Meta-analysis of summary survival curve data.
The use of standard univariate fixed- and random-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.
Arends
Lidia R
LR
Department of Epidemiology & Biostatistics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands. l.arends@erasmusmc.nl
Hunink
M G Myriam
MG
Stijnen
Theo
T
D000704:Analysis of Variance; D016026:Bone Marrow Transplantation; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D018572:Disease-Free Survival; D006801:Humans; D053208:Kaplan-Meier Estimate; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D009369:Neoplasms / Q000188:drug therapy / Q000601:surgery; D011336:Probability