Competing time-to-event endpoints in cardiology trials: A simulation study to illustrate the importance of an adequate statistical analysis

Geraldine Rauch; Meinhard Kieser; Sandra Ulrich; Patrick Doherty; Bernhard Rauch; Steffen Schneider; Thomas Riemer; Jochen Senges

doi:10.1177/2047487312460518

Competing time-to-event endpoints in cardiology trials: A simulation study to illustrate the importance of an adequate statistical analysis

Geraldine Rauch, Meinhard Kieser, Sandra Ulrich, Patrick Doherty, Bernhard Rauch, Steffen Schneider, Thomas Riemer, Jochen Senges

Health Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

Clinical trials in cardiology commonly consider time-to-event endpoints that are often influenced by competing risks. In the presence of competing risks, standard survival analysis techniques, such as the Kaplan-Meier estimator, can yield seriously biased results. Although methods to account for competing risks are well known in the statistical literature, they are rarely applied in clinical trials.

Original language	English
Pages (from-to)	74-80
Number of pages	7
Journal	European journal of preventive cardiology
Volume	21
Issue number	1
Early online date	10 Sep 2012
DOIs	https://doi.org/10.1177/2047487312460518
Publication status	Published - Jan 2014

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10.1177/2047487312460518

Cite this

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abstract = "Clinical trials in cardiology commonly consider time-to-event endpoints that are often influenced by competing risks. In the presence of competing risks, standard survival analysis techniques, such as the Kaplan-Meier estimator, can yield seriously biased results. Although methods to account for competing risks are well known in the statistical literature, they are rarely applied in clinical trials.",

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