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.
CITATION STYLE
Kuehnapfel, A., Schwarzenberger, F., & Scholz, M. (2017). On the Conditional Power in Survival Time Analysis Considering Cure Fractions. International Journal of Biostatistics, 13(1). https://doi.org/10.1515/ijb-2015-0073
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