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A comparison of three comorbidity indexes in a head and neck cancer population
Oral Oncology 38 (2002) 187–194 www.elsevier.com/locate/oraloncology
A comparison of three comorbidity indexes in a head and neck cancer population Britt C. Reida,*, Anthony J. Albergb, Ann C. Klassenc, R. Gary Rozierd, Isabel Garciae, Deborah M. Winnf, Jonathan M. Sametg a
Department of Oral Health Care Delivery, School of Dentistry, Room 3E-04, University of Maryland, 666 West Baltimore Street, Baltimore, MD 21201, USA b Department of Epidemiology, School of Hygiene and Public Health, 615 Wolfe Street, Johns Hopkins University, Baltimore, MD 2120, USA c Department of Health Policy and Management, School of Hygiene and Public Health, 624 N Broadway, Room 745, Baltimore, MD 21205, USA d Department of Health Policy and Administration, CB#7400 McGavran-Greenberg Bld, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7400, USA e Office of the Director, NIDCR, NIH, Bethesda, MD 20892, USA f Division of Cancer Control and Population Sciences, National Cancer Institute, Executive Plaza North, Room 5114, MSC 7395, 6130 Executive Boulevard, Bethesda, MD 20892-7395, USA g Department of Epidemiology, School of Hygiene and Public Health, 615 Wolfe Street, Johns Hopkins University, USA Received 14 February 2001; accepted 7 March 2001
Abstract We explored differences in prognostic ability for mortality of the established and validated Charlson comorbidity index with two other comorbidity indexes developed for this study. Our study was limited to persons diagnosed with HNCA between 1985 and 1993 in a database formed by a linkage of files from the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program with Health Care Finance Administration Medicare files (n=9386). Adjusted relative risks (RR) and 95% confidence intervals (95%CI) for comorbidity index scores of 1 or more compared to 0 were (RR=1.50, 95% CI 1.43–1.68) Charlson index, (RR=1.53 95% CI 1.42–1.66) HNCA index, and (RR=1.49, 95% CI 1.32–1.68) ATC index, respectively. The Charlson and HNCA indexes displayed dose-response patterns (P-value for trend < 0.0001). Although the ATC index appears promising, the HNCA and Charlson indexes had similar adjusted RR’s, dose-response patterns, P-values, and chi-square scores and appear particularly well-suited to the measurement of comorbidity. # 2002 Elsevier Science Ltd. All rights reserved. Keywords: Comorbidity; Survival; Epidemiology; Head and neck neoplasms; Age >65 years
1. Introduction Comorbidity indexes are commonly used as summary measures for research and clinical purposes. The ability to measure and summarize comorbidity is a necessary step in making adjustments for the confounding effects of comorbidity in both epidemiologic and health services studies. The validity of a comorbidity index is based upon the assumption that increasing comorbidity will be associated with worse health outcomes [1].
* Corresponding author. Tel.: +1-410-706-4923; fax: +1-410-7063028. E-mail addresses: [email protected] (B.C. Reid), [email protected] (A.J. Alberg), [email protected] (A.C. Klassen), [email protected] (R.G. Rozier), [email protected] (I. Garcia), [email protected] (D.M. Winn), [email protected] (J.M. Samet).
Our study aim was to compare three different comorbidity indexes for their prognostic ability in a head and neck cancer (HNCA) population. Of interest was whether one index represented an improvement upon the others with regard to prognostic ability, thus presenting advantages for its use among HNCA patients. Our hypothesis was that a comorbidity index developed specifically for HNCA patients would have greater prognostic ability than one developed for a general medical population. To accomplish this aim and test our hypothesis, we developed three indexes of comorbidity; one was an existing index the other two indexes were derived for this study. We then compared these three indexes for their effects on the estimated association between comorbidity and survival in a HNCA population. We compared the prognostic ability for mortality of: [1] the Charlson index, a widely used and validated
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comorbidity index, [2] the HNCA index, an adaptation of the Charlson index derived specifically for this study, from a HNCA population, and [3] the ATC index, a novel index derived for this study that focuses on conditions associated with alcohol and tobacco use. Among a number of comorbidity indexes that have been developed over the years (including but not limited to: Kaplan and Feinstein [4]; Charlson et al. [3]; Piccirillo [12]), the Charlson comorbidity index (1987) is frequently used because of its predictive ability and relative ease of derivation [2–10]. Though commonly used, the Charlson index contains a few inherent weaknesses, some noted in the original publication [3]. The prevalence and range of medical conditions available for inclusion in the index vary by population and time period. Additionally, the association between a given medical condition and survival (the assigned weight) may vary by calendar time if changes occur in treatment efficacy or disease severity. Finally, possible effect modification across comorbid conditions was not accounted for in the index as it was assumed that relative risk (RR) increases were additive in the log scale for each condition present. To address some of these weaknesses, an adaptation of the Charlson index has been suggested by Cleves et al. [11], which selects and weights comorbid conditions based upon the prevalent medical conditions in a given study population. We developed just such an adaptation of the Charlson index by use of a HNCA population and refer to it in this manuscript as the HNCA index. In a review by Schneeweiss et al. [1], study-specific weights improved the validity of the Charlson index measurement of comorbidity. Because of a high prevalence of alcohol and tobacco exposure, persons with HNCA may experience a high prevalence of comorbidities associated with these agents. Therefore, a novel index was developed that captures alcohol- and tobacco-related comorbidity, the ATC index. The ATC index would therefore have construct validity if found to be prognostic in a HNCA population. Comorbidity appears to have prognostic value for mortality in HNCA populations [8,9,12–14]. Comparing the prognostic value of comorbidity indexes will identify the relative merits of different measurement approaches and help to establish standards of comparability across studies.
