The use of standard univariate fixed- and fandom-effects models in meta-analysis has become well known in the last 20 years. However, these models are unsuitable for meta-analysis of clinical trials that present multiple survival estimates (usually illustrated by a survival curve) during a follow-up period. Therefore, special methods are needed to combine the survival curve data from different trials in a meta-analysis. For this purpose, only fixed-effects models have been suggested in the literature. In this paper, we propose a multivariate random-effects model for joint analysis of survival proportions reported at multiple time points and in different studies, to be combined in a meta-analysis. The model could be seen as a generalization of the fixed-effects model of Dear (Biometrics 1994; 50:989-1002). We illustrate the method by using a simulated data example as well as using a clinical data example of meta-analysis with aggregated survival curve data. All analyses can be carried out with standard general linear MIXED model software.

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Statistics in Medicine
Erasmus MC: University Medical Center Rotterdam

Arends, L., Hunink, M., & Stijnen, T. (2008). Meta-analysis of summary survival curve data. Statistics in Medicine, 27(22), 4381–4396. doi:10.1002/sim.3311