Conditional power of survival endpoints at interim analyses can support decisions on continuing a trial or stopping it for futility. When a cure fraction becomes apparent, conditional power cannot be calculated accurately using simple survival models, e.g. the exponential model. Non-mixture models consider such cure fractions. In this paper, we derive conditional power functions for non-mixture models, namely the non-mixture exponential, the non-mixture Weibull, and the non-mixture Gamma models. Formulae were implemented in the R package CP. For an example data set of a clinical trial, we calculated conditional power under the non-mixture models and compared results with those under the simple exponential model.
PubMed ID: 28328527
Projects: Genetical Statistics and Systems Biology
Publication type: Journal article
Journal: Int J Biostat
Human Diseases: No Human Disease specified
Citation: Int J Biostat. 2017 Mar 17;13(1). pii: /j/ijb.ahead-of-print/ijb-2015-0073/ijb-2015-0073.xml. doi: 10.1515/ijb-2015-0073.
Date Published: 17th Mar 2017
Registered Mode: by PubMed ID
Views: 1909
Created: 3rd Sep 2020 at 08:01
Last updated: 7th Dec 2021 at 17:58
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