On the Conditional Power in Survival Time Analysis Considering Cure Fractions

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 c...

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Veröffentlicht in:The international journal of biostatistics 2017-03, Vol.13 (1), p.351
Hauptverfasser: Kuehnapfel, Andreas, Schwarzenberger, Fabian, Scholz, Markus
Format: Artikel
Sprache:eng
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Zusammenfassung: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 . 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.
ISSN:1557-4679
2194-573X
1557-4679
DOI:10.1515/ijb-2015-0073