- Email: [email protected]
Outcome of Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndrome According to Health Insurance Status
Original Study
Outcome of Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndrome According to Health Insurance Status Ali Al-Ameri,1 Ankit Anand,1 Mohamed Abdelfatah,1 Zeyad Kanaan,1 Tracy Hammonds,1 Nairmeen Haller,1 Mohamad Cherry2 Abstract AML and high risk MDS patient outcomes in community hospital setting may vary based on health care insurance status. Ninety four patients were reviewed. Likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P [ .018) times the likelihood in patients who had Medicare with supplemental insurance. Age and risk of mortality were found to be significant predictors of survival whereas insurance did not contribute significantly to the model. Overall survival in the study was inferior as compared to national average. Early referral to a specialized center may improve outcomes. Background: Age, cytogenetic status, and molecular features are the most important prognostic factors in acute myeloid leukemia (AML). This study aimed to analyze the outcomes of patients with AML or high-risk myelodysplastic syndrome (MDS) according to insurance status. Patients and Methods: A retrospective chart review was performed, covering all patients with AML and high-risk MDS evaluated and treated at Akron General Medical Center between 2002 and 2012. A Cox regression model was analyzed to account for survival over time, adjusted for insurance type, while controlling for patient age at diagnosis and patient risk of mortality. Results: A total of 130 adult patients (age 18 years) were identified. Insurance information was available for 97 patients enrolled in the study; 3 were excluded because of self-pay status. Cox regression analysis with insurance type as the predictor found that overall survival declines over time and that the rate of decline may be influenced by insurance type (c2(2) ¼ 6.4; P ¼ .044). The likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P ¼ .018) times the likelihood in patients who had Medicare with supplemental insurance. To explain the difference, variables of age, gender, and risk of mortality were added to the model. Age and risk of mortality were found to be significant predictors of survival. The addition of insurance type to the model did not significantly contribute (c2(3) ¼ 3.83; P ¼ .147). Conclusion: No significant difference in overall survival was observed when patients with AML or high-risk MDS were analyzed according to their health insurance status. The overall survival was low in this study compared with the national average. Early referral to a specialized center or possible clinical trial enrollment may be a good alternative to improve outcome. Clinical Lymphoma, Myeloma & Leukemia, Vol. 14, No. 6, 509-13 ª 2014 Elsevier Inc. All rights reserved. Keywords: AML/MDS, Cytogenetic data, Insurance, Outcome, Survival
Introduction Acute myeloid leukemia (AML) is a heterogeneous group of aggressive neoplasms affecting the myeloid lineage of stem cells. It 1
Internal Medicine, Akron General Medical Center, Akron, OH University of Oklahoma Health Sciences Center, Oklahoma City, OK
2
Submitted: Jan 15, 2014; Revised: Mar 17, 2014; Accepted: Mar 17, 2014; Epub: Jun 12, 2014 Address for correspondence: Ankit Anand, MD, Akron General Medical Center, 1 Akron General Ave, Akron, OH 44307 E-mail contact: [email protected], [email protected]
2152-2650/$ - see frontmatter ª 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clml.2014.03.003
usually originates in the bone marrow with subsequent manifestation in the peripheral blood but can affect any other organ. AML is the most common type of adult acute leukemia, with a median age of 67 years at diagnosis. As the leading cause of death from leukemia in adults, AML in the setting of community hospitals is one of the most challenging diseases to manage, involving prolonged hospitalizations, high readmission rates, severe infectious complications, and highly trained nurses and house staff.1 The 2008 revised World Health Organization (WHO) classification of AML requires morphology, immunophenotyping, cytogenetic data, and molecular studies for proper classification and
Clinical Lymphoma, Myeloma & Leukemia December 2014
- 509
Outcome of AML and MDS Versus Insurance Status Table 1 Demographic Data of the Study Group Characteristic
Medicaid or Medicare Without Supplemental Insurance (n [ 32)
Medicare With Supplemental Insurance (n [ 38)
Private Insurance (n [ 24)
42.0% 80.5 (71.5-89.5) 61.0% 86.8% 16.0 (0.0-73.0)
47.0% 74.5 (59.5-89.5) 47.0% 71.9% 40.0 (0.0-203.5)
67.0% 61.0 (33.0-89.0) 25.0% 62.5% 40.5 (0.0-163.0)
% Female Age (y) at Diagnosis, Median (IQR) % at High Risk for Mortality % Mortality at 200 wk Survival (wk), Median (IQR) Abbreviation: IQR ¼ interquartile range.
