考虑治愈分数的生存时间分析中的条件幂。

IF 1.2 4区 数学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Andreas Kuehnapfel, Fabian Schwarzenberger, Markus Scholz
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引用次数: 1

摘要

中期分析的有条件生存力终点可以支持继续试验或因无效而停止试验的决定。当固化分数变得明显时,不能使用简单的生存模型(例如指数模型)准确地计算条件功率。非混合模型考虑这样的固化分数。本文导出了非混合模型的条件幂函数,即非混合指数模型、非混合Weibull模型和非混合Gamma模型。公式在R包CP中实现。以临床试验数据集为例,我们计算了非混合模型下的条件功率,并将结果与简单指数模型下的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.

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来源期刊
International Journal of Biostatistics
International Journal of Biostatistics MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY
CiteScore
2.10
自引率
8.30%
发文量
28
审稿时长
>12 weeks
期刊介绍: The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.
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