Iterative generalized least squares for meta-analysis of survival data at multiple times

Abstract

A method is presented for joint analysis of survival proportions reported at multiple times in published studies to be combined in a meta-analysis. Generalized least squares is used to fit linear models including between-trial and within-trial covariates, using current fitted values iteratively to derive correlations between times within studies. Multi-arm studies and nonrandomized historical controls can be included with no special handling. The method is illustrated with data from two previously published meta-analyses. In one, an early treatment difference is detected that was not apparent in the original analysis.