review board approval, a search identified 130 patients who had AML and high-risk MDS. Of these, 98 patients could be classified according to WHO criteria; 32 patients were excluded owing to incomplete data (mostly a lack of cytogenetic data). The majority of patients with AML were treated with 7 þ 3 induction protocols. There were only 15 patients with the diagnosis of high-risk MDS according to the International Prognostic Scoring System criteria. These patients were treated with 7 þ 3 or hypomethylating agents such as azacitidine or decitabine. Patient demographic data, diagnosis types/subtypes, treatment, and cytogenetic data were recorded. Patients were also classified according to the presence of health insurance coverage at the time of diagnosis. Continuous variables in comparison groups were described using means, SDs, medians, and interquartile ranges (IQRs). Categorical variables in comparison groups were described using percentages. A Cox regression model was analyzed to account for survival over time, adjusted for insurance type, while controlling for patient age at diagnosis and patient risk of mortality.
prognostication. Age and cytogenetic data are considered the most important prognostic factors.2-4 Patients with AML usually undergo induction chemotherapy comprising cytarabine and an anthracycline (such as daunorubicin or idarubicin). Postremission therapy either with high-dose cytarabine or stem cell transplant is needed to achieve long-term survival. Patients are mainly divided into 3 risk groups according to their cytogenetic data: patients with inversion of chromosome 16 [inv(16)] or translocation between the long arms of chromosomes 8 and 21 [t(8:21)(q22;q22)] are considered as having favorable risk; patients with normal cytogenetic data are considered as having intermediate risk; and those with monosomies or complex cytogenetic data are considered as having high risk. Molecular testing further subdivides the intermediate-risk group into intermediate-1 (lesser risk) and intermediate-2 (greater risk). Among adverse prognostic markers, FLT3 (fms-related tyrosine kinase 3) internal tandem duplication (FLT3-ITD) and FLT3 tyrosine kinase domain (FLT3-TKD) mutations are particularly unfavorable, and most patients with FLT3 mutations are destined for bone marrow transplant. By contrast, mutations in CEBPA (CCAAT/enhancer binding protein (C/EBP), alpha) and NPM1 (nucleophosmin [nucleolar phosphoprotein B23, numatrin]) (and concomitant wild type FLT3) have been associated with favorable prognosis.5-11,12 Patients with AML or high-risk myelodysplastic syndrome (MDS) who have different health insurances may have different socioeconomic status, which can potentially interfere with the ability to receive appropriate treatment (such as stem cell transplant) when indicated. Literature addressing this factor in the community hospital setting is largely lacking. This report presents the results of a retrospective analysis addressing this important question.13-16
Results Of 130 patients who had been treated, insurance information was available for 97; 3 of the 97 were excluded because of self-pay status. Of those enrolled in the study, 34.0% (32 of 94) had Medicaid or Medicare without supplemental insurance; 40.4% (38 of 94) had Medicare with supplemental insurance; and 25.5% (24 of 94) had private insurance. Insured patients were found to be at low risk for early mortality based on cytogenetic testing (53.2% vs. 46.9%). The average age of the sample population was 69.7 15.1 years (median, 75.0 years), and the average length of survival after diagnosis was 75.5 105.1 weeks (median, 26.0 weeks). There were equal numbers of male and female patients enrolled. The median age of patients who had Medicare with supplemental insurance was 80.5 years (IQR, 71.5-89.5 years), versus 74.5 years (IQR, 59.5-89.5 years) for patients with Medicaid or Medicare
Patients and Methods The authors conducted a retrospective chart review of patients with AML or high-risk MDS treated at Akron General Medical Center, Akron, Ohio, during 2002-2010. After institutional
Table 2 Postdiagnosis Analysis of Survival Based on Type of Insurance Exp(b)
95% CI
P
Step 1: Adjusted by Age at Diagnosis
1.019
1.006-1.032
.005
Step 2: Adjusted by Age at Diagnosis and Risk of Mortality
1.018
1.005-1.031
.008
Medicaid or Medicare Without Supplemental Insurance
.616
.333-1.138
.122
Medicare With Supplemental Insurance
.930
.491-1.762
.823
Cox Regression Model
Block 2: Private Insurance
510
-
Clinical Lymphoma, Myeloma & Leukemia December 2014
.158
Ali Al-Ameri et al Figure 1 Survival Function for Insured Patients Diagnosed With Acute Myelogenous Leukemia or Myelodysplastic Syndrome
without supplemental insurance and 61.0 years (IQR, 33.0-89.0 years) for patients with private insurance. Patients who had Medicare with supplemental insurance were more likely to be at high risk
