screening, Mortality, and Survival among Women Ages 50 Years and Over (1987-2005). Cancer Epidemiol Biomarkers Prev. 2009;18(1):121–31. Tehranifar P, Neugut AI, Phelan JC, Link BG, Liao Y, Desai M, et al. Medical Advances and Racial/Ethnic Disparities in Cancer Survival. Cancer Epidemiol Biomarkers Prev. 2009 Sep 29;:1–9. Fesinmeyer MD, Goulart B, Blough DK, Buchwald D, Ramsey SD. Lung cancer histology, stage, treatment, and survival in American Indians and Alaska Natives and whites. Cancer. 2010 Jul 1;116(20):4810–6. Yu G-P, Li JC-L, Branovan D, McCormick S, Schantz SP. Thyroid cancer incidence and survival in the national cancer institute surveillance, epidemiology, and end results race/ethnicity groups. Thyroid. 2010 May;20(5):465–73. Cetin K, Ettinger DS, Hei Y, O'Malley CD. Prognostic factors by histologic subtype in stage IV non-small cell lung cancer (NSCLC): A population-based survival analysis of data from the Surveillance, Epidemiology, and End Results (SEER) Program (1988-2003). ASCO Meeting Abstracts. 2009 May 20;27(15S):11053. Cueto CV, Szeja S, Wertheim BC, Ong ES, Tsikitis VL. Disparities in Treatment and Survival of White and Native American Patients with Colorectal Cancer: A SEER Analysis. J Am Coll Surg. 2011 Oct 1;213(4):469–74. Du XL, Lin CC, Johnson NJ, Altekruse S. Effects of individual-level socioeconomic factors on racial disparities in cancer treatment and survival. Cancer. 2011 Jan
EP
35.
47.
48.
49.
50.
19
ACCEPTED MANUSCRIPT
55.
56. 57. 58.
59.
60.
RI PT
AC C
61.
SC
54.
M AN U
53.
TE D
52.
EP
51.
24;117(14):3242–51. Ooi SL, Martinez ME, Li CI. Disparities in breast cancer characteristics and outcomes by race/ethnicity. Breast Cancer Res Treat. 2011 Jun 7;127(3):729–38. Smith CB, Bonomi M, Packer S, Wisnivesky JP. Disparities in lung cancer stage, treatment and survival among American Indians and Alaskan Natives. Lung Cancer. 2011 May;72(2):160–4. Wu X-C, Eide MJ, King J, Saraiya M, Huang Y, Wiggins C, et al. Racial and ethnic variations in incidence and survival of cutaneous melanoma in the United States, 1999-2006. J Am Acad Dermatol. 2011 Nov 1;65(5):S26.e1–S26.e13. Singh GK. Rural–Urban Trends and Patterns in Cervical Cancer Mortality, Incidence, Stage, and Survival in the United States, 1950–2008. J Community Health. 2012 Feb 20;37(1):217–23. Kaya H, Peressini B, Jawed I, Martincic D, Elaimy AL, Lamoreaux WT, et al. Impact of age, race and decade of treatment on overall survival in a critical population analysis of 40,000 multiple myeloma patients. Int J Hematol. 2012 Jan 9;95(1):64–70. Kelly JJ, Alberts SR, Sacco F. Colorectal cancer in Alaska Native people, 2005– 2009. Gastrointest Cancer Res. 2012 Sept;5(5):149-54. Taghavi S, Jayarajan SN, Davey A, Willis AI. Prognostic Significance of Signet Ring Gastric Cancer. J Clin Oncol. 2012 Sep 28;30(28):3493–8. Dwojak SM, Finkelstein DM, Emerick KS, Lee JH, Petereit DG, Deschler DG. Poor Survival for American Indians with Head and Neck Squamous Cell Carcinoma. Otolaryngol Head Neck Surg. 2014 Jul 23;151(2):265–71. Dwojak SM, Sequist TD, Emerick K, Deschler DG. Survival differences among American Indians/Alaska natives with head and neck squamous cell carcinoma. Head Neck. 2012 Aug 8;35(8):1114–8. Tannenbaum SL, Koru-Sengul T, Miao F, Byrne MM. Disparities in survival after female breast cancer diagnosis: a population-based study. Cancer Causes Control. 2013 Jun 18;24(9):1705–15. Tannenbaum SL, Koru-Sengul T, Zhao W, Miao F, Byrne MM. Survival Disparities in Non–Small Cell Lung Cancer by Race, Ethnicity, and Socioeconomic Status. Cancer J Sci Am. 2014;20(4):237–45. Javid SH, Varghese TK, Morris AM, Porter MP, He H, Buchwald D, et al. Guideline-concordant cancer care and survival among American Indian/Alaskan Native patients. Cancer. 2014 Apr 7;120(14):2183–90. Lee DJ, Tannenbaum SL, Koru-Sengul T, Miao F, Zhao W, Byrne MM. Native American race, use of the Indian Health Service, and breast and lung cancer survival in Florida, 1996-2007. Prev Chronic Dis. 2014;11:E35. Mahdi H, Schlick CJ, Kowk L-L, Moslemi-Kebria M, Michener C. Endometrial cancer in Asian and American Indian/Alaskan Native women: Tumor characteristics, treatment and outcome compared to non-Hispanic white women. Gynecol Oncol. 2014 Feb 1;132(2):443–9. Lethaby AE, Mason BH, Holdaway IM, Kay RG. Age and ethnicity as prognostic factors influencing overall survival in breast cancer patients in the Auckland region. Auckland Breast Cancer Study Group. N Z Med J. 1992 Dec 9;105(947):485–8.
62.
63.
64.
65.
20
ACCEPTED MANUSCRIPT
71. 72.
73.
74.
75.
76.
AC C
77.
RI PT
70.
SC
69.
M AN U
68.
TE D
67.
