Applied Health Economics and Health Policy

, Volume 11, Issue 3, pp 275–286 | Cite as

Medicare Fee-for-Service Enrollees with Primary Acute Myeloid Leukemia: An Analysis of Treatment Patterns, Survival, and Healthcare Resource Utilization and Costs

  • Juliana MeyersEmail author
  • Yanni Yu
  • James A. Kaye
  • Keith L. Davis
Original Research Article



Acute myeloid leukemia (AML) is the most common form of acute leukemia affecting adults, with incidence increasing with patient age. Previous studies have found that older AML patients, constituting the majority of the AML population, generally have poor outcomes, high healthcare expenditures, and median survival of <3 months. Because up-to-date information on treatment patterns, survival trends, and costs of care for elderly AML patients are lacking in the literature, we examined Medicare fee-for-service enrollees with primary AML to update these estimates and report on changes in treatment for this population.


The primary objective of this study was to examine real-world data on treatment patterns, survival, and costs in elderly patients with primary AML. Factors associated with receipt of chemotherapy and with mortality also were assessed.


This is a retrospective database analysis using the Surveillance, Epidemiology, and End Results cancer registry and linked Medicare claims. Patients aged 65 years and older, who were newly diagnosed with AML between 1 January 1997 and 31 December 2007 were selected if they had no previous neoplasm or hematological disease. Patients were followed until death or to the end of the observation period (31 December 2007). Study measures included chemotherapy and supportive care (SC) received, survival time, and all-cause healthcare utilization and costs accrued from AML diagnosis until death or observation period end. Regression analyses assessed factors associated with receipt of chemotherapy (logistic) and mortality among chemotherapy and SC users (Cox).


Of the 4,058 patients meeting the inclusion criteria, 43 % received chemotherapy; 57 % received SC only. Among patients receiving chemotherapy, 69.1 % died within 1 year; median survival was 7.0 months. Among patients receiving only SC, 95.0 % died within 1 year; median survival was 1.5 months. The most significant factors associated with receipt of chemotherapy were patient age [odds ratio (OR) = 0.420 among patients 75–84 years and 0.099 among patients 85+ years, compared with patients aged 65–74 years) and Charlson Comorbidity Index (CCI) score (OR = 0.614 for patients with a CCI = 2 or 3 and 0.707 for patients with a CCI >3, compared with patients with a CCI = 0) (all P < 0.001). The most significant factors associated with mortality among patients receiving chemotherapy were patient age [hazard ratio (HR) = 1.321 among patients 75–84 years and 1.832 among patients 85+ years, compared with patients aged 65–74 years] and CCI score (OR = 1.287 for patients with a CCI = 2 or 3 and 1.220 for patients with a CCI >3, compared with patients with a CCI = 0) (all P < 0.01). Mean (standard deviation) all-cause healthcare costs were $96,078 ($109,072); the largest component was inpatient utilization (76.3 %).


Younger patients with fewer comorbidities were more likely to receive chemotherapy and had longer survival. AML is associated with a substantial economic burden, and treatment outcomes appear to be suboptimal, with limited therapy options currently available.


Acute Myeloid Leukemia Hematopoietic Stem Cell Transplantation Charlson Comorbidity Index Healthcare Utilization Acute Myeloid Leukemia Patient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This study used the linked SEER-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the Applied Research Program of the National Cancer Institute; the Office of Research, Development and Information of the Centers for Medicare and Medicaid Services; Information Management Services, Inc.; and the SEER Program’s tumor registries in the creation of the SEER-Medicare database.

Authorship Contributions

JM, YY, JAK, and KLD designed the research, performed the research, analyzed data, and wrote the article. All authors have read and approved the submission of this manuscript. JM is the guarantor for the overall content of the manuscript.

Conflict of Interest Disclosures

This study was supported by research funding from Boehringer Ingelheim Pharmaceuticals, Inc. to JM, JAK, and KLD. YY is an employee of Boehringer Ingelheim Pharmaceuticals, Inc. JM, JAK, and KLD are employees of RTI Health Solutions; RTI Health Solutions received funding from Boehringer Ingelheim Pharmaceuticals, Inc. to perform this research.