for mortality (61%) and were more likely to have died at or before 200 weeks (86.8%). The median number of weeks to mortality from diagnosis was 16.0 (IQR, 0-73 weeks) in patients that
Figure 2 Survival Function Based on Insurance Type After Controlling for Age and Risk of Mortality
Clinical Lymphoma, Myeloma & Leukemia December 2014
- 511
Outcome of AML and MDS Versus Insurance Status had Medicare with supplemental insurance, versus 40.0 weeks (IQR, 0-203.5 weeks) and 40.5 weeks (IQR, 0-163.0 weeks) in patients with Medicaid or Medicare without supplemental insurance and those with private insurance, respectively (Table 1). Cox regression analysis with insurance type as the predictor found that overall survival declined over time and that the rate of decline may have been influenced by insurance type (c2(2) ¼ 6.4; P ¼ .044). The likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P ¼ .018) times the likelihood of survival in patients with Medicare with supplemental insurance, indicating that patients who have Medicare without supplemental insurance have a higher rate of mortality. To explain the difference, variables of age, gender, and risk of mortality were added to the model in a stepwise fashion. Age and risk of mortality were found to be significant predictors of survival. Every 1-year increase in age is associated with a 1.8% increase in risk of death (95% CI, 1.006-1.032; P ¼ .005). Additionally, mortality is 1.71 times less likely in patients with low risk than in those with high risk (Exp(b) ¼ .585; 95% CI, .382-.896; P ¼ .014). The addition of insurance type to the model did not significantly contribute (c2(3) ¼ 3.83; P ¼ .147), thus indicating that age and risk of mortality explained the initial influence of insurance type on survival (Table 2, Figures 1 and 2).
Discussion It is estimated that more than 50 million people in the United States do not have any kind of medical coverage. There are emerging concerns regarding their outcomes and whether they receive optimal management. A large retrospective study conducted using the National Cancer Institute data mainly in breast and colorectal cancer concluded that patients who have no health insurance coverage tend to present late with advanced cancer and consequently may have poorer outcomes.17 The present study, to the best of the authors’ knowledge, is the first study in patients with AML treated in community hospitals that tries to address this issue. Interestingly, Halpern et al18 found that patients with Medicaid insurance had health outcomes similar to those of patients without insurance. The present study aimed to investigate whether patients on Medicaid or Medicare have the same outcomes as those with private insurance when treated in the community hospital setting.19,20 Compared with national data, the outcomes of the patients in this study are inferior. This may reflect the fact that the outcomes of patients treated in community hospitals are indeed inferior to the outcomes of those treated in major academic centers, and it stresses the importance of referral of these patients to more experienced centers for optimal management. However, the present results clearly indicate that health insurance status (mainly private vs. Medicare/Medicaid), contrary to the authors’ previous assumption, is not a major determinant of the outcome in patients with AML or high-risk MDS.18,21,22 The major limitation of this study is the identification of only 3 uninsured patients, which makes this group of patients underrepresented, and consequently this group was not included and compared with other health insurance statuses.
512
-
Clinical Lymphoma, Myeloma & Leukemia December 2014
Conclusion This study highlights the complexity of AML management in the community hospital setting and the fact that the overall outcomes may be inferior compared with the outcomes seen in patients treated in major academic centers. A strategy of early referral to high-volume centers may ultimately improve the outcomes of these patients, but a more reasonable approach may rely on better local management by adopting more aggressive induction treatment and better selection for stem cell transplant. The fact that patients with Medicaid/Medicare have similar outcomes compared with those having private insurance is important, especially with the push for wide adoption of the Affordable Care Act by the government. A larger-scale study should be conducted prospectively for better assessment of the outcomes of patients with AML according to health insurance status.
Clinical Practice Points Outcomes are dependent on access to health care. Patients with medicare/medicaid have similar outcomes as
compared to those with private insurance. Supports affordable care act and improvement in outcomes with
wider availability of healthcare resources.
Disclosure The authors have stated that they have no conflicts of interest.
