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Eur Heart J. 2014 Nov 7;35(42):2936-41. doi: 10.1093/eurheartj/ehu131. Epub 2014 Apr 7.

Competing risks analyses: objectives and approaches.

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Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK
Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland.
ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Department of Cardiology, University Hospital Basel, Basel, Switzerland.
Centre INSERM U897 Epidemiology-Biostatistics, ISPED, University of Bordeaux, Bordeaux, France.
Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.


Studies in cardiology often record the time to multiple disease events such as death, myocardial infarction, or hospitalization. Competing risks methods allow for the analysis of the time to the first observed event and the type of the first event. They are also relevant if the time to a specific event is of primary interest but competing events may preclude its occurrence or greatly alter the chances to observe it. We give a non-technical overview of competing risks concepts for descriptive and regression analyses. For descriptive statistics, the cumulative incidence function is the most important tool. For regression modelling, we introduce regression models for the cumulative incidence function and the cause-specific hazard function, respectively. We stress the importance of choosing statistical methods that are appropriate if competing risks are present. We also clarify the role of competing risks for the analysis of composite endpoints.


Cause-specific hazard function; Combined endpoints; Cumulative incidence function; Multiple failure causes; Survival analysis

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