An extension of generalized pairwise comparisons for prioritized outcomes in the presence of censoring

Author:

Péron Julien12,Buyse Marc34,Ozenne Brice12,Roche Laurent12,Roy Pascal12

Affiliation:

1. Service de biostatistiques, Centre Hospitalier Lyon-Sud, Institut du Cancer des Hospices Civils de Lyon, France

2. CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique-Santé, Université Lyon 1, France

3. International Drug Development Institute (IDDI), USA

4. Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt University, Belgium

Abstract

Generalized pairwise comparisons have been proposed to permit a comprehensive assessment of several prioritized outcomes between two groups of observations. This procedure estimates Δ, the net chance of a better outcome with treatment than with control by comparing the patients outcomes among all possible pairs taking one patient from the treatment group and one patient from the control group. For time to event outcomes, the standard procedure of generalized pairwise comparisons is analogous to the Gehan’s modification of the Mann-Whitney test which is biased in presence of censored observation and less powerful than Efron’s modification of this test. We adapt Efron’s modification to generalized pairwise comparisons. We show how a pairwise contribution to Δ can be calculated from the estimates of the survival function in the presence of right-censored data. We performed a simulation study to assess the bias, the type I error and the power of the new procedure. The estimate of Δ with the new procedure is only slightly biased even in presence of heavy censoring. We also show how this bias can be corrected when only one time-to-event outcome is analyzed. The new procedure has higher power in most cases compared to the standard procedure.

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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