References 1. Estey EH. Acute myeloid leukemia: 2012 update on diagnosis, risk stratification, and management. Am J Hematol 2012; 87:89-99. 2. Smith SM, Le Beau MM, Huo D, et al. Clinical-cytogenetic associations in 306 patients with therapy-related myelodysplasia and myeloid leukemia: the University of Chicago series. Blood 2003; 102:43-52. 3. Appelbaum FR, Gundacker H, Head DR, et al. Age and acute myeloid leukemia. Blood 2006; 107:3481-5. 4. Mailankody S, Pfeiffer RM, Kristinsson SY, et al. Risk of acute myeloid leukemia and myelodysplastic syndromes after multiple myeloma and its precursor disease (MGUS). Blood 2011; 118:4086-92. 5. Walter R, Othus M, Borthakur G, et al. Quantitative effect of age in predicting empirically-defined treatment-related mortality and resistance in newly diagnosed AML: case against age alone as primary determinant of treatment assignment [ASH abstract 2191]. Blood 2010; 116:21. 6. Vardiman JW, Thiele J, Arger DA, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood 2009:937-51. 7. Bennett JM, Catovsky D, Daniel MT, et al. Proposals for the classification of the acute leukaemias. French-American-British (FAB) co-operative group. Br J Haematol 1976; 33:451-8. 8. Estey E, Thall P, Beran M, et al. Effect of diagnosis (refractory anemia with excess blasts, refractory anemia with excess blasts in transformation, or acute myeloid leukemia [AML]) on outcome of AML-type chemotherapy. Blood 1997; 90:2969-77. 9. Giles FJ, Shen Y, Kantarjian HM, et al. Leukapheresis reduces early mortality in patients with acute myeloid leukemia with high white cell counts but does not improve long-term survival. Leuk Lymphoma 2001; 42:67-73. 10. Burnett AK, Milligan D, Prentice AG, et al. A comparison of low-dose cytarabine and hydroxyurea with or without all-trans retinoic acid for acute myeloid leukemia and high-risk myelodysplastic syndrome in patients not considered fit for intensive treatment. Cancer 2007; 109:1114-24. 11. Sekeres MA, Elson P, Kalaycio ME, et al. Time from diagnosis to treatment initiation predicts survival in younger, but not older, acute myeloid leukemia patients. Blood 2009; 113:28-36. 12. Grimwade D, Walker H, Oliver F, et al. The importance of diagnostic cytogenetics on outcome in AML: analysis of 1,612 patients entered into the MRC AML 10 trial. Blood 1998; 92:2322-33. 13. Marcucci G, Haferlach T, Dohner H. Molecular genetics of adult acute myeloid leukemia: prognostic and therapeutic implications. J Clin Oncol 2011; 29:475-86. 14. Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. N Engl J Med 2008; 358: 1909-18.
Ali Al-Ameri et al 15. Gale RE, Green C, Allen C, et al. The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia. Blood 2008; 111: 2776-84. 16. Paschka P, Marcucci G, Ruppert AS, et al. Adverse prognostic significance of KIT mutations in adult acute myeloid leukemia with inv(16) and t(8;21): a Cancer and Leukemia Group B Study. J Clin Oncol 2006; 24:3904-11. 17. Farkas DT, Greenbaum A, Singhal V, Cosgrove JM. Effect of insurance status on the stage of breast and colorectal cancers in a safety-net hospital. J Oncol Pract 2012; 8(3 suppl):16s-21s. http://dx.doi.org/10.1200/JOP.2012.000542. 18. Halpern MT, Ward EM, Pavluck AL, et al. Association of insurance status and ethnicity with cancer stage at diagnosis for 12 cancer sites: a retrospective analysis. Lancet Oncol 2008; 9:222-31.
19. Bullinger L, Ehrich M, Dohner K, et al. Quantitative DNA methylation predicts survival in adult acute myeloid leukemia. Blood 2010; 115:636-42. 20. Dohner H, Estey EH, Amadori S, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 2010; 115: 453-74. 21. Wheatley K, Brookes CL, Howman AJ, et al. Prognostic factor analysis of the survival of elderly patients with AML in the MRC AML11 and LRF AML14 trials. Br J Haematol 2009; 145:598-605. 22. Krug U, Rollig C, Koschmieder A, et al. Complete remission and early death after intensive chemotherapy in patients aged 60 years or older with acute myeloid leukaemia: a web-based application for prediction of outcomes. Lancet 2010; 376: 2000-8.