2. Methods 2.1. Data Source A linkage of files from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program 1985–1993, a population-based system of cancer
registries, and the Health Care Finance Administration’s (HCFA) Medicare Program form the study database (the SEER/HCFA database). Medicare beneficiaries were US citizens aged 65 years and older. The 11 SEER sites used for this study cover approximately 14% of the US population. The survival status, cause of death, and data on all cancers (except non-melanoma skin cancer) diagnosed in individuals residing within the defined areas of the SEER registries were reported [15]. The Medicare files from HCFA available for the linked database include: (1) the denominator files which provide demographic information, entitlement status, and enrollment status for each beneficiary; and (2) a Medicare Provider and Analysis Review file which is a summary of in-patient records accumulated by each beneficiary with diagnoses recorded using the International Classification for Disease, 9th edition, Clinical Modification (ICD-9-CM). Potosky et al. [16] published details of the linkage of the SEER and HCFA files, including the exact algorithm used for linkage. The linkage project successfully merged 93% of all SEER cancer cases in persons diagnosed at age 65 or more years with the appropriate Medicare files. 2.2. Selection criteria Persons included in the SEER/HCFA study database were those in the SEER registry database and successfully matched against the HCFA master-file. The study database is further limited to those with microscopically confirmed, incident, squamous cell carcinomas of the head and neck region [anatomic sites oral cavity, pharynx, and larynx (ICD-9-CM codes 141–146.9, 148– 149.9, 161–161.9)]. Exclusions were for persons with cancers diagnosed at autopsy or from death certificates only (n=161), incomplete race or historic stage at diagnosis data (n=1180), and those with entitlement to Medicare based upon disability (n=39). Persons enrolled in a health maintenance organization or not entitled to Medicare part A for a full year were excluded due to the inability to capture all of their inpatient care information (n=1646). All cases were at least age 66 years at diagnosis to allow a full year of entitlement to Medicare part A. The study group meeting all of these criteria totaled 9386 persons. The in-patient files were searched for comorbidities recorded in the 11-month time window preceding the month of diagnosis with head and neck cancer. The month of diagnosis was excluded so that ascertainment of comorbidity would not be dependent upon treatment for HNCA. This was a concern because virtually all surgical, but few radiation patients, were hospitalized, and hospitalization was required to generate an opportunity to assess comorbidity. Excluding the
B.C. Reid et al. / Oral Oncology 38 (2002) 187–194
month of diagnosis also avoids the possibility that the recorded comorbidity was a result of treatment. The vast majority of patients in the database [n=8261 (88.0%)] did not have any in-patient records generated within the 11-month window prior to the month of diagnosis. Index scores were derived from ICD-9-CM codes contained in the MEDPAR files as described elsewhere [10].
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committees. This index tends to emphasize chronic comorbid conditions anticipated to be more prevalent in HNCA patients than those without HNCA. Hypertension was included in the index, although its association with alcohol use is complex and dose-dependent [17]. The ATC index consists of a simple count of conditions present and does not attempt to weight conditions for seriousness, it has a theoretical range of 0–11 (Fig. 1).
2.3. Comorbidity indexes Three different index measures of comorbidity were used: 1. The Charlson index; Charlson et al. published an index that predicted 1- and 10-year survival of hospitalized patients based on the number and seriousness of comorbid conditions [3]. The Charlson index includes 19 comorbid conditions and weights each condition using integer weights (Fig. 1). The Charlson conditions and weights, which were derived from a hospitalized general medical population were applied to the SEER/ HCFA HNCA population, it has a theoretical range of 0–33. Scores for the Charlson index were developed for our study using the in-patient records of each patient in the SEER/HCFA database and the ICD-9-CM codes contained in the MEDPAR files as described elsewhere [10]. 2. The head and neck cancer comorbidity (HNCA) index; Cleves et al. [11] evaluated two different methods of calculating the Charlson index and concluded that it is preferable to include conditions prevalent in a given population and to calculate weights for specific populations, diseases, and outcomes. Therefore, a second index was developed specifically for this HNCA population and referred to as the HNCA index. The HNCA index was derived from in-patient records using proportional hazard regression with non-cancer mortality as outcome. An adjusted relative risk (RR) for each condition was used as a weight. An index score was then calculated by multiplying each weight with its corresponding dichotomous indicator (1 if present, 0 if not present) and summed for all conditions prevalent to arrive at a total index score for each patient, it has a theoretical range of 0–10 (Fig. 1). 3. The ATC (alcohol and tobacco-related comorbidity) index: this index was created for our study and based upon comorbid conditions associated with alcohol and tobacco use, the primary etiologic agents for HNCA. The ATC index included only comorbid conditions with substantial causal associations with alcohol or tobacco use as established in Surgeon’s General Reports or by consensus
Worked example: calculating index scores for two hypothetical patients. Patient No. 1: has two conditions listed in their in-patient records during the 11 months preceding diagnosis with HNCA, arthritis and hemiplegia. The Charlson index does not include arthritis, therefore no score is given for this condition, the Charlson index does include hemiplegia and gives it a weight of 2. The Charlson index score for patient No. 1 is therefore 0+2 for a total score of 2. The HNCA and the ATC indexes do not include either condition and would therefore both give index scores of 0 for patient No. 1. Patient No. 2: has one condition listed in their in-patient records during the 11 months preceding diagnosis with HNCA, chronic pulmonary disease. The Charlson, HNCA, and ATC indexes all include the condition and give it a weight of 1, therefore all three indexes would give patient No. 2 the same score of 1. 2.4. Analyses The proportional hazard regression methods used in this study provide estimates of adjusted relative hazard for each variable in the model. Relative hazards are, in turn, estimates of the relative risk (rate ratio) over the entire period of observation for each subject. Interested readers are referred to Tibshirani [18] for an introduction to proportional hazards models and the relationship between relative risk and relative hazard. Indexes were directly compared by Spearman bivariate correlation, and then indirectly compared by evaluating their associations with survival. For this purpose, indexes were compared by univariate RR, adjusted RR, and with a chi-square score from a proportional hazards regression that included the variables of age and stage at diagnosis, race, sex, marital and socioeconomic status, histologic grade, anatomic site, treatment, and pre-1991 diagnosis. The chi-square score is the overall model partial likelihood ratio which measures the model’s predictive ability relative to a constant hazard model. Socioeconomic status (SES) was assessed by household wealth and education at the zip code level. Both socioeconomic measures were among standard SES
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Fig. 1. Construction of the comorbidity indexes.
variables available to SEER/HCFA database users [16]. Education was measured at the zip code level, by using 1990 census data to classify each subject according to whether 20% of those aged 25 years or more living in the same zip code had completed their high school educa-
tion. Household wealth was assigned at the zip code level using 1990 census bureau data (Table 1). To examine possible dose-response relationships, each index was inserted as an ordinal variable into the proportional hazards regression (P-value for trend from the Wald
B.C. Reid et al. / Oral Oncology 38 (2002) 187–194 Table 1 Frequency distribution of selected characteristics of the SEER/HCFA, head and neck cancer patient population 1985–1993 Variable
Percent (n=9386)
Age at diagnosis 66–75 75–84 85+
61.9 31.6 06.5
Sex Male
70.5
Race White Black
91.9 08.1
Marital status Single Married No longer married/unknown
0.78 55.2 37.0
Education (assigned at zip code level) 420% did not complete high school >20% did not complete high school
24.3 75.7
Household wealth (assigned at zip code level) 0< X 4$93,000 $93,000< X 4$135,000 $135,000< X Not available
29.6 28.8 28.5 13.1
Anatomic site Oral cavity Pharynx Larynx
38.6 19.8 41.6
Histologic grade 1 or ungraded 2 3 4
37.9 40.5 20.9 00.7
Historic stage In-situ Local Regional Distant
03.8 41.1 44.3 10.8
Treatment Received None documented
96.4 03.6
Vital status Alive Non-cancer deaths Cancer deaths Dead, cause unknown
41.0 18.7 38.4 01.9
statistic). To examine differences between indexes in predicting short- versus longer-term survival, adjusted RR estimates were developed stratified by survival time. All analyses were accomplished using SPSS statistical software [19].
