对 I/II 期临床试验的新型模型辅助设计进行比较审查。

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Haolun Shi, Ruitao Lin, Xiaolei Lin
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引用次数: 0

摘要

近年来,出现了基于模型的设计和模型辅助设计,用于在免疫疗法和靶向细胞药物的I/II期试验中有效确定最佳生物剂量(OBD)。基于模型的设计需要反复进行模型拟合,每次剂量分配决策都需要进行计算密集的后验取样,这限制了其在实际试验中的应用。另一方面,模型辅助设计采用简单的统计模型,便于预先计算供整个试验使用的决策表,从而无需反复进行模型拟合。由于模型辅助设计既简单又透明,因此在 I/II 期试验中常常受到青睐。在本文中,除了众所周知的基于模型的 EffTox 设计外,我们还通过全面的数值模拟,系统地评估和比较了近期几种模型辅助 I/II 期设计的操作特性,包括 TEPI、PRINTE、Joint i3+3、BOIN-ET、STEIN、uTPI 和 BOIN12。为确保比较无偏见,我们使用随机情景生成算法为每个预定的 OBD 位置生成了 10,000 个剂量情景。我们全面评估了八种设计的各种性能指标,如选择百分比、OBD 患者平均分配率和超剂量百分比。在这些评估的基础上,我们提出了针对不同目标、样本大小和起始剂量位置的设计建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative review of novel model-assisted designs for phase I/II clinical trials

In recent years, both model-based and model-assisted designs have emerged to efficiently determine the optimal biological dose (OBD) in phase I/II trials for immunotherapy and targeted cellular agents. Model-based designs necessitate repeated model fitting and computationally intensive posterior sampling for each dose-assignment decision, limiting their practical application in real trials. On the other hand, model-assisted designs employ simple statistical models and facilitate the precalculation of a decision table for use throughout the trial, eliminating the need for repeated model fitting. Due to their simplicity and transparency, model-assisted designs are often preferred in phase I/II trials. In this paper, we systematically evaluate and compare the operating characteristics of several recent model-assisted phase I/II designs, including TEPI, PRINTE, Joint i3+3, BOIN-ET, STEIN, uTPI, and BOIN12, in addition to the well-known model-based EffTox design, using comprehensive numerical simulations. To ensure an unbiased comparison, we generated 10,000 dosing scenarios using a random scenario generation algorithm for each predetermined OBD location. We thoroughly assess various performance metrics, such as the selection percentages, average patient allocation to OBD, and overdose percentages across the eight designs. Based on these assessments, we offer design recommendations tailored to different objectives, sample sizes, and starting dose locations.

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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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