Clinical Lymphoma, Myeloma & Leukemia December 2014
- 513
Outcome of Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndrome According to Health Insurance Status Ali Al-Ameri,1 Ankit Anand,1 Mohamed Abdelfatah,1 Zeyad Kanaan,1 Tracy Hammonds,1 Nairmeen Haller,1 Mohamad Cherry2 Abstract AML and high risk MDS patient outcomes in community hospital setting may vary based on health care insurance status. Ninety four patients were reviewed. Likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P [ .018) times the likelihood in patients who had Medicare with supplemental insurance. Age and risk of mortality were found to be significant predictors of survival whereas insurance did not contribute significantly to the model. Overall survival in the study was inferior as compared to national average. Early referral to a specialized center may improve outcomes. Background: Age, cytogenetic status, and molecular features are the most important prognostic factors in acute myeloid leukemia (AML). This study aimed to analyze the outcomes of patients with AML or high-risk myelodysplastic syndrome (MDS) according to insurance status. Patients and Methods: A retrospective chart review was performed, covering all patients with AML and high-risk MDS evaluated and treated at Akron General Medical Center between 2002 and 2012. A Cox regression model was analyzed to account for survival over time, adjusted for insurance type, while controlling for patient age at diagnosis and patient risk of mortality. Results: A total of 130 adult patients (age 18 years) were identified. Insurance information was available for 97 patients enrolled in the study; 3 were excluded because of self-pay status. Cox regression analysis with insurance type as the predictor found that overall survival declines over time and that the rate of decline may be influenced by insurance type (c2(2) ¼ 6.4; P ¼ .044). The likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P ¼ .018) times the likelihood in patients who had Medicare with supplemental insurance. To explain the difference, variables of age, gender, and risk of mortality were added to the model. Age and risk of mortality were found to be significant predictors of survival. The addition of insurance type to the model did not significantly contribute (c2(3) ¼ 3.83; P ¼ .147). Conclusion: No significant difference in overall survival was observed when patients with AML or high-risk MDS were analyzed according to their health insurance status. The overall survival was low in this study compared with the national average. Early referral to a specialized center or possible clinical trial enrollment may be a good alternative to improve outcome. Clinical Lymphoma, Myeloma & Leukemia, Vol. 14, No. 6, 509-13 ª 2014 Elsevier Inc. All rights reserved. Keywords: AML/MDS, Cytogenetic data, Insurance, Outcome, Survival
Introduction Acute myeloid leukemia (AML) is a heterogeneous group of aggressive neoplasms affecting the myeloid lineage of stem cells. It 1
Internal Medicine, Akron General Medical Center, Akron, OH University of Oklahoma Health Sciences Center, Oklahoma City, OK
2
Submitted: Jan 15, 2014; Revised: Mar 17, 2014; Accepted: Mar 17, 2014; Epub: Jun 12, 2014 Address for correspondence: Ankit Anand, MD, Akron General Medical Center, 1 Akron General Ave, Akron, OH 44307 E-mail contact: [email protected], [email protected]
2152-2650/$ - see frontmatter ª 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clml.2014.03.003
usually originates in the bone marrow with subsequent manifestation in the peripheral blood but can affect any other organ. AML is the most common type of adult acute leukemia, with a median age of 67 years at diagnosis. As the leading cause of death from leukemia in adults, AML in the setting of community hospitals is one of the most challenging diseases to manage, involving prolonged hospitalizations, high readmission rates, severe infectious complications, and highly trained nurses and house staff.1 The 2008 revised World Health Organization (WHO) classification of AML requires morphology, immunophenotyping, cytogenetic data, and molecular studies for proper classification and
Clinical Lymphoma, Myeloma & Leukemia December 2014
- 509
Outcome of AML and MDS Versus Insurance Status Table 1 Demographic Data of the Study Group Characteristic
Medicaid or Medicare Without Supplemental Insurance (n [ 32)
Medicare With Supplemental Insurance (n [ 38)
Private Insurance (n [ 24)
42.0% 80.5 (71.5-89.5) 61.0% 86.8% 16.0 (0.0-73.0)
47.0% 74.5 (59.5-89.5) 47.0% 71.9% 40.0 (0.0-203.5)
67.0% 61.0 (33.0-89.0) 25.0% 62.5% 40.5 (0.0-163.0)
% Female Age (y) at Diagnosis, Median (IQR) % at High Risk for Mortality % Mortality at 200 wk Survival (wk), Median (IQR) Abbreviation: IQR ¼ interquartile range.