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The outcome of interest, all-cause mortality, has no competing causes, thus satisfying the assumption of proportional hazards regression methods that censoring must be independent of competing causes for the outcome [20]. The estimated RR for all-cause mortality indicates the risk of death from any cause at any time during the period of observation. Survival status was known for all study subjects as of 31 March 1994. The start time for computation of survival was the month of diagnosis with first primary head and neck cancer. A dichotomous variable for a pre-1991 diagnosis was created to check for a possible secular trend resulting from the institution of a new reporting system for comorbidities by Medicare in 1990. This variable along with log minus log plots serve as a check for violation of the proportional hazards assumption underlying the use of proportional hazards regression methods.
3. Results The descriptive characteristics of the study population are found in Table 1. Few persons had no documented treatment for their cancers (3.6%). For every AfricanAmerican person with HNCA there were about 11 white persons. More than half of the population (55.2%) was married and the majority (55.1%) had regional or distant stage disease at the time of diagnosis. Few (6.5%) persons were aged 85 or more years at diagnosis; most (61.9%) were aged 65–74 years. Oral cavity and laryngeal cancers were about twice as frequent as pharyngeal cancers. The ratio of females with HNCA to males was about 1:2. Of those that had been diagnosed with HNCA and died from 1985 to 1993 (60%), 31.8% had a non-cancer cause of death assigned on their death certificates. The Spearman correlation between the Charlson and HNCA indexes was 0.81, between the Charlson and ATC index 0.24, and between the HNCA and ATC index 0.22 (all P-values < 0.001). RR (and 95% confidence intervals) for positive scores for each comorbidity index adjusted for age and historic stage at diagnosis, race, sex, marital status, socioeconomic status, histologic grade, anatomic site, treatment, and pre-1991 diagnosis were 1.50 (1.43–1.68) Charlson index, 1.53 (1.42–1.66) HNCA index, and 1.49 (1.32–1.68) ATC index (Table 2). The overall chi-square scores, with 17 degrees of freedom (d.f.) in a multivariate model were 2002, 2012, and 1925 for the Charlson, HNCA, and ATC indexes, respectively (Table 2). The adjusted RRs for index scores of 0, 1, and 2+, respectively were HNCA index 1.00, 1.42, 1.69 and Charlson index 1.00, 1.41, 1.78; both had a P-value for trend < 0.0001 (Table 3). The ATC index showed the same P-value for trend as the other two indexes but displayed a non-linear pattern with adjusted RRs for index scores of 0, 1, and 2+ of 1.00, 1.53, and 0.76,
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Table 2 Comparison of three comorbidity indexes by crude and adjusted relative risks (RR) with 95% confidence intervals (95% CI) and overall chi-square score, SEER/HCFA, head and neck cancer patients, 1985–1993 Index
Crude RR and (95% CI)
Adjusted RR and (95% CI)a
Change in RR by adjustment
Overall chi-squareb
HNCAc Charlsond ATCe
1.68 (1.56–1.82) 1.58 (1.46–1.70) 1.55 (1.37–1.74)
1.53 (1.42–1.66) 1.50 (1.43–1.68) 1.49 (1.32–1.68)
9.5% 5.0% 4.0%
2012 2002 1925
a RR of all-cause mortality for comorbidity from a proportional hazard regression adjusted for age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education, household wealth, histologic grade, and treatment. b The overall chi-square score (with 17 degrees of freedom) for a proportional hazards model that included a given comorbidity index and the covariates age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education at zip code level, mean household wealth at zip code level, histologic grade, and treatment. The overall chi-square measures the model’s predictive ability relative to a constant hazard model. c Head and neck cancer comorbidity index score of (1 or more) with 0 as reference. d Charlson index score of (1 or more) with 0 as reference. e Alcohol and tobacco related comorbidity index score of (1 or more) with 0 as reference.
Table 3 Adjusted relative risk (RR) dose-response patterns with 95% confidence intervals (95% CI) and trend statistics for three comorbidity indexes, SEER/HCFA, head and neck cancer patients, 1985–1993, n=9386 ATC index RRa
HNCA index 95% CI
RRa
Charlson index 95% CI
RRa
95% CI
Index score 0 1+
1.00 1.49
– 1.32–1.68
1.00 1.53
– 1.42–1.66
1.00 1.50
– 1.43–1.68
Index score 0 1 2+
1.00 1.53 0.76
– 1.35–1.72 0.34–1.69
1.00 1.38 1.61
– 1.20–1.58 1.47–1.76
1.00 1.33 1.83
– 1.21–1.47 1.64–2.05
P-value for trend
<0.0001
<0.0001
<0.0001
a All relative risks are for all-cause mortality and adjusted for age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education at the zip code level, household wealth at the zip code level, histologic grade, and treatment. P-value for trend from the Wald statistic.
respectively. Few subjects had ATC scores of 2+ (Table 4). Adjusted RR estimates were derived for groups of subjects surviving at least 1, 2, 3, 4, and 5 years (Table 5). All three indexes displayed little change in adjusted RR estimates across survival time categories.