Delahunt B, Bethwaite P, Nacey JN. Renal cell carcinoma in New Zealand: a national survival study. Urology. 1994 Mar;43(3):300–9. Gill AJ, Martin IG. Survival from upper gastrointestinal cancer in New Zealand: The effect of distance from a major hospital, socio-economic status, ethnicity, age and gender. ANZ J Surg. 2002;72(9):643–6. Phillips ARJ, Lawes CMM, Cooper GJS, Windsor JA. Ethnic disparity of pancreatic cancer in New Zealand. Int J Gastrointest Cancer. 2002;31(1-3):137–45. Jeffreys M, Stevanovic V, Tobias M, Lewis C, Ellison-Loschmann L, Pearce N, et al. Ethnic inequalities in cancer survival in New Zealand: linkage study. Am J Public Health. 2005;95(5):834. Haynes R, Pearce J, Barnett R. Cancer survival in New Zealand: ethnic, social and geographical inequalities. Soc Sci Med. 2008 Sep;67(6):928–37. Sneyd MJ. Ethnic differences in prostate cancer survival in New Zealand: a national study. Cancer Causes Control. 2008 Nov 14;19(9):993–9. Brewer N, Pearce N, Jeffreys M, White P, Ellison-Loschmann L. Demographic differences in stage at diagnosis and cervical cancer survival in New Zealand, 19942005. J Womens Health (Larchmt). 2009 Jul;18(7):955–63. Hill S, Sarfati D, Blakely T, Robson B, Purdie G, Chen J, et al. Survival disparities in Indigenous and non-Indigenous New Zealanders with colon cancer: the role of patient comorbidity, treatment and health service factors. J Epidemiol Community Health. 2010 Jan 7;64(2):117–23. Mcleod M, Harris R, Purdie G, Cormack D, Robson B, Sykes P, et al. Improving survival disparities in cervical cancer between Māori and non-Māori women in New Zealand: a national retrospective cohort study. Aust N Z J Public Health. 2010 Apr 1;34(2):193–9. Priest P, Sadler L, Sykes P, Marshall R, Peters J, Crengle S. Determinants of inequalities in cervical cancer stage at diagnosis and survival in New Zealand. Cancer Causes Control. 2010 Feb 22;21(2):209–14. Sammour T, Kahokehr A, Vather R, Connolly AB, Hill AG. Ethnic disparity in colonic cancer outcomes in New Zealand--biology or an access issue? Colorectal Dis. 2010 Jul;12(7 Online):e50–6. Brewer N, Borman B, Sarfati D, Jeffreys M, Fleming ST, Cheng S, et al. Does comorbidity explain the ethnic inequalities in cervical cancer survival in New Zealand? A retrospective cohort study. BMC Cancer. 2011;11(1):132. Brewer N, Zugna D, Daniel R, Borman B, Pearce N, Richiardi L. Which factors account for the ethnic inequalities in stage at diagnosis and cervical cancer survival in New Zealand? Cancer Epidemiol. 2012 Aug;36(4):e251–7. Swart EM, Sarfati D, Cunningham R, Dennett E, Signal V, Gurney J, et al. Ethnicity and rectal cancer management in New Zealand. N Z Med J. 2013 Oct 18;126(1384):42–54. Sarfati D, Gurney J, Stanley J, Koea J. A retrospective cohort study of patients with stomach and liver cancers: the impact of comorbidity and ethnicity on cancer care and outcomes. BMC Cancer. 2014 Nov 7;14(1):1–11. Campbell I, Scott N, Seneviratne S, Kollias J, Walters D, Taylor C, et al. Breast Cancer Characteristics and Survival Differences between Maori, Pacific and other
EP
66.
78.
79.
80.
81.
21
ACCEPTED MANUSCRIPT
86.
87.
88.
89.
90.
RI PT
AC C
91.
SC
85.
M AN U
84.
TE D
83.
EP
82.
New Zealand Women Included in the Quality Audit Program of Breast Surgeons of Australia and New Zealand. Asian Pac J Cancer Prev. 2015 Apr 3;16(6):2465–72. Gurney JK, Sarfati D, Stanley J. Obscure etiology, unusual disparity: the epidemiology of testicular cancer in New Zealand. Cancer Causes Control. 2015 Feb 17;26(4):561–9. Lawrenson R, Lao C, Obertová Z, Brown C, Holmes M, Tyrie L, et al. Management and characteristics of patients with metastatic prostate cancer in a cohort of New Zealand men. Oncology. 2015;88(3):157–63. Obertová Z, Scott N, Brown C, Stewart A, Lawrenson R. Survival disparities between Māori and non-Māori men with prostate cancer in New Zealand. BJU Int. 2015 Apr 1;115:24–30. Seneviratne S, Campbell I, Scott N, Shirley R, Peni T, Lawrenson R. Accuracy and completeness of the New Zealand Cancer Registry for staging of invasive breast cancer. Cancer Epidemiol. 2014 Oct 1;38(5):638–44. Signal V, Sarfati D, Cunningham R, Gurney J, Koea J, Ellison-Loschmann L. Indigenous inequities in the presentation and management of stomach cancer in New Zealand: a country with universal health care coverage. Gastric Cancer. 2015 Apr 15;18(2):1–9. Laurvick CL, Semmens JB, Holman CDJ, Leung YC. Ovarian cancer in Western Australia (1982-98): incidence, mortality and survival. Aust N Z J Public Health. 2003 Dec;27(6):588–95. Condon JR, Barnes T, Armstrong BK, Selva-Nayagam S, Elwood JM. Stage at diagnosis and cancer survival for Indigenous Australians in the Northern Territory. Med J Aust. 2005 Mar 21;182(6):277–80. Parker C, Tong SYC, Dempsey K, Condon J, Sharma SK, Chen JWC, et al. Hepatocellular carcinoma in Australia's Northern Territory: high incidence and poor outcome. Med J Aust. 2014 Oct 20;201(8):470–4. Supramaniam R, Gibberd A, Dillon A, Goldsbury DE, O'Connell DL. Increasing rates of surgical treatment and preventing comorbidities may increase breast cancer survival for Aboriginal women. BMC Cancer. 2014;14(1):163. Valery PC, Coory M, Stirling J, Green AC. Cancer diagnosis, treatment, and survival in Indigenous and non-Indigenous Australians: a matched cohort study. The Lancet. 2006;367(9525):1842–8. Coory MD, Green AC, Stirling J, Valery PC. Survival of Indigenous and nonIndigenous Queenslanders after a diagnosis of lung cancer: a matched cohort study. Med J Aust. 2008 May 19;188(10):562–6. Moore SP, Green AC, Garvey G, Coory MD, Valery PC. A study of head and neck cancer treatment and survival among indigenous and non-indigenous people in Queensland, Australia, 1998 to 2004. BMC Cancer. 2011;11(1):460. Dasgupta P, Baade PD, Aitken JF, Turrell G. Multilevel determinants of breast cancer survival: association with geographic remoteness and area-level socioeconomic disadvantage. Breast Cancer Res Treat. 2012 Apr 9;132(2):701–10. Cramb SM, Garvey G, Valery PC, Williamson JD, Baade PD. The first year counts: cancer survival among Indigenous and non-Indigenous Queenslanders, 1997–2006. Med J Aust. 2012 Mar 5;196(4):270–4.