review board approval, a search identified 130 patients who had AML and high-risk MDS. Of these, 98 patients could be classified according to WHO criteria; 32 patients were excluded owing to incomplete data (mostly a lack of cytogenetic data). The majority of patients with AML were treated with 7 þ 3 induction protocols. There were only 15 patients with the diagnosis of high-risk MDS according to the International Prognostic Scoring System criteria. These patients were treated with 7 þ 3 or hypomethylating agents such as azacitidine or decitabine. Patient demographic data, diagnosis types/subtypes, treatment, and cytogenetic data were recorded. Patients were also classified according to the presence of health insurance coverage at the time of diagnosis. Continuous variables in comparison groups were described using means, SDs, medians, and interquartile ranges (IQRs). Categorical variables in comparison groups were described using percentages. A Cox regression model was analyzed to account for survival over time, adjusted for insurance type, while controlling for patient age at diagnosis and patient risk of mortality.
prognostication. Age and cytogenetic data are considered the most important prognostic factors.2-4 Patients with AML usually undergo induction chemotherapy comprising cytarabine and an anthracycline (such as daunorubicin or idarubicin). Postremission therapy either with high-dose cytarabine or stem cell transplant is needed to achieve long-term survival. Patients are mainly divided into 3 risk groups according to their cytogenetic data: patients with inversion of chromosome 16 [inv(16)] or translocation between the long arms of chromosomes 8 and 21 [t(8:21)(q22;q22)] are considered as having favorable risk; patients with normal cytogenetic data are considered as having intermediate risk; and those with monosomies or complex cytogenetic data are considered as having high risk. Molecular testing further subdivides the intermediate-risk group into intermediate-1 (lesser risk) and intermediate-2 (greater risk). Among adverse prognostic markers, FLT3 (fms-related tyrosine kinase 3) internal tandem duplication (FLT3-ITD) and FLT3 tyrosine kinase domain (FLT3-TKD) mutations are particularly unfavorable, and most patients with FLT3 mutations are destined for bone marrow transplant. By contrast, mutations in CEBPA (CCAAT/enhancer binding protein (C/EBP), alpha) and NPM1 (nucleophosmin [nucleolar phosphoprotein B23, numatrin]) (and concomitant wild type FLT3) have been associated with favorable prognosis.5-11,12 Patients with AML or high-risk myelodysplastic syndrome (MDS) who have different health insurances may have different socioeconomic status, which can potentially interfere with the ability to receive appropriate treatment (such as stem cell transplant) when indicated. Literature addressing this factor in the community hospital setting is largely lacking. This report presents the results of a retrospective analysis addressing this important question.13-16
Results Of 130 patients who had been treated, insurance information was available for 97; 3 of the 97 were excluded because of self-pay status. Of those enrolled in the study, 34.0% (32 of 94) had Medicaid or Medicare without supplemental insurance; 40.4% (38 of 94) had Medicare with supplemental insurance; and 25.5% (24 of 94) had private insurance. Insured patients were found to be at low risk for early mortality based on cytogenetic testing (53.2% vs. 46.9%). The average age of the sample population was 69.7 15.1 years (median, 75.0 years), and the average length of survival after diagnosis was 75.5 105.1 weeks (median, 26.0 weeks). There were equal numbers of male and female patients enrolled. The median age of patients who had Medicare with supplemental insurance was 80.5 years (IQR, 71.5-89.5 years), versus 74.5 years (IQR, 59.5-89.5 years) for patients with Medicaid or Medicare
Patients and Methods The authors conducted a retrospective chart review of patients with AML or high-risk MDS treated at Akron General Medical Center, Akron, Ohio, during 2002-2010. After institutional
Table 2 Postdiagnosis Analysis of Survival Based on Type of Insurance Exp(b)
95% CI
P
Step 1: Adjusted by Age at Diagnosis
1.019
1.006-1.032
.005
Step 2: Adjusted by Age at Diagnosis and Risk of Mortality
1.018
1.005-1.031
.008
Medicaid or Medicare Without Supplemental Insurance
.616
.333-1.138
.122
Medicare With Supplemental Insurance
.930
.491-1.762
.823
Cox Regression Model
Block 2: Private Insurance
510
-
Clinical Lymphoma, Myeloma & Leukemia December 2014
.158
Ali Al-Ameri et al Figure 1 Survival Function for Insured Patients Diagnosed With Acute Myelogenous Leukemia or Myelodysplastic Syndrome
without supplemental insurance and 61.0 years (IQR, 33.0-89.0 years) for patients with private insurance. Patients who had Medicare with supplemental insurance were more likely to be at high risk
