Hyunsoon Cho, PhD; Carrie N. Klabunde, PhD; K. Robin Yabroff, PhD, MBA; Zhuoqiao Wang, MS; Angela Meekins, BS; Iris Lansdorp-Vogelaar, PhD; Angela B. Mariotto, PhD
Disclaimer: The content is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health, the National Cancer Institute, or the Centers for Disease Control and Prevention.
Grant Support: This study received no external funding. Dr. Lansdorp-Vogelaar was supported by the National Cancer Institute at the National Institutes of Health and the Centers for Disease Control (grants U01-CA-152959 and U01 CA152926.
Potential Conflicts of Interest: None disclosed. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-2996.
Reproducible Research Statement: Study protocol: Detailed in the Methods section and Supplement. Statistical code: Available on request. Data set: Restricted. SEER–Medicare data are available to investigators for research purposes through request (see http://appliedresearch.cancer.gov/seermedicare/obtain/).
Requests for Single Reprints: Hyunsoon Cho, PhD, Data Modeling Branch, Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD 20892; e-mail, firstname.lastname@example.org or email@example.com.
Current Author Addresses: Drs. Cho and Mariotto: Data Modeling Branch, Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD 20892.
Drs. Klabunde and Yabroff: Health Services and Economics Branch, Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD 20892.
Mr. Wang and Ms. Meekins: Information Management Services, 3901 Calverton Boulevard, Suite 200, Calverton, MD 20705.
Dr. Lansdorp-Vogelaar: Department of Public Health, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA Rotterdam, the Netherlands.
Author Contributions: Conception and design: H. Cho, C.N. Klabunde, K.R. Yabroff, A.B. Mariotto.
Analysis and interpretation of the data: H. Cho, C.N. Klabunde, Z. Wang, I. Lansdorp-Vogelaar, A.B. Mariotto.
Drafting of the article: H. Cho, K.R. Yabroff, A.B. Mariotto.
Critical revision of the article for important intellectual content: H. Cho, C.N. Klabunde, K.R. Yabroff, I. Lansdorp-Vogelaar, A.B. Mariotto.
Final approval of the article: H. Cho, C.N. Klabunde, K.R. Yabroff, Z. Wang, I. Lansdorp-Vogelaar, A.B. Mariotto.
Statistical expertise: H. Cho, Z. Wang, A.B. Mariotto.
Administrative, technical, or logistic support: H. Cho.
Collection and assembly of data: H. Cho, A. Meekins.
Cho H., Klabunde C., Yabroff K., Wang Z., Meekins A., Lansdorp-Vogelaar I., Mariotto A.; Comorbidity-Adjusted Life Expectancy: A New Tool to Inform Recommendations for Optimal Screening Strategies. Ann Intern Med. 2013;159:667-676. doi: 10.7326/0003-4819-159-10-201311190-00005
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Published: Ann Intern Med. 2013;159(10):667-676.
Many guidelines recommend considering health status and life expectancy when making cancer screening decisions for elderly persons.
To estimate life expectancy for elderly persons without a history of cancer, taking into account comorbid conditions.
Population-based cohort study.
A 5% sample of Medicare beneficiaries in selected geographic areas, including their claims and vital status information.
Medicare beneficiaries aged 66 years or older between 1992 and 2005 without a history of cancer (n = 407 749).
Medicare claims were used to identify comorbid conditions included in the Charlson index. Survival probabilities were estimated by comorbidity group (no, low/medium, and high) and for the 3 most prevalent conditions (diabetes, chronic obstructive pulmonary disease, and congestive heart failure) by using the Cox proportional hazards model. Comorbidity-adjusted life expectancy was calculated based on comparisons of survival models with U.S. life tables. Survival probabilities from the U.S. life tables providing the most similar survival experience to the cohort of interest were used.
Persons with higher levels of comorbidity had shorter life expectancies, whereas those with no comorbid conditions, including very elderly persons, had favorable life expectancies relative to an average person of the same chronological age. The estimated life expectancy at age 75 years was approximately 3 years longer for persons with no comorbid conditions and approximately 3 years shorter for those with high comorbidity relative to the average U.S. population.
The cohort was limited to Medicare fee-for-service beneficiaries aged 66 years or older living in selected geographic areas. Data from the Surveillance, Epidemiology, and End Results cancer registry and Medicare claims lack information on functional status and severity of comorbidity, which might influence life expectancy in elderly persons.
Life expectancy varies considerably by comorbidity status in elderly persons. Comorbidity-adjusted life expectancy may help physicians tailor recommendations for stopping or continuing cancer screening for individual patients.
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Cardiology, Endocrine and Metabolism, Geriatric Medicine, Hematology/Oncology, Pulmonary/Critical Care.
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Print ISSN: 0003-4819 | Online ISSN: 1539-3704
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