92.
93.
94.
95.
22
ACCEPTED MANUSCRIPT
100.
101.
102.
103.
104.
RI PT
AC C
105.
SC
99.
M AN U
98.
TE D
97.
Moore SP, le C Green A, Bray F, Garvey G, Coory M, Martin J, et al. Survival disparities in Australia: an analysis of patterns of care and comorbidities among indigenous and non-indigenous cancer patients. BMC Cancer. 2014 Jul 18;14(1):1– 9. Diaz A, Moore SP, Martin JH, Green AC, Garvey G, Valery PC. Factors Associated With Cancer-Specific and Overall Survival Among Indigenous and Non-Indigenous Gynecologic Cancer Patients in Queensland, Australia: A Matched Cohort Study. Int J Gynecol Cancer. 2015 Mar 1;25(3):542–7. Cottrell J, Street J, Chong A, Roder D. Comparing cancer profiles and survival of aboriginal and non-aboriginal patients in South Australia: where are the opportunities for improving Aboriginal health? Asian Pac J Cancer Prev. 2007 Oct 1;8(4):495–501. Chong A, Roder D. Exploring differences in survival from cancer among Indigenous and non-Indigenous Australians: implications for health service delivery and research. Asian Pac J Cancer Prev. 2010;11(4):953–61. Luke C, Tracey E, Stapleton A, Roder D. Exploring contrary trends in bladder cancer incidence, mortality and survival: implications for research and cancer control. Intern Med J. 2010 May;40(5):357–62. Gillis DC, Irvine J, Tan L, Chiu S, Liu L, Robson D. Cancer incidence and survival of Saskatchewan northerners and registered Indians, 1967-1986. Arctic Med Res. 1991;Suppl:447–51. Irvine J, Gillis DC, Tan L, Chiu S, Liu L, Robson D. Lung, breast and cervical cancer incidence and survival in Saskatchewan northerners and registered Indians (1967-86). Arctic Med Res. 1991;Suppl:452–6. Sheppard AJ, Chiarelli AM, Marrett LD, Nishri ED, Trudeau ME. Stage at diagnosis and comorbidity influence breast cancer survival in First Nations women in Ontario, Canada. Cancer Epidemiol Biomarkers Prev. 2011 Oct;20(10):2160–7. Nishri ED, Sheppard AJ, Withrow DR, Marrett LD. Cancer survival among First Nations people of Ontario, Canada (1968-2007). Int J Cancer. 2014 Jun 13;136(3):639-45. Erickson B, Biron VL, Zhang H, Seikaly H, Côté DWJ. Survival outcomes of First Nations patients with oral cavity squamous cell carcinoma (Poliquin 2014). J Otolaryngol Head Neck Surg. 2015;44(1):4. Gomez SL, Le GM, West DW, Satariano WA, O'Connor L. Hospital policy and practice regarding the collection of data on race, ethnicity, and birthplace. Am J Public Health. 2003 Oct;93(10):1685–8. Robertson H, Lumley J, Berg S. How midwives identify women as aboriginal or Torres Strait Islanders. Aust Coll Midwives Inc J. 1995 Sep;8(3):26–9. Young MJ. Assessing the quality of identification of Aboriginal and Torres Strait Islander people in Western Australia Hospital Data, 2000. Health Information Occasional Paper 13. Health Department of Western Australia, Perth. Condon J, Zhao Y, Armstrong B, Barnes T. Northern Territory Cancer Register data quality, 1981-2001. NT Cancer Registry, the Cooperative Research Centre for Aboriginal Health, Charles Darwin University and the Menzies School of Health Research; 2004.
EP
96.
106.
107. 108.
109.
23
ACCEPTED MANUSCRIPT
114.
115.
116.
117.
118.
119.
RI PT
AC C
120.
SC
113.
M AN U
112.
TE D
111.
Cormack D, Robson B, Purdie G, Ratima M, Brown R. Access to cancer services for Maori: a report prepared for the Ministry of Health, Wellington School of Medicine and Health Sciences;2006. Johnson JC, Soliman AS, Tadgerson D, Copeland GE, Seefeld DA, Pingatore NL, et al. Tribal linkage and race data quality for American Indians in a state cancer registry. Am J Prev Med. 2009 Jun;36(6):549–54. Clegg LX, Reichman ME, Hankey BF, Miller BA, Lin YD, Johnson NJ, et al. Quality of race, Hispanic ethnicity, and immigrant status in population-based cancer registry data: implications for health disparity studies. Cancer Causes Control. 2007 Mar;18(2):177–87. Berrino F. The EUROCARE Study: strengths, limitations and perspectives of population-based, comparative survival studies. Ann Oncol. 2003 Dec 1;14(suppl 5):v9–v13. Howlader N, Ries LAG, Mariotto AB, Reichman ME, Ruhl J, Cronin KA. Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010 Oct 20;102(20):1584–98. German RR, Fink AK, Heron M, Stewart SL, Johnson CJ, Finch JL, Yin D, Accuracy of Cancer Mortality Study Group. The accuracy of cancer mortality statistics based on death certificates in the United States. Cancer Epidemiol. 2011 Apr 30; 35(2):126-31. Coleman MP, Quaresma M, Berrino F, Lutz J-M, De Angelis R, Capocaccia R, et al. Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol. 2008 Aug;9(8):730–56. Coleman MP, Forman D, Bryant H, Butler J, Rachet B, Maringe C, et al. Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995–2007 (the International Cancer Benchmarking Partnership): an analysis of populationbased cancer registry data. The Lancet. 2011 Jan 8;377(9760):127–38. Coleman MP, Rachet B, Woods LM, Mitry E, Riga M, Cooper N, et al. Trends and socioeconomic inequalities in cancer survival in England and Wales up to 2001. Br J Cancer. 2004 Apr 5;90(7):1367–73. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA: A Cancer Journal for Clinicians. 2012 Jan 4;62(1):10–29. Rosenberg HM, Maurer JD, Sorlie PD, Johnson NJ, MacDorman MF, Hoyert DL, et al. Quality of Death Rates by Race and Hispanic Origin: A summary of Current Research, 1999. Vital Health Stat 2. 1999 Sep 24;128:1–20. Condon JR, Zhang X, Baade P, Griffiths K. Cancer survival for Aboriginal and Torres Strait Islander Australians: a national study of survival rates and excess mortality. Popul Health Metr. 2014 Jan 31;12(1). Hill S, Sarfati D, Blakely T, Robson B, Purdie G, Dennett E, et al. Ethnicity and management of colon cancer in New Zealand: do indigenous patients get a worse deal? Cancer. 2010 Jul 1;116(13):3205–14. Seneviratne S. Impact of mammographic screening on ethnic and socioeconomic inequities in breast cancer stage at diagnosis and survival in New Zealand: a cohort study. BMC Public Health. 2015 Feb 2;15(46):1–10. Cetin K, Ettinger DS, Hei Y-J, O’Malley CD. Survival by histologic subtype in
EP
110.