for mortality (61%) and were more likely to have died at or before 200 weeks (86.8%). The median number of weeks to mortality from diagnosis was 16.0 (IQR, 0-73 weeks) in patients that
Figure 2 Survival Function Based on Insurance Type After Controlling for Age and Risk of Mortality
Clinical Lymphoma, Myeloma & Leukemia December 2014
- 511
Outcome of AML and MDS Versus Insurance Status had Medicare with supplemental insurance, versus 40.0 weeks (IQR, 0-203.5 weeks) and 40.5 weeks (IQR, 0-163.0 weeks) in patients with Medicaid or Medicare without supplemental insurance and those with private insurance, respectively (Table 1). Cox regression analysis with insurance type as the predictor found that overall survival declined over time and that the rate of decline may have been influenced by insurance type (c2(2) ¼ 6.4; P ¼ .044). The likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P ¼ .018) times the likelihood of survival in patients with Medicare with supplemental insurance, indicating that patients who have Medicare without supplemental insurance have a higher rate of mortality. To explain the difference, variables of age, gender, and risk of mortality were added to the model in a stepwise fashion. Age and risk of mortality were found to be significant predictors of survival. Every 1-year increase in age is associated with a 1.8% increase in risk of death (95% CI, 1.006-1.032; P ¼ .005). Additionally, mortality is 1.71 times less likely in patients with low risk than in those with high risk (Exp(b) ¼ .585; 95% CI, .382-.896; P ¼ .014). The addition of insurance type to the model did not significantly contribute (c2(3) ¼ 3.83; P ¼ .147), thus indicating that age and risk of mortality explained the initial influence of insurance type on survival (Table 2, Figures 1 and 2).
Discussion It is estimated that more than 50 million people in the United States do not have any kind of medical coverage. There are emerging concerns regarding their outcomes and whether they receive optimal management. A large retrospective study conducted using the National Cancer Institute data mainly in breast and colorectal cancer concluded that patients who have no health insurance coverage tend to present late with advanced cancer and consequently may have poorer outcomes.17 The present study, to the best of the authors’ knowledge, is the first study in patients with AML treated in community hospitals that tries to address this issue. Interestingly, Halpern et al18 found that patients with Medicaid insurance had health outcomes similar to those of patients without insurance. The present study aimed to investigate whether patients on Medicaid or Medicare have the same outcomes as those with private insurance when treated in the community hospital setting.19,20 Compared with national data, the outcomes of the patients in this study are inferior. This may reflect the fact that the outcomes of patients treated in community hospitals are indeed inferior to the outcomes of those treated in major academic centers, and it stresses the importance of referral of these patients to more experienced centers for optimal management. However, the present results clearly indicate that health insurance status (mainly private vs. Medicare/Medicaid), contrary to the authors’ previous assumption, is not a major determinant of the outcome in patients with AML or high-risk MDS.18,21,22 The major limitation of this study is the identification of only 3 uninsured patients, which makes this group of patients underrepresented, and consequently this group was not included and compared with other health insurance statuses.
512
-
Clinical Lymphoma, Myeloma & Leukemia December 2014
Conclusion This study highlights the complexity of AML management in the community hospital setting and the fact that the overall outcomes may be inferior compared with the outcomes seen in patients treated in major academic centers. A strategy of early referral to high-volume centers may ultimately improve the outcomes of these patients, but a more reasonable approach may rely on better local management by adopting more aggressive induction treatment and better selection for stem cell transplant. The fact that patients with Medicaid/Medicare have similar outcomes compared with those having private insurance is important, especially with the push for wide adoption of the Affordable Care Act by the government. A larger-scale study should be conducted prospectively for better assessment of the outcomes of patients with AML according to health insurance status.
Clinical Practice Points Outcomes are dependent on access to health care. Patients with medicare/medicaid have similar outcomes as
compared to those with private insurance. Supports affordable care act and improvement in outcomes with
wider availability of healthcare resources.
Disclosure The authors have stated that they have no conflicts of interest.
