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Estimating Treatment Benefits for the Elderly: The Effect of Competing Risks

H. Gilbert Welch, MD, MPH; Peter C. Albertsen, MD; Robert F. Nease, PhD; Thomas A. Bubolz, PhD; and John H. Wasson, MD
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From Department of Veterans Affairs Medical Center, White River Junction, Vermont; Dartmouth Medical School, Hanover, New Hampshire; the University of Connecticut, Farmington, Connecticut; and Washington University School of Medicine, St. Louis, Missouri. Acknowledgments: The authors thank J. Robert Beck for his methodologic review; R. Peter Mogielnicki, Robert S. Pritchard, and Gregory W. Froehlich for their thoughtful critique of the manuscript; and James O. Taylor for data from the East Boston Senior Health Project, one of the National Institute on Aging's Established Populations for the Epidemiologic Study of the Elderly (contract AG02107). Grant Support: Dr. Welch is supported by a Veterans Affairs Career Development Award in health services research and development. Dr. Nease is a Picker/Commonwealth Scholar. Requests for Reprints: John Wasson, MD, Department of Community and Family Medicine, Dartmouth Medical School, 7265 Butler Building, Hanover, NH 03755-3862. Current Author Addresses: Dr. Welch: Veterans Affairs Outcomes Group (111B), Department of Veterans Affairs Hospital, White River Junction, VT 05009.

Copyright ©2004 by the American College of Physicians

Ann Intern Med. 1996;124(6):577-584. doi:10.7326/0003-4819-124-6-199603150-00007
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To fully involve patients in treatment decisions, physicians need to communicate future health prospects that patients will have both with and without newly diagnosed disease.These prospects depend not only on the risks patients face from the new disease but also on the risks they face from other causes. Nowhere is an understanding of these competing risks more relevant than in the care of the elderly.

In this study, we use the declining exponential approximation for life expectancy (DEALE) to provide a framework to help clinicians gauge the effect of competing risks as a function of age.Because older patients have many competing risks for death, the absolute effect of a new diagnosis on life expectancy is often relatively small. Consequently, the potential gain in survival even from perfect therapy may also be small. Moreover, no therapy is perfect, and the risks of therapy often increase with age. In the elderly, the combination of a high burden of competing risks and high rates of treatment-related complications conspires to reduce the net benefit of numerous interventions. We conclude that, compared with younger patients, the elderly should request only the more clearly effective treatments and should be willing to tolerate fewer associated complications before they agree to initiate therapy.


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Figure 3.
The estimated effect of age on the expectation of disability for nondisabled men and women 5 years in the future[9]

. The definition of disability encompasses conditions ranging from the institutionalized frail elderly to persons who are cognitively impaired or cannot perform two or more instrumental activities of daily living.

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Figure 2.
The effect of age on the distribution of health states in the future.

This example considers the distribution of health states over 10 years for a woman newly diagnosed with a disease for which the 10-year disease-related mortality is 10%.

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Figure 1.
The effect of selected disease-related mortality rates on the remaining life expectancy of women (left) and men (right) at the time of diagnosis.

Normal life expectancy is indicated by the top curve; the four curves beneath the top curve represent life expectancies resulting from 5-year disease-related mortality rates of 5%, 10%, 25%, and 50%.

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