Iterative generalized least squares for meta-analysis of survival data at multiple times.
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.
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Technology Assessment Group, Harvard School of Public Health, Boston, Massachusetts 02115.
D000970:Antineoplastic Agents / Q000627:therapeutic use; D001699:Biometry / Q000379:methods; D016026:Bone Marrow Transplantation; D003131:Combined Modality Therapy; D018572:Disease-Free Survival; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000188:drug therapy / Q000401:mortality / Q000628:therapy; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D011336:Probability; D016016:Proportional Hazards Models; D016019:Survival Analysis; D014184:Transplantation, Homologous
D000970:Antineoplastic Agents