121.
122.
123.
124.
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ACCEPTED MANUSCRIPT
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EP
TE D
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SC
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stage IV nonsmall cell lung cancer based on data from the Surveillance, Epidemiology and End Results Program. Clin Epidemiol. 2011;3(1):139–48. Lee DJ, Tannenbaum SL, Koru-Sengul T, Miao F, Zhao W, Byrne MM. Native American Race, Use of the Indian Health Service, and Breast and Lung Cancer Survival in Florida, 1996–2007. Prev Chronic Dis. 2014 Mar 6;11:130162–6.
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Tables Table 1. Basic characteristics of reviewed articles, listed chronologically by country (n=83). Region
Indigenous groupa
Years of diagnosis
2003
Western Australia
Aboriginal
1982-1998
Condon, JR(15)
2005
Northern Territory
Indigenous
1991-2001
Condon, JR(88) Valery, PC(91) Cottrell, J(98) Coory, MD(92)
2005 2006 2007 2008
Northern Territory Queensland South Australia Queensland
Indigenous Indigenous Aboriginal Indigenous
1991-2000 1997-2002 1977-2003 1997-2002
Chong, A(99)
2010
South Australia
Indigenous
1977-2007
Luke, C(100) Moore, SP(93) Dasgupta, P(94) Cramb, S(95)
2010 2011 2012 2012
South Australia Queensland Queensland Queensland
Aboriginal Indigenous Indigenous Indigenous
1980-2004 1998-2004 1997-2006 1997-2006
Condon, JR(121)
2014
National
Indigenous
1991-2005
Moore, SP(96)
2014
Queensland
Parker, C(89)
2014
Supramaniam, R(90) Diaz, A(97) Canada Gillis, DC(101) Irvine, J(102) Sheppard, AJ(103)
M AN U
TE D
EP
AC C
Cancer(s)
Ovary Breast, cervix, colon and rectum, esophagus, leukemia, liver, lung, lymphoma, nasopharyngeal, pancreas, thyroid, uterus Breast, cervix, colon and rectum, lung, NHL All cancers combined All cancers combined Lung All cancers combined, breast, cervix, colon and rectum, lung, unknown primary site Bladder Head and neck Breast All cancers combined All cancers combined, anus, bladder, breast, cervix, colorectal, head and neck, Hodgkin lymphoma, kidney, leukemia, liver, lung, melanoma, NHL, ovary, pancreas, prostate, stomach, testis, thyroid, unknown primary site, uterus All cancers combined, breast, central nervous system, cervix, colorectal and small intestine, corpus uteri, esophagus, head and neck, liver, lung and bronchus, lymphoma and leukemia, melanoma, ovary, pancreas, prostate, renal tract, stomach, thyroid, unknown primary site
SC
Publication year
First author Australia Laurvick, CL(87)
Indigenous
1998-2004
Indigenous
2000-2011
Liver
2014 2015
Northern Territory (Top End) New South Wales Queensland
Aboriginal Indigenous
2001-2007 1998-2004
Breast Cervix, other gynecological, ovary, corpus uteri
1991 1991 2011
Saskatchewan Saskatchewan Ontario
Registered Indians Registered Indians First Nations
1967-1986 1967-1986 1995-2004
All cancers combined Breast, cervix, lung Breast
ACCEPTED MANUSCRIPT
Indigenous groupa First Nations First Nations
Years of diagnosis 1968-2001 1998-2009
1992 1994
Auckland National
Maori Maori
1976-1985 1976-1986
Gill, AJ(67)
2002
National
Maori
1995-1997
Phillips, ARJ(68)
2002
National
Maori
1988-1997
Jeffreys, M(69)
2005
National
Maori
1994-2002
Haynes, R(70) Sneyd, MJ(71) Brewer, N(72) Hill, S(122) McLeod, M(74) Priest, P(75) Sammour, T(76) Brewer, N(77) Brewer, N(78) Swart, EM(79) Sarfati, L(80) Campbell, ID(81) Gurney, JK(82) Lawrenson, R(83) Obertova, Z(84) Seneviratne, S(123) Signal, V(86) United States
2008 2008 2009 2010 2010 2010 2010 2011 2012 2013 2014 2014 2015 2015 2015 2015 2015
National National National National National National National National National North Island National National National Midland National Waikato North Island
Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori Maori
Bleed, DM(26)
1992
Montana
Sugarman, JR(27)
1994
Baquet, C(28)
1996
Frost, F(29)
1996
M AN U
TE D
EP
AC C
Seattle-Puget Sound New Mexico/Arizona New Mexico/Arizona
Cancer(s) Breast, cervix, colorectal, lung, prostate Oral cavity squamous cell carcinoma
RI PT
Region Ontario Alberta
Breast Kidney Esophagus, liver, pancreas, stomach, upper gastrointestinal tract, biliary tree Pancreas Bladder, brain, breast, cervix, colon and rectum, esophagus, liver, lung, melanoma, ovary, pancreas, prostate, thyroid, uterus Breast, colon and rectum, lung, melanoma, prostate Prostate Cervix Colon and rectum Cervix Cervix Colon and rectum Cervix Cervix Rectal Stomach and liver combined Breast Testis Prostate Prostate Breast Stomach
SC
Publication year 2014 2015
First author Nishri, ED(104) Erickson, B(105) New Zealand Lethaby, AE(65) Delahunt, B(66)
1994-2004 1996-1999 1994-2005 1996-2003 1996-2006 2000-2002 1996-2003 1994-2005 1994-2005 2006-2008 2006-2008 1998-2010 2000-2011 2009-2012 1996-2010 1999-2012 2006-2008
