Ruth Etzioni1, Roman Gulati2, Daniel W Lin3. 1. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA. Electronic address: retzioni@fhcrc.org. 2. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA. 3. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA; University of Washington School of Medicine, Seattle, WA.
Abstract
BACKGROUND: A variety of measures of survival benefit are available to an investigator comparing outcomes across the various arms of a drug development trial. In this article, we systematically review the most common measures of comparative survival used in published studies. MATERIALS: We distinguish between relative and absolute survival differences, and measures of instantaneous and cumulative risk. We consider settings in which the end point is overall survival as well as those in which disease-specific end points are of primary interest. RESULTS: We note that different measures capture different aspects of benefit, and some may be more reliable than others or more representative of clinically relevant benefit. CONCLUSIONS: Rather than simply using procedures that have become standard, analyses should identify the most clinically relevant measures of effect and apply procedures that reliably estimate these.
BACKGROUND: A variety of measures of survival benefit are available to an investigator comparing outcomes across the various arms of a drug development trial. In this article, we systematically review the most common measures of comparative survival used in published studies. MATERIALS: We distinguish between relative and absolute survival differences, and measures of instantaneous and cumulative risk. We consider settings in which the end point is overall survival as well as those in which disease-specific end points are of primary interest. RESULTS: We note that different measures capture different aspects of benefit, and some may be more reliable than others or more representative of clinically relevant benefit. CONCLUSIONS: Rather than simply using procedures that have become standard, analyses should identify the most clinically relevant measures of effect and apply procedures that reliably estimate these.
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