4. Discussion This study was conducted to assess the relative prognostic value of three measures of comorbidity: the Charlson, HNCA, and ATC indexes. The Charlson and HNCA indexes had a moderately high Spearman bivariate correlation (0.81 P < 0.001). This finding was not surprising given the similarities in derivation of the Charlson and HNCA indexes. The ATC index, which is limited to a smaller spectrum of comorbidities and does not weight for seriousness, was poorly correlated with the other two indexes. Despite the lack of correlation of the ATC index with the other two indexes, the adjusted RR was similar in magnitude, (ATC RR=1.49, 95%CI 1.32–1.68),
(Charlson RR=1.50, 95% CI 1.43–1.68), (HNCA RR= 1.53, 95%CI 1.42–1.66). Overall chi-square scores were derived from multivariable models, with 17 d.f., that differed only by comorbidity index used. The overall chi-square scores for the Charlson and HNCA indexes were virtually identical followed by the ATC index (2012, 2002, and 1925, respectively). The Charlson and HNCA indexes were also virtually indistinguishable when examined for dose-response patterns. The ATC index did not display a linear trend, possibly because of so few subjects in the 2+ score category (n=12, Table 4), and therefore was not judged to have a clear dose-response pattern. All three indexes displayed consistency in adjusted RR estimates across survival time categories indicating prognostic value for mortality for short- as well as longer-term survivors (Table 5). One previous study has tested the Charlson index in a HNCA population [9]. Singh et al. [9] reported findings from 88 HNCA patients diagnosed at or prior to age 45, drawn from three New York-area hospitals over a 12year period. The outcome was tumor-specific survival,
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B.C. Reid et al. / Oral Oncology 38 (2002) 187–194 Table 4 Distribution of the SEER/HCFA head and neck cancer population 1985–1993 (n=9386) among the comorbidity indexes Scorea
0 1 2+ a
Charlson
HNCA
ATC
%
(n)
%
(n)
%
(n)
88.0 07.1 04.9
(8261) (663) (462)
88.9 03.5 07.6
(8344) (325) (717)
95.8 04.0 0.01
(8995) (379) (12)
Fewer than 2% of persons had scores of three or more using any of the indexes.
Table 5 Adjusted relative risks (RR) and 95% confidence intervals (95% CI) for comorbidity indexes by selected survival time categories, SEER/HCFA, head and neck cancer patients, 1985–1993 Survival time categoriesa
All subjects included (n=9386) Includes only subjects surviving >1 year (n=6705) >2 years (n=4524) >3 years (n=3175) >4 years (n=2386) >5 years (n=1692)
Charlson Index
HNCA Index
ATC Index
RRb
95% CI
RRb
95% CI
RRb
95% CI
1.50
1.43–1.60
1.53
1.42–1.66
1.49
1.32–1.68
1.35 1.41 1.42 1.38 1.35
1.21–1.50 1.22–1.63 1.17–1.71 1.09–1.74 1.01–1.81
1.46 1.46 1.36 1.38 1.28
1.30–1.64 1.25–1.71 1.11–1.67 1.07–1.78 0.92–1.79
1.32 1.57 1.70 1.44 1.43
1.11–1.57 1.26–1.96 1.29–2.22 1.01–2.05 0.92–2.22
a
The same proportional hazards regression was conducted using only those subjects that had already survived for the indicated amount of time. For example, the adjusted relative risk for a Charlson index score of 1 or more compared to 0, was 1.50 if all subjects were analyzed and 1.35 if only those subjects surviving more than 5 years were analyzed. b All relative risks are for all-cause mortality and adjusted for age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education at the zip code level, household wealth at the zip code level, histologic grade, and treatment.
which has competing causes (non-cancer causes of death); a violation of the assumption of independent censoring underlying the (Kaplan–Meier and Cox regression) survival methods used [20]. The Charlson index was found to be an independent predictor of survival, supporting the findings of the present study despite differences in population source, age distribution, and analytic methods. The use of ICD-9-CM codes to identify comorbid conditions in the derivation of the HNCA index allowed the inclusion of non-disease codes. For example, electrolyte imbalance is not a distinct disease entity and could be the result of a number of medical conditions. Yet electrolyte imbalance was prevalent in the HNCA population; it predicted survival; and satisfied the definition of a comorbid condition, and was therefore included as a comorbid condition. The Charlson, HNCA, and ATC indexes had similar adjusted RR estimates. The Charlson and HNCA indexes were slight improvements upon the ATC index with regard to overall chi-square scores and doseresponse patterns. The three indexes were nonetheless quite comparable in assessing the association of comorbidity and survival in this population. The Charlson index can be used and compared across different populations and studies as it does not require recalculation
for each new application. This advantage, coupled with comparable validity, makes the Charlson index preferable to the others for comorbidity measurement in a HNCA population. Nonetheless, other even simpler measures of comorbidity, including number of hospitalized days, have been reported in one study [21] to provide comparable predictions of mortality in claims-derived databases. Although strengths of our study included its large size and being population-based, it was nonetheless limited by inclusion of only those aged 66 or more at diagnosis Another limitation was the insensitive measurement of comorbidity by use of in-patient records which capture only the more severe cases of comorbid disease. In contrast to the low sensitivity, the specificity of comorbidity measurement was likely very high. The ascertainment of comorbidity required that a person be sufficiently ill to be hospitalized for their comorbid condition in the year prior to their diagnosis with HNCA. As a result, virtually no persons would be classified falsely as having comorbidity — a false positive rate of nearly zero — assuring a very high specificity. It was notable that despite the use of an insensitive comorbidity measurement, all three indexes demonstrated an independent and significant association with survival, supporting the use of this approach.
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The measurement of comorbidity has applications in research and clinical settings. In research it can be used to adjust for group differences in comorbidity to reduce possible confounding of study associations. In the clinical setting, comorbidity can be included in developing a prognosis for individual patients. Additional studies to validate these findings among persons diagnosed with HNCA at ages younger than 66 years and using more sensitive measures of comorbidity are needed. All three indexes studied — Charlson, HNCA, ATC — displayed strong associations with survival. Although the ATC index shows promise, the HNCA and Charlson indexes had similar adjusted RR estimates, dose-response patterns, P-values, and overall chi-square scores, and appear particularly well-suited to measuring comorbidity in this population. The Charlson index enjoys the additional advantage of allowing comparisons across populations and studies and may therefore be preferable to the HNCA and ATC indexes for research purposes. However, given that comorbidity is predictive of survival among persons with HNCA, it would appear from this study that efforts to include comorbidity in prognostic evaluations should take priority over concerns about how to measure comorbidity.
Acknowledgements Thanks to James Tonascia, Joan Warren, Arnie Potosky, and Nicki Schussler for help and comments during the study. B.C. Reid received support from a National Research Scientist Award from the NIDCR (T32 DE-7255), A.J. Alberg received support from a Preventive Oncology Academic Award from the NCI (CA73790), R.G. Rozier received support from a W.R. Kenan award from the University of North Carolina.
