基于双变量指数向量的贝叶斯预测概率,用于具有二元有效性和安全性终点的单臂 II 期研究。

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Takuya Yoshimoto, Satoru Shinoda, Kouji Yamamoto, Kouji Tahata
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引用次数: 0

摘要

在肿瘤学领域,II 期研究对临床开发计划至关重要,因为这类研究可以确定具有足够活性的强效制剂,以便在随后的 III 期试验中继续开发。传统上,II 期研究是单臂研究,主要终点是短期疗效。然而,药物安全性也是一个重要的考虑因素。在这种多结果设计的背景下,人们开发了基于预测概率的贝叶斯监测策略,以评估临床试验是否能提供足够的证据,从而在预定试验结束时继续进行 III 期研究。因此,我们提出了一种新的简单指数向量来总结现有策略无法捕捉的结果。具体来说,我们定义了治疗潜在效果最差和最有希望的两种情况,然后使用提出的指数向量来衡量两种情况之间的偏差。最后,我们进行了模拟研究,以评估设计的运行特性。结果表明,建议的方法能做出适当的 "去/不去 "临时决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian Predictive Probability Based on a Bivariate Index Vector for Single-Arm Phase II Study With Binary Efficacy and Safety Endpoints.

In oncology, Phase II studies are crucial for clinical development plans as such studies identify potent agents with sufficient activity to continue development in the subsequent Phase III trials. Traditionally, Phase II studies are single-arm studies, with the primary endpoint being short-term treatment efficacy. However, drug safety is also an important consideration. In the context of such multiple-outcome designs, predictive probability-based Bayesian monitoring strategies have been developed to assess whether a clinical trial will provide enough evidence to continue with a Phase III study at the scheduled end of the trial. Therefore, we propose a new simple index vector to summarize the results that cannot be captured by existing strategies. Specifically, we define the worst and most promising situations for the potential effect of a treatment, then use the proposed index vector to measure the deviation between the two situations. Finally, simulation studies are performed to evaluate the operating characteristics of the design. The obtained results demonstrate that the proposed method makes appropriate interim go/no-go decisions.

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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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