American Indians
1982-1987
All cancers combined, breast, cervix, gallbladder, lung, prostate
American Indians
1974-1989
Breast, cervix, colon and rectum, lung, prostate
American Indians
1975-1984
Breast, colon and rectum, gallbladder, kidney, liver, lung, NHL, pancreas, prostate, stomach
American Indians
1973-1992
Breast 27
ACCEPTED MANUSCRIPT
Years of diagnosis 1983-1992 1969-1992 1969-1993
1998
New Mexico/Arizona
American Indians
1969-1994
Gilliland, FD(34)
1998
New Mexico
American Indians
1969-1994
Dennis, TD(35)
2000
Montana
American Indians
1984-1993
Clegg, L(36)
2002
9 SEER Registries
AI/AN
Li, CI(37) Biggs, ML(38)
2003 2004
11 SEER Registries 12 SEER Registries
American Indians AI/AN
1992-1998 1973-1999
Jemal, A(25)
2004
12 SEER Registries
AI/AN
1992-2000
Chien, C(39) Wampler, NS(40) Cormier, JN(41) Goggins, WB(42) Wang, SJ(43) Harper, S(44) Tehranifar, P(45) Fesinmeyer, MD(46) Yu, G(47) Cetin, K(124) Cueto, CV(49)
2005 2005 2006 2007 2007 2009 2009 2010 2010 2011 2011
11 SEER Registries 11 SEER Registries 11 SEER Registries 17 SEER Registries 13 SEER Registries 13 SEER Registries 12 SEER Registries 17 SEER Registries 13 SEER Registries 9 SEER Registries 17 SEER Registries
Du, X(50)
2011
Ooi, SL(51) Smith, CB(52) Wu, X(53) Singh, GK(54)
2011 2011 2011 2012
M AN U
TE D
Gilliland, FD(33)
Cancer(s) Prostate Uterus Colon and rectum Bladder, brain, breast, cervix, colon and rectum, esophagus, gallbladder, head and neck, Hodgkins lymphoma, kidney, larynx, leukemia, liver, lung, melanoma, NHL, ovary, pancreas, prostate, stomach, testis, thyroid, uterus Prostate All cancers combined, breast, colon and rectum, lung, prostate All cancers combined, breast, colon and rectum, lung, prostate Breast Testis All cancers combined, bladder, buccal cavity and pharynx, brain, breast, cervix, colon and rectum, esophagus, gallbladder, kidney, larynx, leukemia, liver, lung, melanoma, myeloma, NHL, ovary, pancreas, prostate, stomach, thyroid, uterus Colon and rectum Breast Melanoma Breast, colon and rectum, liver, lung, prostate, stomach Lung Breast All cancers combined Lung Thyroid Lung Colon and rectum Bladder, breast, cervix and uterus, colon and rectum, lung, melanoma, ovary, prostate Breast Lung Melanoma Cervix
RI PT
Indigenous groupa American Indians AI/AN Alaska Natives
SC
Region New Mexico New Mexico Alaska
1975-1997
AI/AN AI/AN AI/AN AI/AN AI/AN AI/AN AI/AN AI/AN American Indians AI/AN AI/AN
1988-2000 1973-1996 1992-2002 1991-2003 1988-1995 1992-2003 1995-1999 1973-2006 1992-2004 1988-2001 1992-2003
15 SEER Registries
AI/AN
1973-2003
17 SEER Registries 17 SEER Registries 17 SEER Registries 17 SEER Registries
AI/AN AI/AN AI/AN AI/AN
2000-2006 1988-2006 1999-2006 2000-2007
EP
Publication year 1996 1997 1998
AC C
First author Gilliland, FD(30) Schiff, M(31) Brown, M(32)
28
ACCEPTED MANUSCRIPT
2012
Kelly, JJ(56)
2012
Taghavi, S(57) Dwojak, SM(59) Tannenbaum, SL(60) Dwojak, SM(58)
2012 2013 2013 2014
Javid, SH(62)
2014
Lee, DJ(125)
2014
Mahdi, H(64)
2014
Indigenous groupa
Years of diagnosis
AI/AN
1973-2003
Alaska Natives
2005-2009
AI/AN AI/AN Native American AI
2004-2007 1996-2007 1996-2007 1999-2009
AI/AN
1996-2005
Cancer(s)
RI PT
Kaya, M(55)
Region Unknown number of SEER Registries Alaska Tumour Registry and SEER 18 SEER Registries 17 SEER Registries Florida South Dakota Unknown number of SEER Registries Florida Unknown number of SEER Registries
Multiple myeloma
Colorectal
Signet ring carcinoma, gastric adenocarcinoma Hypopharynx and larynx, oral cavity, oropharynx Breast Head and neck squamous cell carcinoma
SC
Publication year
M AN U
First author
Breast, colon, lung, prostate
Native American
1996-2007
Breast, lung
AI/AN
1988-2009
Endometrial adenocarcinoma
AC C
EP
TE D
Tannenbaum,um, 2014 Florida Native American 1996-2007 Non-small cell lung cancer SL(61) a Using the nomenclature used in the paper, unless not specified, in which nomenclature for the Indigenous group was inferred by DW. AI/AN: American Indian/Alaska Native; NHL: non-Hodgkin lymphoma; SEER: Surveillance, Epidemiology and End Results
29
ACCEPTED MANUSCRIPT
Mortality outcome(s)
Method for relative estimate of survival
2003 2005 2005
All-cause Cause-specific Cause-specific
N/A N/A Other
Cox PH Cox PH Cox PH
Valery, PC(91)
2006
Cause-specific
N/A
Cox PH
Cottrell, J(98)
2007
All-cause
Kaplan-Meier
N/A
Coory, MD(92)
2008
Cause-specific
N/A
Chong, A(99) Luke, C(100)
2010 2010
Kaplan-Meier N/A
Moore, SP(93)
2011
Cause-specific Cause-specific All-cause, causespecific and noncancer
Dasgupta, P(94)
2012
Cause-specific
N/A
Cramb, S(95)
2012
Condon, JR(121)
2014
Actuarial Relative survival ratio
Moore, SP(96)
2014
Parker, C(89)
2014
Cause-specific Excess mortality and cause-specific All-cause, causespecific and noncancer All-cause
Supramaniam, R(90)
