Meta-analysis of clinical trials with competing time-to-event endpoints

Alessandra Meddis, Aurélien Latouche, Bingqing Zhou, Stefan Michiels, Jason Fine

    Résultats de recherche: Contribution à un journalArticleRevue par des pairs

    1 Citation (Scopus)

    Résumé

    Recommendations for the analysis of competing risks in the context of randomized clinical trials are well established. Meta-analysis of individual patient data (IPD) is the gold standard for synthesizing evidence for clinical interpretation based on multiple studies. Surprisingly, no formal guidelines have been yet proposed to conduct an IPD meta-analysis with competing risk endpoints. To fill this gap, this work details (i) how to handle the heterogeneity between trials via a stratified regression model for competing risks and (ii) that the usual metrics of inconsistency to assess heterogeneity can readily be employed. Our proposal is illustrated by the re-analysis of a recently published meta-analysis in nasopharyngeal carcinoma, aiming at quantifying the benefit of the addition of chemotherapy to radiotherapy on each competing endpoint.

    langue originaleAnglais
    Pages (de - à)712-723
    Nombre de pages12
    journalBiometrical Journal
    Volume62
    Numéro de publication3
    Les DOIs
    étatPublié - 1 mai 2020

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