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A comparison of three comorbidity indexes in a head and neck cancer population Britt C. Reida,*, Anthony J. Albergb, Ann C. Klassenc, R. Gary Rozierd, Isabel Garciae, Deborah M. Winnf, Jonathan M. Sametg a
Department of Oral Health Care Delivery, School of Dentistry, Room 3E-04, University of Maryland, 666 West Baltimore Street, Baltimore, MD 21201, USA b Department of Epidemiology, School of Hygiene and Public Health, 615 Wolfe Street, Johns Hopkins University, Baltimore, MD 2120, USA c Department of Health Policy and Management, School of Hygiene and Public Health, 624 N Broadway, Room 745, Baltimore, MD 21205, USA d Department of Health Policy and Administration, CB#7400 McGavran-Greenberg Bld, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7400, USA e Office of the Director, NIDCR, NIH, Bethesda, MD 20892, USA f Division of Cancer Control and Population Sciences, National Cancer Institute, Executive Plaza North, Room 5114, MSC 7395, 6130 Executive Boulevard, Bethesda, MD 20892-7395, USA g Department of Epidemiology, School of Hygiene and Public Health, 615 Wolfe Street, Johns Hopkins University, USA Received 14 February 2001; accepted 7 March 2001
Abstract We explored differences in prognostic ability for mortality of the established and validated Charlson comorbidity index with two other comorbidity indexes developed for this study. Our study was limited to persons diagnosed with HNCA between 1985 and 1993 in a database formed by a linkage of files from the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program with Health Care Finance Administration Medicare files (n=9386). Adjusted relative risks (RR) and 95% confidence intervals (95%CI) for comorbidity index scores of 1 or more compared to 0 were (RR=1.50, 95% CI 1.43–1.68) Charlson index, (RR=1.53 95% CI 1.42–1.66) HNCA index, and (RR=1.49, 95% CI 1.32–1.68) ATC index, respectively. The Charlson and HNCA indexes displayed dose-response patterns (P-value for trend < 0.0001). Although the ATC index appears promising, the HNCA and Charlson indexes had similar adjusted RR’s, dose-response patterns, P-values, and chi-square scores and appear particularly well-suited to the measurement of comorbidity. # 2002 Elsevier Science Ltd. All rights reserved. Keywords: Comorbidity; Survival; Epidemiology; Head and neck neoplasms; Age >65 years
1. Introduction Comorbidity indexes are commonly used as summary measures for research and clinical purposes. The ability to measure and summarize comorbidity is a necessary step in making adjustments for the confounding effects of comorbidity in both epidemiologic and health services studies. The validity of a comorbidity index is based upon the assumption that increasing comorbidity will be associated with worse health outcomes [1].
* Corresponding author. Tel.: +1-410-706-4923; fax: +1-410-7063028. E-mail addresses: [email protected] (B.C. Reid), [email protected] (A.J. Alberg), [email protected] (A.C. Klassen), [email protected] (R.G. Rozier), [email protected] (I. Garcia), [email protected] (D.M. Winn), [email protected] (J.M. Samet).
Our study aim was to compare three different comorbidity indexes for their prognostic ability in a head and neck cancer (HNCA) population. Of interest was whether one index represented an improvement upon the others with regard to prognostic ability, thus presenting advantages for its use among HNCA patients. Our hypothesis was that a comorbidity index developed specifically for HNCA patients would have greater prognostic ability than one developed for a general medical population. To accomplish this aim and test our hypothesis, we developed three indexes of comorbidity; one was an existing index the other two indexes were derived for this study. We then compared these three indexes for their effects on the estimated association between comorbidity and survival in a HNCA population. We compared the prognostic ability for mortality of: [1] the Charlson index, a widely used and validated
1368-8375/02/$ - see front matter # 2002 Elsevier Science Ltd. All rights reserved. PII: S1368-8375(01)00044-6
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comorbidity index, [2] the HNCA index, an adaptation of the Charlson index derived specifically for this study, from a HNCA population, and [3] the ATC index, a novel index derived for this study that focuses on conditions associated with alcohol and tobacco use. Among a number of comorbidity indexes that have been developed over the years (including but not limited to: Kaplan and Feinstein [4]; Charlson et al. [3]; Piccirillo [12]), the Charlson comorbidity index (1987) is frequently used because of its predictive ability and relative ease of derivation [2–10]. Though commonly used, the Charlson index contains a few inherent weaknesses, some noted in the original publication [3]. The prevalence and range of medical conditions available for inclusion in the index vary by population and time period. Additionally, the association between a given medical condition and survival (the assigned weight) may vary by calendar time if changes occur in treatment efficacy or disease severity. Finally, possible effect modification across comorbid conditions was not accounted for in the index as it was assumed that relative risk (RR) increases were additive in the log scale for each condition present. To address some of these weaknesses, an adaptation of the Charlson index has been suggested by Cleves et al. [11], which selects and weights comorbid conditions based upon the prevalent medical conditions in a given study population. We developed just such an adaptation of the Charlson index by use of a HNCA population and refer to it in this manuscript as the HNCA index. In a review by Schneeweiss et al. [1], study-specific weights improved the validity of the Charlson index measurement of comorbidity. Because of a high prevalence of alcohol and tobacco exposure, persons with HNCA may experience a high prevalence of comorbidities associated with these agents. Therefore, a novel index was developed that captures alcohol- and tobacco-related comorbidity, the ATC index. The ATC index would therefore have construct validity if found to be prognostic in a HNCA population. Comorbidity appears to have prognostic value for mortality in HNCA populations [8,9,12–14]. Comparing the prognostic value of comorbidity indexes will identify the relative merits of different measurement approaches and help to establish standards of comparability across studies.