2014
Cause-specific
Diaz, A(97)
2015
Cause-specific and N/A all-cause
Cox PH Cox PH
Cox PH
EP
TE D
Other
Cox PH Cox PH & Poisson
Kaplan-Meier
Cox PH
Kaplan-Meier Cumulative mortality curve
Cox PH
AC C
Canada
Cox PH
N/A
Covariates
Age, histology, SES, location of residence Age, sex Age, stage Age, stage, sex, period of dx, surgery, radiotherapy, chemotherapy, place of residence, cancer site, remoteness Age, sex, cancer site Age, stage, sex, treatment, surgery, radiotherapy, histology, chemotherapy, comorbidity, rurality Age, sex, period of dx, geographic region, metropolitan vs. non Age, period of dx, SES, geographic region, birthplace
M AN U
First author Australia Laurvick, CL(87) Condon, JR(15) Condon, JR(88)
SC
Publication year
Method for absolute estimate of survival
RI PT
Table 2. Mortality outcomes, analytic approaches to survival and covariates in reviewed articles, listed chronologically by country.
Cox PH
Age, stage, sex, treatment, surgery, radiotherapy, chemotherapy, comorbidity, location of residence
Age, stage, SES, geographical remoteness, occupation, marital status Age, sex, SES, geographic remoteness, broad cancer group Age, sex, location of residence, period of dx Age, stage, sex, cancer site, location of residence, SES, comorbidity, treatment Age, sex, cirrhosis Age, period of dx, disease spread, co-morbidity, surgery, location of residence, SES
Cox PH
Stage, location of residence, SES, treatment, co-morbidity
Actuarial
N/A
Age, sex
Not stated
N/A
Sex Age, stage, period of dx, comorbidity, treatment hospital, proximity to treatment, BMI, smoking Age
Gillis, DC(101)
1991
Irvine, J(102)
1991
All-cause and cause-specific Cause-specific
Sheppard, AJ(103)
2011
All-cause
N/A
Cox PH
Nishri, ED(104)
2014
All-cause and
Actuarial
Flexible
ACCEPTED MANUSCRIPT
Mortality outcome(s) cause-specific
Erickson, B(105)
2015
All-cause and cause-specific
New Zealand Lethaby, AE(65) Delahunt, B(66) Gill, AJ(67) Phillips, ARJ(68)
1992 1994 2002 2002
Cause-specific All-cause All-cause All-cause
Jeffreys, M(69)
2005
Excess mortality
Haynes, R(70) Sneyd, MJ(71) Brewer, N(72)
2008 2008 2009
Hill, S(122)
Cox PH Cox PH N/A Cox PH N/A
All-cause Cause-specific Cause-specific
N/A Actuarial Kaplan-Meier Kaplan-Meier Relative survival ratio N/A Kaplan-Meier N/A
2010
Cause-specific
Kaplan-Meier
McLeod, M(74) Priest, P(75) Sammour, T(76) Brewer, N(77)
2010 2010 2010 2011
Cause-specific All-cause All-cause Cause-specific
Kaplan-Meier Not stated Kaplan-Meier N/A
Cox PH Cox PH Cox PH Cox PH
Brewer, N(78)
2012
Cause-specific
N/A
Cox PH
Swart, EM(79)
2013
Sarfati, L(80)
2014
Cause-specific All-cause and cause-specific
2014
Gurney, JK(82)
2015
Lawrenson, R(83)
2015
Obertova, Z(84)
2015
Cause-specific
All-cause and cause-specific All-cause All-cause and cause-specific
None stated None stated Age, sex, SES, distance to major hospital None stated
N/A
Age, stage
Cox PH Cox PH Cox PH
N/A
Cox PH
Age, stage, sex Age, Gleason score Age, stage, period of dx, rurality, grade Age, stage, sex, period of dx, surgery, chemotherapy, comorbidity, rurality, grade, smoking, emergency presentation Age, stage, treatment, surgery, radiotherapy Age, stage Age, stage, sex, subsite Age, stage, period of dx, SES, comorbidity, rurality Age, registration year, SEP, screening history, co-morbidity, travel time to nearest GP and cancer centre Age, stage, tumour grade
Kaplan-Meier
Cox PH
Age, sex, site, stage, SES, location of residence, co-morbidity
Kaplan-Meier
Cox PH
Age, remoteness, histology, tumour size, tumour grade, nodal status, estrogen and progesterone receptor status, HER-2 receptor status, phenotype, vascular invasion, tumour location, laterality, cancer foci, period of dx, referral type, annual surgeon case load
Kaplan-Meier
Cox PH
Age, stage of disease, SES, location of residence
Other
Cox PH
Age, ethnicity, androgen deprivation therapy (ADT) use
Kaplan-Meier
Cox PH
Age, period of dx, SES, location of residence
Cox PH
TE D
EP
AC C
Campbell, ID(81)
Age, stage, gender, tumour subsite, treatment, smoking
M AN U
Kaplan-Meier
RI PT
Publication year
Method for relative estimate of survival Covariates parametric survival models
SC
First author
Method for absolute estimate of survival
31
ACCEPTED MANUSCRIPT
Method for relative estimate of survival
Publication year
Seneviratne, S(123)
2015
Cause-specific
Kaplan-Meier
Cox PH
Screening, SES
Signal, V(86) United States
2015
Cause-specific
N/A
Cox PH
Age, sex, stage, tumour site, co-morbidity
Bleed, DM(26)
1992
Excess mortality
Sugarman, JR(27)
1994
All-cause
Baquet, C(28)
1996
Excess mortality
Frost, F(29)
1996
Gilliland, FD(30)
1996
All-cause, causespecific and excess mortality All-cause
Schiff, M(31)
1997
Excess mortality
Brown, M(32)
1998
All-cause
Gilliland, FD(33)
1998
Excess mortality
Gilliland, FD(34)
