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 |
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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. |
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ISSN: | 1557-4679 2194-573X 1557-4679 |
DOI: | 10.1515/ijb-2015-0073 |