2. Methods 2.1. Data Source A linkage of files from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program 1985–1993, a population-based system of cancer
registries, and the Health Care Finance Administration’s (HCFA) Medicare Program form the study database (the SEER/HCFA database). Medicare beneficiaries were US citizens aged 65 years and older. The 11 SEER sites used for this study cover approximately 14% of the US population. The survival status, cause of death, and data on all cancers (except non-melanoma skin cancer) diagnosed in individuals residing within the defined areas of the SEER registries were reported [15]. The Medicare files from HCFA available for the linked database include: (1) the denominator files which provide demographic information, entitlement status, and enrollment status for each beneficiary; and (2) a Medicare Provider and Analysis Review file which is a summary of in-patient records accumulated by each beneficiary with diagnoses recorded using the International Classification for Disease, 9th edition, Clinical Modification (ICD-9-CM). Potosky et al. [16] published details of the linkage of the SEER and HCFA files, including the exact algorithm used for linkage. The linkage project successfully merged 93% of all SEER cancer cases in persons diagnosed at age 65 or more years with the appropriate Medicare files. 2.2. Selection criteria Persons included in the SEER/HCFA study database were those in the SEER registry database and successfully matched against the HCFA master-file. The study database is further limited to those with microscopically confirmed, incident, squamous cell carcinomas of the head and neck region [anatomic sites oral cavity, pharynx, and larynx (ICD-9-CM codes 141–146.9, 148– 149.9, 161–161.9)]. Exclusions were for persons with cancers diagnosed at autopsy or from death certificates only (n=161), incomplete race or historic stage at diagnosis data (n=1180), and those with entitlement to Medicare based upon disability (n=39). Persons enrolled in a health maintenance organization or not entitled to Medicare part A for a full year were excluded due to the inability to capture all of their inpatient care information (n=1646). All cases were at least age 66 years at diagnosis to allow a full year of entitlement to Medicare part A. The study group meeting all of these criteria totaled 9386 persons. The in-patient files were searched for comorbidities recorded in the 11-month time window preceding the month of diagnosis with head and neck cancer. The month of diagnosis was excluded so that ascertainment of comorbidity would not be dependent upon treatment for HNCA. This was a concern because virtually all surgical, but few radiation patients, were hospitalized, and hospitalization was required to generate an opportunity to assess comorbidity. Excluding the
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month of diagnosis also avoids the possibility that the recorded comorbidity was a result of treatment. The vast majority of patients in the database [n=8261 (88.0%)] did not have any in-patient records generated within the 11-month window prior to the month of diagnosis. Index scores were derived from ICD-9-CM codes contained in the MEDPAR files as described elsewhere [10].
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committees. This index tends to emphasize chronic comorbid conditions anticipated to be more prevalent in HNCA patients than those without HNCA. Hypertension was included in the index, although its association with alcohol use is complex and dose-dependent [17]. The ATC index consists of a simple count of conditions present and does not attempt to weight conditions for seriousness, it has a theoretical range of 0–11 (Fig. 1).
2.3. Comorbidity indexes Three different index measures of comorbidity were used: 1. The Charlson index; Charlson et al. published an index that predicted 1- and 10-year survival of hospitalized patients based on the number and seriousness of comorbid conditions [3]. The Charlson index includes 19 comorbid conditions and weights each condition using integer weights (Fig. 1). The Charlson conditions and weights, which were derived from a hospitalized general medical population were applied to the SEER/ HCFA HNCA population, it has a theoretical range of 0–33. Scores for the Charlson index were developed for our study using the in-patient records of each patient in the SEER/HCFA database and the ICD-9-CM codes contained in the MEDPAR files as described elsewhere [10]. 2. The head and neck cancer comorbidity (HNCA) index; Cleves et al. [11] evaluated two different methods of calculating the Charlson index and concluded that it is preferable to include conditions prevalent in a given population and to calculate weights for specific populations, diseases, and outcomes. Therefore, a second index was developed specifically for this HNCA population and referred to as the HNCA index. The HNCA index was derived from in-patient records using proportional hazard regression with non-cancer mortality as outcome. An adjusted relative risk (RR) for each condition was used as a weight. An index score was then calculated by multiplying each weight with its corresponding dichotomous indicator (1 if present, 0 if not present) and summed for all conditions prevalent to arrive at a total index score for each patient, it has a theoretical range of 0–10 (Fig. 1). 3. The ATC (alcohol and tobacco-related comorbidity) index: this index was created for our study and based upon comorbid conditions associated with alcohol and tobacco use, the primary etiologic agents for HNCA. The ATC index included only comorbid conditions with substantial causal associations with alcohol or tobacco use as established in Surgeon’s General Reports or by consensus
Worked example: calculating index scores for two hypothetical patients. Patient No. 1: has two conditions listed in their in-patient records during the 11 months preceding diagnosis with HNCA, arthritis and hemiplegia. The Charlson index does not include arthritis, therefore no score is given for this condition, the Charlson index does include hemiplegia and gives it a weight of 2. The Charlson index score for patient No. 1 is therefore 0+2 for a total score of 2. The HNCA and the ATC indexes do not include either condition and would therefore both give index scores of 0 for patient No. 1. Patient No. 2: has one condition listed in their in-patient records during the 11 months preceding diagnosis with HNCA, chronic pulmonary disease. The Charlson, HNCA, and ATC indexes all include the condition and give it a weight of 1, therefore all three indexes would give patient No. 2 the same score of 1. 2.4. Analyses The proportional hazard regression methods used in this study provide estimates of adjusted relative hazard for each variable in the model. Relative hazards are, in turn, estimates of the relative risk (rate ratio) over the entire period of observation for each subject. Interested readers are referred to Tibshirani [18] for an introduction to proportional hazards models and the relationship between relative risk and relative hazard. Indexes were directly compared by Spearman bivariate correlation, and then indirectly compared by evaluating their associations with survival. For this purpose, indexes were compared by univariate RR, adjusted RR, and with a chi-square score from a proportional hazards regression that included the variables of age and stage at diagnosis, race, sex, marital and socioeconomic status, histologic grade, anatomic site, treatment, and pre-1991 diagnosis. The chi-square score is the overall model partial likelihood ratio which measures the model’s predictive ability relative to a constant hazard model. Socioeconomic status (SES) was assessed by household wealth and education at the zip code level. Both socioeconomic measures were among standard SES
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Fig. 1. Construction of the comorbidity indexes.
variables available to SEER/HCFA database users [16]. Education was measured at the zip code level, by using 1990 census data to classify each subject according to whether 20% of those aged 25 years or more living in the same zip code had completed their high school educa-
tion. Household wealth was assigned at the zip code level using 1990 census bureau data (Table 1). To examine possible dose-response relationships, each index was inserted as an ordinal variable into the proportional hazards regression (P-value for trend from the Wald
B.C. Reid et al. / Oral Oncology 38 (2002) 187–194 Table 1 Frequency distribution of selected characteristics of the SEER/HCFA, head and neck cancer patient population 1985–1993 Variable
Percent (n=9386)
Age at diagnosis 66–75 75–84 85+
61.9 31.6 06.5
Sex Male
70.5
Race White Black
91.9 08.1
Marital status Single Married No longer married/unknown
0.78 55.2 37.0
Education (assigned at zip code level) 420% did not complete high school >20% did not complete high school
24.3 75.7
Household wealth (assigned at zip code level) 0< X 4$93,000 $93,000< X 4$135,000 $135,000< X Not available
29.6 28.8 28.5 13.1
Anatomic site Oral cavity Pharynx Larynx
38.6 19.8 41.6
Histologic grade 1 or ungraded 2 3 4
37.9 40.5 20.9 00.7
Historic stage In-situ Local Regional Distant
03.8 41.1 44.3 10.8
Treatment Received None documented
96.4 03.6
Vital status Alive Non-cancer deaths Cancer deaths Dead, cause unknown
41.0 18.7 38.4 01.9
statistic). To examine differences between indexes in predicting short- versus longer-term survival, adjusted RR estimates were developed stratified by survival time. All analyses were accomplished using SPSS statistical software [19].
