title: Competing time-to-event endpoints in cardiology trials: a simulation study to illustrate the importance of an adequate statistical analysis.
abstract: BACKGROUND
  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.
  
  
  METHODS
  Simulation study, to demonstrate the appropriate application and interpretation of the competing risks methodology with respect to time-to-event endpoints.
  
  
  METHODS
  In this paper, different statistical approaches to account for competing risks are systematically compared, based on a simulation study and using the original data from a cardiology trial.
  
  
  RESULTS
  Group comparisons in clinical trials that have competing time-to-event endpoints should be based on the cause-specific hazard functions. In contrast, group comparisons based on event rates should be carried out with care, as event rates are directly influenced by competing events.
  
  
  CONCLUSIONS
  Ignoring or not fully accounting for competing risks may yield misleading or even erroneous results, which could hinder understanding of survival trends; therefore, it is important that competing risks methodology be routinely incorporated into clinical trial standards.
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Germany.
authors.forename: Geraldine
authors.initials: G
authors.lastname: Rauch
authors.forename: Meinhard
authors.initials: M
authors.lastname: Kieser
authors.forename: Sandra
authors.initials: S
authors.lastname: Ulrich
authors.forename: Patrick
authors.initials: P
authors.lastname: Doherty
authors.forename: Bernhard
authors.initials: B
authors.lastname: Rauch
authors.forename: Steffen
authors.initials: S
authors.lastname: Schneider
authors.forename: Thomas
authors.initials: T
authors.lastname: Riemer
authors.forename: Jochen
authors.initials: J
authors.lastname: Senges
mesh_terms: D035843:Biomedical Research / Q000706:statistics & numerical data*; D002309:Cardiology / Q000706:statistics & numerical data*; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D023381:Endpoint Determination; D006801:Humans; D053208:Kaplan-Meier Estimate; D015233:Models, Statistical; D016016:Proportional Hazards Models; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome