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Survivor Treatment Selection Bias in Observational Studies: Examples from the AIDS Literature

Marshall J. MD, Glesby; and Donald R. Hoover, PhD
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From Johns Hopkins University, Baltimore, Maryland. Acknowledgments: The authors thank Wendy Tocci for preparing the figures and Dr. Ted Hoehn-Saric for his thoughtful review of the manuscript. Grant Support: In part by contract IU0135042-01 from the National Institute of Allergy and Infectious Diseases. Requests for Reprints: Donald R. Hoover, PhD, Department of Epidemiology, The Johns Hopkins University School of Hygiene and Public Health, 624 North Broadway, Room 784, Baltimore, MD 21205. Current Author Addresses: Dr. Glesby: Division of Infectious Diseases, The Johns Hopkins University School of Medicine, Ross Research Building, Room 1159, 720 Rutland Avenue, Baltimore, MD 21205.

Copyright ©2004 by the American College of Physicians

Ann Intern Med. 1996;124(11):999-1005. doi:10.7326/0003-4819-124-11-199606010-00008
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Unlike patients in a randomized, clinical trial, patients in an observational study choose if and when to begin treatment. Patients who live longer have more opportunities to select treatment; those who die earlier may be untreated by default. These facts are the essence of an often overlooked bias, termed “survivor treatment selection bias,” which can erroneously lead to the conclusion that an ineffective treatment prolongs survival. Unfortunately, misanalysis of survivor treatment selection bias has been prevalent in the recent literature on the acquired immunodeficiency syndrome. Approaches to mitigating this bias involve complex statistical models. At a minimum, initiation of therapy should be treated as a time-dependent covariate in a proportional hazards model. Investigators and readers should be on the alert for survivor treatment selection bias and should be cautious when interpreting the results of observational treatment studies.


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Figure 1.
Hypothetical example of survivor treatment selection bias.dashed line

Plots of expected Kaplan-Meier estimates of survival in a hypothetical observational cohort of 1000 patients with the acquired immunodeficiency syndrome who are untreated ( ) or treated (solid line) with a drug that has no effect on survival. Regardless of drug use, 50 patients die each month so that all have died by 20 months. Beginning after the first month of observation, 10% of patients who are alive and untreated at each successive monthly interval initiate therapy with the ineffective drug so that about 56% of patients will use the treatment before they die. Even though the treatment is ineffective, it erroneously appears to prolong survival because of survivor treatment selection bias: Living longer increases the chance to use the treatment.

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Figure 2.
Hypothetical example showing that sicker patients are more likely to initiate treatment.

AIDS equals acquired immunodeficiency syndrome.

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Figure 3.
Hypothetical example showing the inadequacy of statistical adjustment for markers of patient health status that are measured only at baseline.

AIDS equals acquired immunodeficiency syndrome.

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Figure 4.
Hypothetical example showing that statistical adjustment for a sequentially measured (time-dependent) marker of health status may incompletely adjust for true health status.

AIDS equals acquired immunodeficiency syndrome.

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Figure 5.
Hypothetical example showing that statistical adjustment for a marker of health status that is influenced by the treatment may eliminate the treatment effect.

AIDS equals acquired immunodeficiency syndrome.

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