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One-stage parametric meta-analysis of time-to-event outcomes Siannis F; Barrett JK; Farewell VT; Tierney JFStat Med 2010[Dec]; 29 (29): 3030-45Methodology for the meta-analysis of individual patient data with survival end-points is proposed. Motivated by questions about the reliance on hazard ratios as summary measures of treatment effects, a parametric approach is considered and percentile ratios are introduced as an alternative to hazard ratios. The generalized log-gamma model, which includes many common time-to-event distributions as special cases, is discussed in detail. Likelihood inference for percentile ratios is outlined. The proposed methodology is used for a meta-analysis of glioma data that was one of the studies which motivated this work. A simulation study exploring the validity of the proposed methodology is available electronically.|*Meta-Analysis as Topic[MESH]|*Models, Statistical[MESH]|*Treatment Outcome[MESH]|Algorithms[MESH]|Computer Simulation[MESH]|Glioma/drug therapy/mortality/therapy[MESH]|Humans[MESH]|Likelihood Functions[MESH]|Logistic Models[MESH]|Proportional Hazards Models[MESH]|Randomized Controlled Trials as Topic[MESH]|Regression Analysis[MESH]|Statistical Distributions[MESH]|Survival Rate[MESH] |