1998
Excess mortality
Dennis, TD(35) Clegg, L(36) Li, CI(37) Biggs, ML(38) Jemal, A(25) Chien, C(39)
2000 2002 2003 2004 2004 2005
All-cause Cause-specific All-cause Cause-specific Cause-specific Cause-specific
Wampler, NS(40)
2005
Cause-specific
Cormier, JN(41)
2006
Goggins, WB(42)
2007
Wang, SJ(43)
2007
Relative survival ratio
All-cause and cause-specific All-cause and cause-specific Excess mortality (conditional)
EP
SC
Cox PH
None stated
Age, sex, treatment, rurality
N/A
None stated
Cox PH
Stage, treatment, marital status, location of residence, treatment delay
Cox PH
Age, stage, period of dx, treatment, histology
N/A
None stated
TE D
N/A Relative survival ratio Actuarial Relative survival ratio Relative survival ratio Actuarial Kaplan-Meier N/A Kaplan-Meier Kaplan-Meier N/A
N/A
Covariates
M AN U
Relative survival ratio Other Relative survival ratio
RI PT
First author
AC C
Mortality outcome(s)
Method for absolute estimate of survival
Cox PH
Age, stage, sex, period of dx
Cox PH
Age, stage, sex, treatment
N/A
Stage
N/A Cox PH Cox PH Cox PH Cox PH Cox PH
Age, sex, period of dx, geographic region, cancer site Age, stage Age, stage, surgery, radiotherapy, registry, hormone status Age, stage, period of dx, histology, registry, marital status Age, stage Age, stage, period of dx, surgery, radiotherapy, registry Age, stage, period of dx, treatment, geographical region, marital status, tumor size, metastases, lymph node involvement Age, stage, sex, period of dx, histology, geographic region, marital status, cancer site Age, stage, sex, period of dx, histology, registry, grade, hormone status, tumor size
N/A
Cox PH
Kaplan-Meier
Cox PH
N/A
Cox PH
Relative survival ratio
N/A
Age, stage, sex, histology
32
ACCEPTED MANUSCRIPT
Covariates Age Age, stage, sex, SES, amenability to treatment Age, stage, sex, surgery, registry None stated Age, sex, period of dx, treatment, histology Age, stage, sex, period of dx, treatment, surgery, radiotherapy
Kaplan-Meier
Cox PH
Age, sex, treatment, surgery, radiotherapy, health insurance
Publication year 2009 2009 2010 2010 2011 2011
Du, X(50)
2011
Ooi, SL(51)
2011
Cause-specific
N/A
Smith, CB(52) Wu, X(53)
2011 2011
Cause-specific Cause-specific
Singh, GK(54)
2012
Excess mortality
Kaya, M(55)
2012
Not stated
Kelly, JJ(56) Taghavi, S(57) Dwojak, SM(59)
2012 2012 2013
Excess mortality Cause-specific All-cause
Kaplan-Meier Kaplan-Meier Relative survival ratio Kaplan-Meier and Other Actuarial N/A Kaplan-Meier
Tannenbaum, SL(60)
2013
All-cause
Kaplan-Meier
Dwojak, SM(58)
2014
All-cause
Javid, SH(62)
2014
Cause-specific
N/A
Extended Cox model
Lee, DJ(125)
2014
All-cause
N/A
Cox PH
Mahdi, H(64)
2014
Kaplan-Meier
Cox PH
Tannenbaum, SL(61)
2014
Kaplan-Meier
N/A
All-cause and cause-specific All-cause
M AN U
SC
First author Harper, S(44) Tehranifar, P(45) Fesinmeyer, MD(46) Yu, G(47) Cetin, K(124) Cueto, CV(49)
Cox PH N/A
Age, stage, period of dx, surgery, radiotherapy, SES, registry, hormone status Age, stage Stage, histology
N/A
None stated
Cox PH
Age, period of dx
EP
TE D
Cox PH
Not stated
RI PT
Method for relative estimate of survival N/A Cox PH Cox PH N/A Cox PH Cox PH
AC C
Mortality outcome(s) Cause-specific Cause-specific All-cause All-cause All-cause Cause-specific All-cause and cause-specific
Method for absolute estimate of survival Kaplan-Meier Kaplan-Meier Kaplan-Meier Not stated Kaplan-Meier N/A
N/A Cox PH Cox PH Cox PH
Cox PH
None stated Age, stage, surgery, radiotherapy, grade Age, sex, stage, period of dx, surgery, radiotherapy Age, stage, marital status, insurance, tobacco use, location of residence, teaching hospital and volume, grade, lymph node status, treatment, co-morbidity Age, sex, stage, location of residence, co-morbidity, alcohol, smoking, insurance, co-morbidity Age, stage, SEER registry, period of dx, co-morbidity Age, sex, stage, grade, SES, marital status, smoking, comorbidity, insurance, lymph node status, treatment, histology Age, stage, grade, histology, extent of lymphadenectomy, radiation N/A
Abbreviations: N/A: Not applicable; Cox PH: Cox Proportional Hazards; Period of dx: Period of diagnosis (e.g. calendar year); BMI: Body Mass Index; SES: Socioeconomic status
33
ACCEPTED MANUSCRIPT
Table 3. Summary of potential sources of information bias and the extent to which they were acknowledged in the included literature. n (%) 78 (100) 46 (59) 30 (38) 9 (12) 25 (32) 13 (17)
RI PT
All mortality outcomes Total Acknowledgement of potential ethnic misclassification? Acknowledgement of potential incomplete case ascertainment? Acknowledgement this could be differential by ethnicity? Acknowledgement of potential incomplete death ascertainment? Acknowledgement this could be differential by ethnicity? Cause-specific survival Total Definition provided of a cancer death?
