Competing risks analyses: objectives and approaches.
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.
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 mwolbers@oucru.org.
Marcel
M
Wolbers
Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland.
Michael T
MT
Koller
ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Vianda S
VS
Stel
Department of Cardiology, University Hospital Basel, Basel, Switzerland.
Beat
B
Schaer
ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Kitty J
KJ
Jager
Centre INSERM U897 Epidemiology-Biostatistics, ISPED, University of Bordeaux, Bordeaux, France.
Karen
K
Leffondré
Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Georg
G
Heinze
D002309:Cardiology / Q000706:statistics & numerical data*; D002318:Cardiovascular Diseases / Q000401:mortality*; D006801:Humans; D015994:Incidence; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D015996:Survival Rate
Cause-specific hazard function; Combined endpoints; Cumulative incidence function; Multiple failure causes; Survival analysis