References 1. Estey EH. Acute myeloid leukemia: 2012 update on diagnosis, risk stratification, and management. Am J Hematol 2012; 87:89-99. 2. Smith SM, Le Beau MM, Huo D, et al. Clinical-cytogenetic associations in 306 patients with therapy-related myelodysplasia and myeloid leukemia: the University of Chicago series. Blood 2003; 102:43-52. 3. Appelbaum FR, Gundacker H, Head DR, et al. Age and acute myeloid leukemia. Blood 2006; 107:3481-5. 4. Mailankody S, Pfeiffer RM, Kristinsson SY, et al. Risk of acute myeloid leukemia and myelodysplastic syndromes after multiple myeloma and its precursor disease (MGUS). Blood 2011; 118:4086-92. 5. Walter R, Othus M, Borthakur G, et al. Quantitative effect of age in predicting empirically-defined treatment-related mortality and resistance in newly diagnosed AML: case against age alone as primary determinant of treatment assignment [ASH abstract 2191]. Blood 2010; 116:21. 6. Vardiman JW, Thiele J, Arger DA, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood 2009:937-51. 7. Bennett JM, Catovsky D, Daniel MT, et al. Proposals for the classification of the acute leukaemias. French-American-British (FAB) co-operative group. Br J Haematol 1976; 33:451-8. 8. Estey E, Thall P, Beran M, et al. Effect of diagnosis (refractory anemia with excess blasts, refractory anemia with excess blasts in transformation, or acute myeloid leukemia [AML]) on outcome of AML-type chemotherapy. Blood 1997; 90:2969-77. 9. Giles FJ, Shen Y, Kantarjian HM, et al. Leukapheresis reduces early mortality in patients with acute myeloid leukemia with high white cell counts but does not improve long-term survival. Leuk Lymphoma 2001; 42:67-73. 10. Burnett AK, Milligan D, Prentice AG, et al. A comparison of low-dose cytarabine and hydroxyurea with or without all-trans retinoic acid for acute myeloid leukemia and high-risk myelodysplastic syndrome in patients not considered fit for intensive treatment. Cancer 2007; 109:1114-24. 11. Sekeres MA, Elson P, Kalaycio ME, et al. Time from diagnosis to treatment initiation predicts survival in younger, but not older, acute myeloid leukemia patients. Blood 2009; 113:28-36. 12. Grimwade D, Walker H, Oliver F, et al. The importance of diagnostic cytogenetics on outcome in AML: analysis of 1,612 patients entered into the MRC AML 10 trial. Blood 1998; 92:2322-33. 13. Marcucci G, Haferlach T, Dohner H. Molecular genetics of adult acute myeloid leukemia: prognostic and therapeutic implications. J Clin Oncol 2011; 29:475-86. 14. Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. N Engl J Med 2008; 358: 1909-18.
Ali Al-Ameri et al 15. Gale RE, Green C, Allen C, et al. The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia. Blood 2008; 111: 2776-84. 16. Paschka P, Marcucci G, Ruppert AS, et al. Adverse prognostic significance of KIT mutations in adult acute myeloid leukemia with inv(16) and t(8;21): a Cancer and Leukemia Group B Study. J Clin Oncol 2006; 24:3904-11. 17. Farkas DT, Greenbaum A, Singhal V, Cosgrove JM. Effect of insurance status on the stage of breast and colorectal cancers in a safety-net hospital. J Oncol Pract 2012; 8(3 suppl):16s-21s. http://dx.doi.org/10.1200/JOP.2012.000542. 18. Halpern MT, Ward EM, Pavluck AL, et al. Association of insurance status and ethnicity with cancer stage at diagnosis for 12 cancer sites: a retrospective analysis. Lancet Oncol 2008; 9:222-31.
19. Bullinger L, Ehrich M, Dohner K, et al. Quantitative DNA methylation predicts survival in adult acute myeloid leukemia. Blood 2010; 115:636-42. 20. Dohner H, Estey EH, Amadori S, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 2010; 115: 453-74. 21. Wheatley K, Brookes CL, Howman AJ, et al. Prognostic factor analysis of the survival of elderly patients with AML in the MRC AML11 and LRF AML14 trials. Br J Haematol 2009; 145:598-605. 22. Krug U, Rollig C, Koschmieder A, et al. Complete remission and early death after intensive chemotherapy in patients aged 60 years or older with acute myeloid leukaemia: a web-based application for prediction of outcomes. Lancet 2010; 376: 2000-8.
Clinical Lymphoma, Myeloma & Leukemia December 2014
- 513