将外部真实世界数据(RWD)纳入确认性适应设计。

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Junjing Lin, Jianchang Lin
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引用次数: 0

摘要

适应性设计,如分组序列设计(以及具有附加适应性特征的设计)或适应性平台试验,一直是未满足医疗需求试验中最重要的有效设计策略,尤其是在从全球各地获取证据方面。这种设计允许进行临时决策,并在必要时对研究设计进行调整,同时保持研究的完整性和操作特性。然而,由于竞争日趋激烈,而且人们希望更快地为患者提供有效治疗,因此,要想进一步推动药物研发工作走上更高效的道路,就必须对已有的功能设计进行创新。实现这一目标的方法之一是在适应性设计中利用外部真实世界数据(RWD),为中期或最终决策提供支持。在本文中,我们提出了一个将外部真实世界数据纳入自适应设计的新框架,以改进中期和/或最终分析决策。在这一框架内,研究人员可以在保持客观性和控制 I 类误差的前提下,预设决策过程,选择借用时机和借用量。本文提供了各种情况下的模拟研究,以描述中期/最终决策的功率、I 型误差和其他性能指标。非小细胞肺癌案例研究用于说明拟议的设计框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incorporating external real-world data (RWD) in confirmatory adaptive design.

Adaptive designs, such as group sequential designs (and the ones with additional adaptive features) or adaptive platform trials, have been quintessential efficient design strategies in trials of unmet medical needs, especially for generating evidence from global regions. Such designs allow interim decision making and making adjustment to study design when necessary, meanwhile maintaining study integrity and operating characteristics. However, driven by the heightened competitive landscape and the desire to bring effective treatment to patients faster, innovation in the already functional designs is still germane to further propel drug development to a more efficient path. One way to achieve this is by leveraging external real-world data (RWD) in the adaptive designs to support interim or final decision making. In this paper, we propose a novel framework of incorporating external RWD in adaptive design to improve interim and/or final analysis decision making. Within this framework, researchers can prespecify the decision process and choose the timing and amount of borrowing while maintaining objectivity and controlling of type I error. Simulation studies in various scenarios are provided to describe power, type I error, and other performance metrics for interim/final decision making. A case study in non-small cell lung cancer is used for illustration on proposed design framework.

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来源期刊
Journal of Biopharmaceutical Statistics
Journal of Biopharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.50
自引率
18.20%
发文量
71
审稿时长
6-12 weeks
期刊介绍: The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers: Drug, device, and biological research and development; Drug screening and drug design; Assessment of pharmacological activity; Pharmaceutical formulation and scale-up; Preclinical safety assessment; Bioavailability, bioequivalence, and pharmacokinetics; Phase, I, II, and III clinical development including complex innovative designs; Premarket approval assessment of clinical safety; Postmarketing surveillance; Big data and artificial intelligence and applications.
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