A Poisson approach to the validation of failure time surrogate endpoints in individual patient data meta-analyses

Surrogate endpoints are often used in clinical trials instead of well-established hard endpoints for practical convenience. The meta-analytic approach relies on two measures of surrogacy: one at the individual level and one at the trial level. In the survival data setting, a two-step model based on copulas is commonly used. We present a new approach which employs a bivariate survival model with an individual random effect shared between the two endpoints and correlated treatment-by-trial interactions. We fit this model using auxiliary mixed Poisson models. We study via simulations the operating characteristics of this mixed Poisson approach as compared to the two-step copula approach. We illustrate the application of the methods on two individual patient data meta-analyses in gastric cancer, in the advanced setting (4069 patients from 20 randomized trials) and in the adjuvant setting (3288 patients from 14 randomized trials).

Jaar van publicatie:2019

Trefwoorden:Health Care Sciences & Services, Mathematical & Computational Biology, Medical Informatics, Statistics & Probability, Surrogate endpoint, failure time, meta-analysis, copula, randomized trials

BOF-keylabel:ja

IOF-keylabel:ja

BOF-publication weight:6

CSS-citation score:1

Auteurs:International

Authors from:Higher Education

Toegankelijkheid:Closed