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在意向性分析中进行治疗转换的非劣效性试验的功效和样本量计算,比较受限平均生存时间。

Power and sample size calculation for non-inferiority trials with treatment switching in intention-to-treat analysis comparing RMSTs.

作者信息

Shih Austin, Hsu Chih-Yuan, Shyr Yu

机构信息

Department of Mathematics, Vanderbilt University, Nashville, TN, 37240, USA.

Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, 37203, USA.

出版信息

BMC Med Res Methodol. 2025 Jun 7;25(1):157. doi: 10.1186/s12874-025-02604-3.

Abstract

BACKGROUND

Difference in Restricted Mean Survival Time (DRMST) has attracted attention and is increasingly used in non-inferiority (NI) trials because of its superior power in detecting treatment effects compared to hazard ratio. However, when treatment switching (also known as crossover) occurs, the widely used intention-to-treat (ITT) analysis can underpower or overpower NI trials.

METHODS

We propose a simulation-based approach, named nifts, to calculate powers and determine the necessary sample size to achieve a desired power for non-inferiority trials that allow treatment switching, in ITT analysis using DRMST.

RESULTS

The nifts approach offers three options for a non-inferiority margin, assumes three entry patterns and generalized gamma distributions for event time, incorporates two distributions for dropout censoring, and provides five distribution options for switching. Real-world and simulated examples are used to illustrate the proposed method and examine how switching probability, switching time, the relative effectiveness of treatments, allocation ratio, entry patterns, and event time distribution influence powers and sample sizes. nifts adjusts the non-inferiority margins intended for NI trials without treatment switching to accommodate the presence of treatment switching in the designs. With the adjusted margins, the type I errors are well-controlled. The ratios of sample sizes with treatment switching to those without switching are close to 1, indicating no significant change in power at sample sizes without switching when using adjusted margins. The performance on power and sample sizes is not sensitive to the choice of switch time distributions.

CONCLUSIONS

This simulation-based approach provides power and sample size calculation in NI trials with treatment switching, when comparing the RMSTs of two treatment groups in ITT analysis. With its comprehensive parameter settings, nifts will be useful for designing NI trials that allow for treatment switching. nifts is freely available at https://github.com/cyhsuTN/nifts .

摘要

背景

受限平均生存时间差异(DRMST)已引起关注,并且由于其在检测治疗效果方面比风险比具有更高的效能,因此在非劣效性(NI)试验中越来越多地被使用。然而,当发生治疗转换(也称为交叉)时,广泛使用的意向性分析(ITT)可能会使NI试验的效能不足或过高。

方法

我们提出了一种基于模拟的方法,称为nifts,用于在使用DRMST的ITT分析中,计算允许治疗转换的非劣效性试验的效能,并确定达到所需效能所需的样本量。

结果

nifts方法为非劣效性界值提供了三种选择,假设事件时间有三种入组模式和广义伽马分布,纳入了两种失访删失分布,并为转换提供了五种分布选项。使用实际例子和模拟例子来说明所提出的方法,并检验转换概率、转换时间、治疗的相对有效性、分配比例、入组模式和事件时间分布如何影响效能和样本量。nifts会调整原本用于无治疗转换的NI试验的非劣效性界值,以适应设计中存在的治疗转换情况。通过调整后的界值,I类错误得到了很好的控制。有治疗转换时的样本量与无转换时的样本量之比接近1,表明在使用调整后的界值时,无转换时的样本量下效能没有显著变化。效能和样本量的表现对转换时间分布的选择不敏感。

结论

这种基于模拟的方法在ITT分析中比较两个治疗组的RMST时,为有治疗转换的NI试验提供了效能和样本量计算。由于其全面的参数设置,nifts将有助于设计允许治疗转换的NI试验。nifts可在https://github.com/cyhsuTN/nifts上免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c8a/12144734/6b8a88a2f0cb/12874_2025_2604_Fig1_HTML.jpg

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