11 (100) 7 (64) 2 (18) 0 (0)
AC C
EP
TE D
M AN U
SC
Comment on the completeness and/or validity of cause of death classification? Excess mortality Total Information provided about elements life tables were specific to? Life tables specific to geographic region of cases? Life tables specific to calendar time?
49 (100) 14 (29) 12 (24)
34
RI PT
ACCEPTED MANUSCRIPT
Figure 1. Flow diagram of literature review process for identifying studies of cancer survival in indigenous populations.
M AN U
SC
Records identified through database search n=1503 MEDLINE n=402 / Embase n=697 / Web of Science n=404
Duplicates removed n=811
Deemed ineligible n=554
EP
TE D
Title and abstract screening n=692
AC C
Full-text assessment n=138
Included in review N=83
Deemed ineligible N=55
ACCEPTED MANUSCRIPT
APPENDIX A: Search Strategy Table 1. MEDLINE search strategy. Three theme-specific searches were combined with “AND”. Indigenous autochton$.mp. OR indigenous$.mp. OR Amerind$.mp. OR (American adj1 indian).mp. OR (native adj1 canadian?).mp. OR inuit?.mp. OR exp Eskimo/ OR Eskimo?.mp. OR Inuktitut.mp. OR Nunavut?.mp. OR Nunavik.mp. OR First Nation?.mp. OR Dene.mp. OR Metis.mp. OR Indians, North American/ OR American Native Continental Ancestry Group/ OR (native adj1 american?).mp. OR ojibway.mp. OR Mohawk.mp. OR Cree.mp. OR yupik.mp. OR aleut.mp. OR (native? adj1 people?).mp. OR (American? adj1 indian?).mp. OR (Alaska? adj1 native?).mp. OR (Aboriginal? adj1 Canadian?).mp. OR (native? Adj1 Hawaii?).mp. OR “Canadian Aboriginals”.mp. OR Aborigin?.mp. OR Oceanic Ancestry Group/ OR “torres strait”.mp. OR maori?.mp. OR Koori$1.mp. OR ngunnawal.mp. OR murri.mp. OR murrdi.mp. OR nyungar.mp. OR yamatji.mp. OR wangai.mp. OR nunga.mp. OR anangu.mp. OR yapa.mp. OR yolngu.mp. OR tiwi.mp. OR anindilyakwa.mp. OR Palawan.mp. Search limited to yr="1990 -Current" where “Current” was September Week 1 2015.
RI PT
Survival Exp Disease-Free Survival/ OR exp Survival Analysis/ OR exp Survival OR exp Survival Rate/ OR survival.mp, ab, sh, ti.
M AN U
SC
Cancer Cancer*.mp. OR exp neoplasm/
Table 2. Embase search strategy. Three theme-specific searches were combined with “AND”. Survival exp event free survival/ OR exp cause specific survival/ OR exp survival/ OR exp survival time/ OR survival*.mp. exp overall survival/ OR exp cancer survival/ OR exp survival rate/ OR exp progression free survival/ OR exp disease free survival/
Indigenous autochton$.mp. OR indigenous$.mp. OR Amerind$.mp. OR (American adj1 indian).mp. OR (native adj1 canadian?).mp. OR inuit?.mp. OR exp Eskimo/ OR Eskimo?.mp. OR Inuktitut.mp. OR Nunavut?.mp. OR Nunavik.mp. OR First Nation?.mp. OR Dene.mp. OR Metis.mp. OR exp American Indian/ OR American Native Continental Ancestry Group/ OR (native adj1 american?).mp. OR ojibway.mp. OR Mohawk.mp. OR Cree.mp. OR yupik.mp. OR aleut.mp. OR (native? adj1 people?).mp. OR (American? adj1 indian?).mp. OR (Alaska? adj1 native?).mp. OR (Aboriginal? adj1 Canadian?).mp. . OR (native? Adj1 Hawaii?).mp. OR “Canadian Aboriginals”.mp. OR Aborigin?.mp. OR Oceanic Ancestry Group/ OR “torres strait”.mp. OR maori?.mp. OR Koori$1.mp. OR ngunnawal.mp. OR murri.mp. OR murrdi.mp. OR nyungar.mp. OR yamatji.mp. OR wangai.mp. OR nunga.mp. OR anangu.mp. OR yapa.mp. OR yolngu.mp. OR tiwi.mp. OR anindilyakwa.mp. OR Palawan.mp. Search limited to yr="1990 -Current" where “Current” was September Week 1 2015.
AC C
EP
TE D
Cancer Cancer*.mp. OR exp neoplasm/
ACCEPTED MANUSCRIPT
Table 3. Web of Science search strategy. Three theme-specific searches were combined with “AND”. Survival Topic=(survival) OR Title=(survival)
Indigenous Topic=(autochton*) OR Topic=(indigenous*) OR Topic=(amerind*) OR Topic=(american$ near/1 indian$) OR Topic=(native$ near/1 canadian$) OR Topic=(inuit$) OR Topic=(eskimo$) OR Topic=(inuktitut) OR Topic=(Nunavut*) OR Topic=(Nunavik) OR Topic=("First Nation$") OR Topic=(Dene) OR Topic=(M?tis) OR Topic=(native$ near/1 american$) OR Topic=(ojibway) OR Topic=(mohawk*) OR Topic=(yupik) OR Topic=(aleut) OR Topic=("native people$") OR Topic=(alaska* near/1 native$) OR Topic=(Aboriginal$ near/1 Canadian$) OR Topic=(native$ near/1 Hawaii*) OR Topic=(Aborigin*) OR Topic=("oceanic ancestry") OR Topic=("torres strait") OR Topic=(maori*) OR Topic=(Koori*) OR Topic=(Ngunnawal) OR Topic=(murri) OR Topic=(murrdi) OR Topic=(nyungar) OR Topic=(yamatji) OR Topic=(wangai) OR Topic=(nunga) OR Topic=(anangu) OR Topic=(yapa) OR Topic=(yolngu) OR Topic=(tiwi) OR Topic=(palawan) Search limited to yr="1990 -Current" where “Current” was September Week 1 2015.
AC C
EP
TE D
M AN U
SC
RI PT
Cancer Topic=(cancer*) OR Title=(cancer*)