Sample size considerations for single-arm clinical trials with time-to-event endpoint using the gamma distribution

IF 1.4 Q4 MEDICINE, RESEARCH & EXPERIMENTAL
Junqiang Dai, Jianghua He, Milind A. Phadnis
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引用次数: 0

Abstract

Background

Time-to-event (TTE) endpoints are evaluated as the primary endpoint in single-arm clinical trials; however, limited options are available in statistical software for sample size calculation. In single-arm trials with TTE endpoints, the non-parametric log-rank test is commonly used. Parametric options for single-arm design assume survival times follow exponential distribution or Weibull distribution.

Methods

The exponential- or Weibull-distributed survival time assumption does not always reflect hazard pattern of real-life diseases. We therefore propose gamma distribution as an alternative parametric option for designing single-arm studies with TTE endpoints. We outline a sample size calculation approach using gamma distribution with a known shape parameter and explain how to extract the gamma shape estimate from previously published resources. In addition, we conduct simulations to assess the accuracy of the extracted gamma shape parameter and to explore the impact on sample size calculation when survival time distribution is misspecified.

Results

Our simulations show that if a previously published study (sample sizes 60 and censoring proportions 20 %) reported median and inter-quartile range of survival time, we can obtain a reasonably accurate gamma shape estimate, and use it to design new studies. When true survival time is Weibull-distributed, sample size calculation could be underestimated or overestimated depending on the hazard shape.

Conclusions

We show how to use gamma distribution in designing a single-arm trial, thereby offering more options beyond the exponential and Weibull. We provide a simulation-based assessment to ensure an accurate estimation of the gamma shape and recommend caution to avoid misspecification of the underlying distribution.

使用伽马分布的单臂临床试验中时间到事件终点的样本量考虑因素
背景时间-事件(TTE)终点在单臂临床试验中作为主要终点进行评估;然而,统计软件中用于样本量计算的选项有限。在以 TTE 为终点的单臂试验中,通常使用非参数对数秩检验。方法指数分布或 Weibull 分布的生存时间假设并不总能反映现实生活中疾病的危害模式。因此,我们建议将伽玛分布作为设计 TTE 终点单臂研究的另一种参数选择。我们概述了使用已知形状参数的伽玛分布计算样本量的方法,并解释了如何从以前发表的资料中提取伽玛形状估计值。此外,我们还进行了模拟,以评估提取的伽玛形状参数的准确性,并探讨当生存时间分布被错误指定时对样本量计算的影响。结果我们的模拟显示,如果以前发表的研究(样本量≥60,删减比例≤20%)报告了生存时间的中位数和四分位间范围,我们就能获得相当准确的伽玛形状估计值,并用它来设计新的研究。结论我们展示了如何在设计单臂试验时使用伽马分布,从而在指数分布和威布尔分布之外提供更多选择。我们提供了一种基于模拟的评估方法,以确保准确估计伽马分布的形状,并建议小心谨慎,避免对基础分布进行错误规范。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Contemporary Clinical Trials Communications
Contemporary Clinical Trials Communications Pharmacology, Toxicology and Pharmaceutics-Pharmacology
CiteScore
2.70
自引率
6.70%
发文量
146
审稿时长
20 weeks
期刊介绍: Contemporary Clinical Trials Communications is an international peer reviewed open access journal that publishes articles pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from a wide range of disciplines including medicine, life science, pharmaceutical science, biostatistics, epidemiology, computer science, management science, behavioral science, and bioethics. Contemporary Clinical Trials Communications is unique in that it is outside the confines of disease specifications, and it strives to increase the transparency of medical research and reduce publication bias by publishing scientifically valid original research findings irrespective of their perceived importance, significance or impact. Both randomized and non-randomized trials are within the scope of the Journal. Some common topics include trial design rationale and methods, operational methodologies and challenges, and positive and negative trial results. In addition to original research, the Journal also welcomes other types of communications including, but are not limited to, methodology reviews, perspectives and discussions. Through timely dissemination of advances in clinical trials, the goal of Contemporary Clinical Trials Communications is to serve as a platform to enhance the communication and collaboration within the global clinical trials community that ultimately advances this field of research for the benefit of patients.
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