On the Conditional Power in Survival Time Analysis Considering Cure Fractions

Kuehnapfel Andreas (), Schwarzenberger Fabian and Scholz Markus
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Kuehnapfel Andreas: Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Haertelstrasse 16-18, 04107Leipzig, Germany
Schwarzenberger Fabian: Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Haertelstrasse 16-18, 04107Leipzig, Germany
Scholz Markus: Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Haertelstrasse 16-18, 04107Leipzig, Germany

The International Journal of Biostatistics, 2017, vol. 13, issue 1, 19

Abstract: 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.

Keywords: cure fraction; exponential survival; Gamma type survival; non-mixture model; proportional hazards; randomised clinical trial; Weibull type survival (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1515/ijb-2015-0073

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