The asymptotic distribution of the Net Benefit estimator in presence of right-censoring

The benefit-risk balance is a critical information when evaluating a new treatment. The Net Benefit has been proposed as a metric for the benefit-risk assessment, and applied in oncology to simultaneously consider gains in survival and possible side effects of chemotherapies. With complete data, one...

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Bibliographic Details
Published in:Statistical methods in medical research Vol. 30; no. 11; p. 2399
Main Authors: Ozenne, Brice, Budtz-Jørgensen, Esben, Péron, Julien
Format: Journal Article
Language:English
Published: England 01.11.2021
Subjects:
Clinical Trials as Topic
Computer Simulation
Humans
Research Design
Clinical trial
censoring
statistical inference
non-parametric statistics
multivariate analysis
ISSN:1477-0334, 1477-0334
Online Access:Get more information
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Summary:The benefit-risk balance is a critical information when evaluating a new treatment. The Net Benefit has been proposed as a metric for the benefit-risk assessment, and applied in oncology to simultaneously consider gains in survival and possible side effects of chemotherapies. With complete data, one can construct a U-statistic estimator for the Net Benefit and obtain its asymptotic distribution using standard results of the U-statistic theory. However, real data is often subject to right-censoring, e.g. patient drop-out in clinical trials. It is then possible to estimate the Net Benefit using a modified U-statistic, which involves the survival time. The latter can be seen as a nuisance parameter affecting the asymptotic distribution of the Net Benefit estimator. We present here how existing asymptotic results on U-statistics can be applied to estimate the distribution of the net benefit estimator, and assess their validity in finite samples. The methodology generalizes to other statistics obtained using generalized pairwise comparisons, such as the win ratio. It is implemented in the R package BuyseTest (version 2.3.0 and later) available on Comprehensive R Archive Network.
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ISSN:1477-0334
1477-0334
DOI:10.1177/09622802211037067