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Stopping at Nothing? Some Dilemmas of Data Monitoring in Clinical Trials
- Steven N. Goodman, MD, MHS, PhD
Abstract
This commentary reviews the argument that clinical trials with data monitoring committees that use statistical stopping guidelines should generally not be stopped early for large observed efficacy differences because efficacy estimates may be exaggerated and there is minimal information on treatment harms. Overall, the average of estimates from trials that use these boundaries differs minimally from the true value. Estimates from a given trial that seem implausibly high can be moderated by using Bayesian methods. Data monitoring committees are not ethically required to precisely estimate a large efficacy difference if that difference differs convincingly from zero, and the requirement to detect harms and balance efficacy against harm depends on whether the nature of the harm is known or unknown before the trial.
Article and Author Information
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Disclaimer: The views and content herein are solely the responsibility of the author.
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Acknowledgments: The author thanks Drs. Donald Berry, Thomas Louis, and Joel Greenhouse for their helpful comments on earlier versions of the manuscript.
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Potential Financial Conflicts of Interest: None disclosed.
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Requests for Single Reprints: Steven N. Goodman, MD, MHS, PhD, Johns Hopkins University Schools of Medicine and Public Health, 550 North Broadway, Suite 1103, Baltimore, MD 21205; e-mail, sgoodman{at}jhmi.edu.
