title: Meta-analysis for aggregated survival data with competing risks: a parametric approach using cumulative incidence functions.
abstract: Meta-analysis of a survival endpoint is typically based on the pooling of hazard ratios (HRs). If competing risks occur, the HRs may lose translation into changes of survival probability. The cumulative incidence functions (CIFs), the expected proportion of cause-specific events over time, re-connect the cause-specific hazards (CSHs) to the probability of each event type. We use CIF ratios to measure treatment effect on each event type. To retrieve information on aggregated, typically poorly reported, competing risks data, we assume constant CSHs. Next, we develop methods to pool CIF ratios across studies. The procedure computes pooled HRs alongside and checks the influence of follow-up time on the analysis. We apply the method to a medical example, showing that follow-up duration is relevant both for pooled cause-specific HRs and CIF ratios. Moreover, if all-cause hazard and follow-up time are large enough, CIF ratios may reveal additional information about the effect of treatment on the cumulative probability of each event type. Finally, to improve the usefulness of such analysis, better reporting of competing risks data is needed. Copyright © 2015 John Wiley & Sons, Ltd.
authors.affiliation: Institute of Medical Biometry and Statistics - Medical Center, University of Freiburg, Freiburg, Germany. bono@imbi.uni-freiburg.de.|Freiburg Center for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany. bono@imbi.uni-freiburg.de.
authors.forename: Federico
authors.identifier: http://orcid.org/0000-0003-4085-9840
authors.initials: F
authors.lastname: Bonofiglio
authors.affiliation: Institute of Statistics, University of Ulm, Ulm, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Beyersmann
authors.affiliation: Institute of Medical Biometry and Statistics - Medical Center, University of Freiburg, Freiburg, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Schumacher
authors.affiliation: Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland.
authors.forename: Michael
authors.initials: M
authors.lastname: Koller
authors.affiliation: Institute of Medical Biometry and Statistics - Medical Center, University of Freiburg, Freiburg, Germany.
authors.forename: Guido
authors.identifier: http://orcid.org/0000-0001-6214-9087
authors.initials: G
authors.lastname: Schwarzer
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D003625:Data Collection; D006801:Humans; D015994:Incidence; D015201:Meta-Analysis as Topic; D011336:Probability; D011381:Programming Languages; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012107:Research Design; D012307:Risk Factors; D013223:Statistics as Topic; D016019:Survival Analysis
keywords: competing risks; cumulative incidence function; meta-analysis; parametric hazard function; randomized controlled trial