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The outcome of interest, all-cause mortality, has no competing causes, thus satisfying the assumption of proportional hazards regression methods that censoring must be independent of competing causes for the outcome [20]. The estimated RR for all-cause mortality indicates the risk of death from any cause at any time during the period of observation. Survival status was known for all study subjects as of 31 March 1994. The start time for computation of survival was the month of diagnosis with first primary head and neck cancer. A dichotomous variable for a pre-1991 diagnosis was created to check for a possible secular trend resulting from the institution of a new reporting system for comorbidities by Medicare in 1990. This variable along with log minus log plots serve as a check for violation of the proportional hazards assumption underlying the use of proportional hazards regression methods.
3. Results The descriptive characteristics of the study population are found in Table 1. Few persons had no documented treatment for their cancers (3.6%). For every AfricanAmerican person with HNCA there were about 11 white persons. More than half of the population (55.2%) was married and the majority (55.1%) had regional or distant stage disease at the time of diagnosis. Few (6.5%) persons were aged 85 or more years at diagnosis; most (61.9%) were aged 65–74 years. Oral cavity and laryngeal cancers were about twice as frequent as pharyngeal cancers. The ratio of females with HNCA to males was about 1:2. Of those that had been diagnosed with HNCA and died from 1985 to 1993 (60%), 31.8% had a non-cancer cause of death assigned on their death certificates. The Spearman correlation between the Charlson and HNCA indexes was 0.81, between the Charlson and ATC index 0.24, and between the HNCA and ATC index 0.22 (all P-values < 0.001). RR (and 95% confidence intervals) for positive scores for each comorbidity index adjusted for age and historic stage at diagnosis, race, sex, marital status, socioeconomic status, histologic grade, anatomic site, treatment, and pre-1991 diagnosis were 1.50 (1.43–1.68) Charlson index, 1.53 (1.42–1.66) HNCA index, and 1.49 (1.32–1.68) ATC index (Table 2). The overall chi-square scores, with 17 degrees of freedom (d.f.) in a multivariate model were 2002, 2012, and 1925 for the Charlson, HNCA, and ATC indexes, respectively (Table 2). The adjusted RRs for index scores of 0, 1, and 2+, respectively were HNCA index 1.00, 1.42, 1.69 and Charlson index 1.00, 1.41, 1.78; both had a P-value for trend < 0.0001 (Table 3). The ATC index showed the same P-value for trend as the other two indexes but displayed a non-linear pattern with adjusted RRs for index scores of 0, 1, and 2+ of 1.00, 1.53, and 0.76,
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Table 2 Comparison of three comorbidity indexes by crude and adjusted relative risks (RR) with 95% confidence intervals (95% CI) and overall chi-square score, SEER/HCFA, head and neck cancer patients, 1985–1993 Index
Crude RR and (95% CI)
Adjusted RR and (95% CI)a
Change in RR by adjustment
Overall chi-squareb
HNCAc Charlsond ATCe
1.68 (1.56–1.82) 1.58 (1.46–1.70) 1.55 (1.37–1.74)
1.53 (1.42–1.66) 1.50 (1.43–1.68) 1.49 (1.32–1.68)
9.5% 5.0% 4.0%
2012 2002 1925
a RR of all-cause mortality for comorbidity from a proportional hazard regression adjusted for age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education, household wealth, histologic grade, and treatment. b The overall chi-square score (with 17 degrees of freedom) for a proportional hazards model that included a given comorbidity index and the covariates age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education at zip code level, mean household wealth at zip code level, histologic grade, and treatment. The overall chi-square measures the model’s predictive ability relative to a constant hazard model. c Head and neck cancer comorbidity index score of (1 or more) with 0 as reference. d Charlson index score of (1 or more) with 0 as reference. e Alcohol and tobacco related comorbidity index score of (1 or more) with 0 as reference.
Table 3 Adjusted relative risk (RR) dose-response patterns with 95% confidence intervals (95% CI) and trend statistics for three comorbidity indexes, SEER/HCFA, head and neck cancer patients, 1985–1993, n=9386 ATC index RRa
HNCA index 95% CI
RRa
Charlson index 95% CI
RRa
95% CI
Index score 0 1+
1.00 1.49
– 1.32–1.68
1.00 1.53
– 1.42–1.66
1.00 1.50
– 1.43–1.68
Index score 0 1 2+
1.00 1.53 0.76
– 1.35–1.72 0.34–1.69
1.00 1.38 1.61
– 1.20–1.58 1.47–1.76
1.00 1.33 1.83
– 1.21–1.47 1.64–2.05
P-value for trend
<0.0001
<0.0001
<0.0001
a All relative risks are for all-cause mortality and adjusted for age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education at the zip code level, household wealth at the zip code level, histologic grade, and treatment. P-value for trend from the Wald statistic.
respectively. Few subjects had ATC scores of 2+ (Table 4). Adjusted RR estimates were derived for groups of subjects surviving at least 1, 2, 3, 4, and 5 years (Table 5). All three indexes displayed little change in adjusted RR estimates across survival time categories.
