BF-BOIN-ET:利用效能和毒性结果进行剂量优化的回填贝叶斯最优间隔设计。

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Kentaro Takeda, Jing Zhu, Akihiro Hirakawa
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引用次数: 0

摘要

新型抗癌药物的剂量发现试验的主要目的是确定最佳剂量(OD),定义为在不可预测的剂量-毒性和剂量-功效关系中具有足够疗效的耐受剂量。FDA的Optimus项目改革了剂量优化的范例,并建议在有希望的剂量水平上进行剂量寻找试验,比较多个剂量来产生这些额外的数据。在药物的功效并不总是随剂量水平而增加的情况下,回填是有帮助的。在试验继续探索更高剂量的同时,通过回填低剂量的患者,可以获得这些剂量的更多信息。本文提出了一种贝叶斯最佳间隔设计,使用疗效和毒性结果,允许在剂量寻找试验期间以较低剂量回填患者,同时优先考虑剂量递增队列以探索更高剂量。仿真研究表明,与其他设计相比,所提出的BF-BOIN-ET设计在正确OD选择百分比、减少样本量和缩短各种现实环境下的试验时间方面具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BF-BOIN-ET: A Backfill Bayesian Optimal Interval Design Using Efficacy and Toxicity Outcomes for Dose Optimization.

The primary purpose of a dose-finding trial for novel anticancer agents is to identify an optimal dose (OD), defined as the tolerable dose that has adequate efficacy in unpredictable dose-toxicity and dose-efficacy relationships. The FDA project Optimus reforms the paradigm of dose optimization and recommends that dose-finding trials compare multiple doses to generate these additional data at promising dose levels. The backfill is helpful in settings where the efficacy of a drug does not always increase with the dose level. More information is available at these doses by backfilling patients at lower doses while the trial continues to explore higher doses. This paper proposes a Bayesian optimal interval design using efficacy and toxicity outcomes that allows patients to be backfilled at lower doses during a dose-finding trial while prioritizing the dose-escalation cohort to explore a higher dose. A simulation study shows that the proposed design, the BF-BOIN-ET design, has advantages compared to the other designs in terms of the percentage of correct OD selection, reducing the sample size, and shortening the duration of the trial in various realistic settings.

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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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