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A log-rank-type test to compare net survival distributions

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  • Nathalie Grafféo
  • Fabienne Castell
  • Aurélien Belot
  • Roch Giorgi

Abstract

type="main" xml:lang="en"> In population-based cancer studies, it is often interesting to compare cancer survival between different populations. However, in such studies, the exact causes of death are often unavailable or unreliable. Net survival methods were developed to overcome this difficulty. Net survival is the survival that would be observed if the disease under study was the only possible cause of death. The Pohar-Perme estimator (PPE) is a nonparametric consistent estimator of net survival. In this article, we present a log-rank-type test for comparing net survival functions (as estimated by PPE) between several groups. We put the test within the counting process framework to introduce the inverse probability weighting procedure as required by the PPE. We built a stratified version to control for categorical covariates that affect the outcome. We performed simulation studies to evaluate the performance of this test and worked an application on real data.

Suggested Citation

  • Nathalie Grafféo & Fabienne Castell & Aurélien Belot & Roch Giorgi, 2016. "A log-rank-type test to compare net survival distributions," Biometrics, The International Biometric Society, vol. 72(3), pages 760-769, September.
    • Handle: RePEc:bla:biomet:v:72:y:2016:i:3:p:760-769
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    1. Nicolas Bovio & Michel Grzebyk & Patrick Arveux & Jean-Luc Bulliard & Arnaud Chiolero & Evelyne Fournier & Simon Germann & Isabelle Konzelmann & Manuela Maspoli & Elisabetta Rapiti & Irina Guseva Canu, 2022. "Work-Related Factors and Lung Cancer Survival: A Population-Based Study in Switzerland (1990–2014)," IJERPH, MDPI, vol. 19(21), pages 1-16, October.

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