论贝叶斯逻辑回归法在肿瘤剂量测定研究中的相对保守性。

IF 1.3 4区医学 Q4 PHARMACOLOGY & PHARMACY

Pharmaceutical Statistics Pub Date : 2024-07-01 Epub Date: 2024-02-05 DOI:10.1002/pst.2364

Cheng-Han Yang, Guanghui Cheng, Ruitao Lin

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引用次数: 0

摘要

贝叶斯逻辑回归法（BLRM）是在肿瘤学 I 期研究中寻找最大耐受剂量时广泛采用的一种灵活设计。然而，由于使用了超剂量控制规则，BLRM 设计在文献中被批评为过于保守。最近，《医学统计学》（Statistics in Medicine）杂志发表了一篇题为 "在肿瘤学剂量探索研究中提高带有总体控制的贝叶斯逻辑回归模型的性能 "的讨论文章，针对标准 BLRM 设计的 "过度保守性 "提出了一种总体控制规则。在这篇短文中，我们讨论了标准 BLRM 设计的相对保守性，并提出了进一步提高其性能的剂量切换规则。

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On the relative conservativeness of Bayesian logistic regression method in oncology dose-finding studies.

The Bayesian logistic regression method (BLRM) is a widely adopted and flexible design for finding the maximum tolerated dose in oncology phase I studies. However, the BLRM design has been criticized in the literature for being overly conservative due to the use of the overdose control rule. Recently, a discussion paper titled "Improving the performance of Bayesian logistic regression model with overall control in oncology dose-finding studies" in Statistics in Medicine has proposed an overall control rule to address the "excessive conservativeness" of the standard BLRM design. In this short communication, we discuss the relative conservativeness of the standard BLRM design and also suggest a dose-switching rule to further enhance its performance.

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来源期刊

Pharmaceutical Statistics 医学-统计学与概率论

CiteScore

2.70

自引率

6.70%

发文量

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.