Several regression-based methods exist to estimate an adjusted difference in RMSTs, but they digress from the model-free method of taking the area under the survival function. see [1,2]). Yes Yes Conceived and designed the experiments: BL AM JPP ORA JB. It provides a more easily understood measure of the treatment effect of an intervention in a controlled clinical trial with a time to event endpoint. Three kinds of between-group constrast metrics (i.e. The difference in restricted mean survival between PWID and people who did not inject drugs was − 0.19 years (95% CI: -0.29, − 0.09). Estimations were done every 355 deaths: at 0.45 year, 0.81 year, 1.25 year, 2.02 years, 5 years and an extra point estimation for patients who died after 5 years. Earle and Wells [32] compared five methods to combine published survival curves from studies of patients treated with chemotherapy for advanced non-small-cell lung cancer. The size of the square is directly proportional to the amount of information contributed by the trial. Gustave Roussy, Ligue Nationale Contre le Cancer meta-analysis plateform, Villejuif, France, Affiliations At a ceiling ratio of € 25,000 per life year-gained, the probability of the experimental treatment being cost-effective ranged from 31% to 68%. Table 1. Our aim was to study if/how the choice of a method impacts on cost-effectiveness results. Calculate Mean Survival Time. in case of non-proportional hazards with survival curves crossing later than t*), a sensitivity analysis varying t* should be performed to determine the impact on the estimation of the overall rmstD. The authors concluded that, overall, all the five methods were quite accurate but they pointed out that most of these methods failed to address stratification by trial and treatment effect heterogeneity. For the first approach, the rmstD can be estimated based on the follow-up of the trials using pooled survival curves. Then, parametric models can be used to estimate the difference in mean survival time beyond the trials’ follow-up. Naive Kaplan-Meier and Stewart-Parmar provided the same survival curve, by definition, for the conventional arm, and quite similar survival curves for the modified arm (S1 Fig). Based on two applications and a simulation study, the authors concluded that the three methods yielded similar results with respect to bias, mean square error and coverage probability. Alternatively, similarly to the Stewart-Parmar method and to the method used in a number of studies reviewed by Guyot and colleagues [30], one could fit a parametric model to compute the survival function in the control arm. Table 1 summarizes the ability of these methods to address stratification by trial, non-proportionality of hazards (variation of the treatment effect over time) and treatment effect heterogeneity. PLoS ONE 11(3): In this case study, we focused on the rmstD using the follow-up of the trials of the MAR-LC. Panel A of Fig. With the second approach, the rmstD is based on the aggregation of rmstDs estimated in each RCT [18]. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Citation: Lueza B, Mauguen A, Pignon J-P, Rivero-Arias O, Bonastre J, MAR-LC Collaborative Group (2016) Difference in Restricted Mean Survival Time for Cost-Effectiveness Analysis Using Individual Patient Data Meta-Analysis: Evidence from a Case Study. If the true survival curves remain separated beyond the point of restriction, the difference in restricted means will increase with t *. The rmstD is then the area between the two Kaplan-Meier survival curves. We applied Stewart and Parmar methodology [25] to estimate the pooled survival curve for the experimental arm using the pooled hazard ratio and the naive Kaplan-Meier survival curve in the control group. The Pooled Kaplan-Meier method addresses non-proportional hazards, whereas the Pooled Exponential method, which is based on the exponential proportional hazards model, does not. Dahlberg (Dana-Farber Cancer Institute), D. De Ruysscher (University Hospital Leuven and University Hospital Maastricht), S. Dische (Mount Vernon Hospital), P. Fournel (Institut de Cancérologie de la Loire), R. Koch (University of Dresden), C. Le Péchoux (Gustave Roussy), S.J. The rmstDs are then pooled across trials. 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