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December 1, 2021

Practical Recommendations on Quantifying and Interpreting Treatment Effects in the Presence of Terminal Competing Risks: A Review

Author Affiliations
  • 1Google, Mountain View, California
  • 2Cardiovascular Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
  • 3Department of Biomedical Data Science, Stanford University, Stanford, California
  • 4Academic Research Organization–Hospital Israelita Albert Einstein, Sao Paulo, Brazil
  • 5Harvard T.H. Chan School of Public Health, Boston, Massachusetts
JAMA Cardiol. 2022;7(4):450-456. doi:10.1001/jamacardio.2021.4932

Importance  In a comparative trial, the time to a clinical event is often a key end point. However, the occurrence of a terminal event, such as death or premature study discontinuation, may preclude observation of this outcome. Although various methods for handling competing risks are available, no specific recommendations have been made for scenarios encountered in practice, especially when the terminal event profiles of the study arms are dissimilar. Moreover, appropriate methods for a desirable outcome, such as live hospital discharge, have seldom been discussed.

Observations  Several of the most commonly used methods are reviewed. The first regards the terminal event as censoring and applies standard survival analysis to the event of interest. The between-group difference is usually summarized by the cause-specific hazard ratio. This summary measure is inappropriate when the new therapy markedly prolongs time to the terminal event. Moreover, the corresponding Kaplan-Meier curve for the end point of interest is uninterpretable. The second method is to use the cumulative incidence curve, which is the probability of experiencing the event of interest by each time point, acknowledging that patients who have died will never experience the event. However, the resulting pseudo hazard ratio is difficult to interpret. With a proper alternative summary measure, this approach works well for a desirable outcome but may not for an undesirable outcome. The third method focuses on the event-free survival time by combining information from occurrences of the terminal event and the event of interest simultaneously. This clinically interpretable method naturally accounts for differences in terminal event rates when comparing treatments with respect to the time to an undesirable outcome.

Conclusions and Relevance  This article enhances our understanding of each method’s advantages and shortcomings and assists practitioners in choosing appropriate methods for handling competing risk problems in practice.

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