4. Discussion This study was conducted to assess the relative prognostic value of three measures of comorbidity: the Charlson, HNCA, and ATC indexes. The Charlson and HNCA indexes had a moderately high Spearman bivariate correlation (0.81 P < 0.001). This finding was not surprising given the similarities in derivation of the Charlson and HNCA indexes. The ATC index, which is limited to a smaller spectrum of comorbidities and does not weight for seriousness, was poorly correlated with the other two indexes. Despite the lack of correlation of the ATC index with the other two indexes, the adjusted RR was similar in magnitude, (ATC RR=1.49, 95%CI 1.32–1.68),
(Charlson RR=1.50, 95% CI 1.43–1.68), (HNCA RR= 1.53, 95%CI 1.42–1.66). Overall chi-square scores were derived from multivariable models, with 17 d.f., that differed only by comorbidity index used. The overall chi-square scores for the Charlson and HNCA indexes were virtually identical followed by the ATC index (2012, 2002, and 1925, respectively). The Charlson and HNCA indexes were also virtually indistinguishable when examined for dose-response patterns. The ATC index did not display a linear trend, possibly because of so few subjects in the 2+ score category (n=12, Table 4), and therefore was not judged to have a clear dose-response pattern. All three indexes displayed consistency in adjusted RR estimates across survival time categories indicating prognostic value for mortality for short- as well as longer-term survivors (Table 5). One previous study has tested the Charlson index in a HNCA population [9]. Singh et al. [9] reported findings from 88 HNCA patients diagnosed at or prior to age 45, drawn from three New York-area hospitals over a 12year period. The outcome was tumor-specific survival,
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B.C. Reid et al. / Oral Oncology 38 (2002) 187–194 Table 4 Distribution of the SEER/HCFA head and neck cancer population 1985–1993 (n=9386) among the comorbidity indexes Scorea
0 1 2+ a
Charlson
HNCA
ATC
%
(n)
%
(n)
%
(n)
88.0 07.1 04.9
(8261) (663) (462)
88.9 03.5 07.6
(8344) (325) (717)
95.8 04.0 0.01
(8995) (379) (12)
Fewer than 2% of persons had scores of three or more using any of the indexes.
Table 5 Adjusted relative risks (RR) and 95% confidence intervals (95% CI) for comorbidity indexes by selected survival time categories, SEER/HCFA, head and neck cancer patients, 1985–1993 Survival time categoriesa
All subjects included (n=9386) Includes only subjects surviving >1 year (n=6705) >2 years (n=4524) >3 years (n=3175) >4 years (n=2386) >5 years (n=1692)
Charlson Index
HNCA Index
ATC Index
RRb
95% CI
RRb
95% CI
RRb
95% CI
1.50
1.43–1.60
1.53
1.42–1.66
1.49
1.32–1.68
1.35 1.41 1.42 1.38 1.35
1.21–1.50 1.22–1.63 1.17–1.71 1.09–1.74 1.01–1.81
1.46 1.46 1.36 1.38 1.28
1.30–1.64 1.25–1.71 1.11–1.67 1.07–1.78 0.92–1.79
1.32 1.57 1.70 1.44 1.43
1.11–1.57 1.26–1.96 1.29–2.22 1.01–2.05 0.92–2.22
a
The same proportional hazards regression was conducted using only those subjects that had already survived for the indicated amount of time. For example, the adjusted relative risk for a Charlson index score of 1 or more compared to 0, was 1.50 if all subjects were analyzed and 1.35 if only those subjects surviving more than 5 years were analyzed. b All relative risks are for all-cause mortality and adjusted for age and date at diagnosis, marital status, race, sex, anatomic site, historic stage, education at the zip code level, household wealth at the zip code level, histologic grade, and treatment.
which has competing causes (non-cancer causes of death); a violation of the assumption of independent censoring underlying the (Kaplan–Meier and Cox regression) survival methods used [20]. The Charlson index was found to be an independent predictor of survival, supporting the findings of the present study despite differences in population source, age distribution, and analytic methods. The use of ICD-9-CM codes to identify comorbid conditions in the derivation of the HNCA index allowed the inclusion of non-disease codes. For example, electrolyte imbalance is not a distinct disease entity and could be the result of a number of medical conditions. Yet electrolyte imbalance was prevalent in the HNCA population; it predicted survival; and satisfied the definition of a comorbid condition, and was therefore included as a comorbid condition. The Charlson, HNCA, and ATC indexes had similar adjusted RR estimates. The Charlson and HNCA indexes were slight improvements upon the ATC index with regard to overall chi-square scores and doseresponse patterns. The three indexes were nonetheless quite comparable in assessing the association of comorbidity and survival in this population. The Charlson index can be used and compared across different populations and studies as it does not require recalculation
for each new application. This advantage, coupled with comparable validity, makes the Charlson index preferable to the others for comorbidity measurement in a HNCA population. Nonetheless, other even simpler measures of comorbidity, including number of hospitalized days, have been reported in one study [21] to provide comparable predictions of mortality in claims-derived databases. Although strengths of our study included its large size and being population-based, it was nonetheless limited by inclusion of only those aged 66 or more at diagnosis Another limitation was the insensitive measurement of comorbidity by use of in-patient records which capture only the more severe cases of comorbid disease. In contrast to the low sensitivity, the specificity of comorbidity measurement was likely very high. The ascertainment of comorbidity required that a person be sufficiently ill to be hospitalized for their comorbid condition in the year prior to their diagnosis with HNCA. As a result, virtually no persons would be classified falsely as having comorbidity — a false positive rate of nearly zero — assuring a very high specificity. It was notable that despite the use of an insensitive comorbidity measurement, all three indexes demonstrated an independent and significant association with survival, supporting the use of this approach.
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The measurement of comorbidity has applications in research and clinical settings. In research it can be used to adjust for group differences in comorbidity to reduce possible confounding of study associations. In the clinical setting, comorbidity can be included in developing a prognosis for individual patients. Additional studies to validate these findings among persons diagnosed with HNCA at ages younger than 66 years and using more sensitive measures of comorbidity are needed. All three indexes studied — Charlson, HNCA, ATC — displayed strong associations with survival. Although the ATC index shows promise, the HNCA and Charlson indexes had similar adjusted RR estimates, dose-response patterns, P-values, and overall chi-square scores, and appear particularly well-suited to measuring comorbidity in this population. The Charlson index enjoys the additional advantage of allowing comparisons across populations and studies and may therefore be preferable to the HNCA and ATC indexes for research purposes. However, given that comorbidity is predictive of survival among persons with HNCA, it would appear from this study that efforts to include comorbidity in prognostic evaluations should take priority over concerns about how to measure comorbidity.
Acknowledgements Thanks to James Tonascia, Joan Warren, Arnie Potosky, and Nicki Schussler for help and comments during the study. B.C. Reid received support from a National Research Scientist Award from the NIDCR (T32 DE-7255), A.J. Alberg received support from a Preventive Oncology Academic Award from the NCI (CA73790), R.G. Rozier received support from a W.R. Kenan award from the University of North Carolina.
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