  1. 1.
    American Cancer Society. Leukemia—acute myeloid (myelogenous) [online]. Accessed 28 Feb 2012.
  2. 2.
    Jernal A, Thomas A, Murray T, et al. Cancer statistics, 2002. CA Cancer J Clin. 2002;52(1):23–47.CrossRefGoogle Scholar
  3. 3.
    Appelbaum FR, Rowe JM, Radich J, et al. Acute myeloid leukemia. ASH Educ Book. 2001;2001(1):62–86. Scholar
  4. 4.
    Rowley JD, Alimena G, Garson M, et al. A collaborative study of the relationship of the morphological type of acute nonlymphocytic leukemia with patient age and karyotype. Blood. 1982;59(5):1013–22.PubMedGoogle Scholar
  5. 5.
    Grimwade D, Walker H, Oliver F, Wheatley K, Harrison C, Harrison G, Rees J, Hann I, Stevens R, Burnett A, Goldstone A. 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.PubMedGoogle Scholar
  6. 6.
    Howlader N, Noone AM, Krapcho M, Neyman N, Aminou R, Altekruse SF, Kosary CL, Ruhl J, Tatalovich Z, Cho H, Mariotto A, Eisner MP, Lewis DR, Chen HS, Feuer EJ, Cronin KA, editors. SEER cancer statistics review, 1975–2009 (vintage 2009 populations). Bethesda: National Cancer Institute. Accessed 30 Nov 2012 (based on November 2011 SEER data submission, posted to the SEER Web site, 2012).
  7. 7.
    Menzin J, Lang K, Earle CC, Kerney D, et al. The outcomes and costs of acute myeloid leukemia among the elderly. Arch Intern Med. 2002;62(14):1597–603.CrossRefGoogle Scholar
  8. 8.
    Warren JL, Harlan LC, Fahey A, et al. Utility of the SEER-Medicare data to identify chemotherapy use. Med Care. 2002;40(8):IV55–61.Google Scholar
  9. 9.
    Nattinger AB, McAuliffe TL, Schapira MM. Generalizability of the surveillance, epidemiology, and end results registry population: factors relevant to epidemiologic and health care research. J Clin Epidemiol. 1997;50(8):939–45.PubMedCrossRefGoogle Scholar
  10. 10.
    Hershman D, Hall MJ, Wang X, et al. Timing of adjuvant chemotherapy initiation after surgery for stage III colon cancer. Cancer. 2006;107(11):2581–8.PubMedCrossRefGoogle Scholar
  11. 11.
    Sundararajan V, Hershman D, Grann VR, et al. Variations in the use of chemotherapy for elderly patients with advanced ovarian cancer: a population-based study. J Clin Oncol. 2002;20(1):173–8.PubMedCrossRefGoogle Scholar
  12. 12.
    Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic co-morbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.PubMedCrossRefGoogle Scholar
  13. 13.
    Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613–9.PubMedCrossRefGoogle Scholar
  14. 14.
    National Cancer Institute. Procedure codes for SEER-Medicare analyses. 2010. Accessed 14 Feb 2013.
  15. 15.
    Roboz GJ. Novel approaches to the treatment of acute myeloid leukemia. ASH Educ Book. 2011;2011(1):43–50.Google Scholar
  16. 16.
    National Comprehensive Cancer Network. Clinical practice guidelines in oncology. Acute myeloid leukemia V.3 (online). 2010. Accessed 28 Feb 2012.
  17. 17.
    Piana R. Geriatric oncology, a much needed discipline for future cancer care. ASCO Post. 2011;2(17).,-a-much-needed-discipline-for-future-cancer-care/. Accessed 28 Feb 2012.

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Juliana Meyers
    • 1
    Email author
  • Yanni Yu
    • 2
  • James A. Kaye
    • 1
  • Keith L. Davis
    • 1
  1. 1.RTI Health SolutionsResearch Triangle ParkUSA
  2. 2.Boehringer Ingelheim Pharmaceuticals, Inc.RidgefieldUSA

Personalised recommendations