A permutation test based on the restricted mean survival time for comparison of net survival distributions in non-proportional excess hazard settings - Aix-Marseille Université Access content directly
Journal Articles Statistical Methods in Medical Research Year : 2019

A permutation test based on the restricted mean survival time for comparison of net survival distributions in non-proportional excess hazard settings

Abstract

Net survival is used in epidemiological studies to assess excess mortality due to a given disease when causes of death are unreliable. By correcting for the general population mortality, it allows comparisons between regions or periods and thus evaluation of health policies. The Pohar-Perme non-parametric estimator of net survival has been recently proposed, soon followed by an appropriate log-rank-type test. However, log-rank tests are known to be under-optimal in non-proportional settings (e.g. crossing of the hazard functions). In classical survival analysis, one solution is to compare the restricted mean survival times. A difference in restricted mean survival time represents a life benefit or loss over the studied period. In the present article the restricted mean net survival time was used to derive a specific test statistic to compare net survivals in proportional and non-proportional hazards settings. The new test was generalized to more than two groups and to stratified analysis. The test performance was assessed on simulation study, compared to the log-rank-type test, and its use illustrated on a population-based colorectal cancer registry. The new test for net survival comparisons proved robust to non-proportionality and well-performing in proportional hazards situations. Furthermore, it is also suited to the classical survival framework.
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Dates and versions

hal-02613459 , version 1 (20-05-2020)

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Anna Wolski, Nathalie Grafféo, Roch Giorgi. A permutation test based on the restricted mean survival time for comparison of net survival distributions in non-proportional excess hazard settings. Statistical Methods in Medical Research, 2019, pp.096228021987021. ⟨10.1177/0962280219870217⟩. ⟨hal-02613459⟩
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