Blinded independent central reviews: The FDA weighs in

R. Walovitch
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Abstract

Abstract The FDA has recently issued a draft Guidance Standard for Clinical Trial Imaging Endpoints, which focuses on how to perform registration trials with imaging as an end-point or using imaging to determine patient eligibility. Leading up to the release of the guidance document, a major question was how the FDA viewed the value proposition of a blinded independent central review (BICR) of imaging data. The FDA states that a BICR is recommended in situations where clinical site image interpretation is variable and results of image measurements are important for eligibility determination, safety and/or efficacy end-points. This recommendation is based on the agency’s assertion that the centralized process can better provide verifiable and uniform reader training, as well as ongoing management of reader performance, ensuring that the process is accurate and that bias and variability are minimized. In addition to a review of the guidance document, this article will discuss a decision tree algorithm for determining when and what type of BICR should be performed, the relationship between bias (accuracy), variability and blinding paradigms, along with criteria for using BICRs to interpret non-imaging subjective clinical trial data.
盲法独立中心评价:FDA介入
FDA最近发布了临床试验成像终点指南标准草案,该草案侧重于如何以成像为终点进行注册试验或使用成像来确定患者资格。在指导文件发布之前,一个主要问题是FDA如何看待成像数据的盲法独立中心审查(BICR)的价值主张。FDA指出,在临床部位图像解释是可变的,并且图像测量结果对合格性确定、安全性和/或有效性终点很重要的情况下,推荐使用BICR。这一建议是基于该机构的主张,即集中式流程可以更好地提供可验证和统一的读者培训,以及对读者绩效的持续管理,确保流程准确,并将偏见和可变性降至最低。除了对指导文件的回顾之外,本文还将讨论决策树算法,用于确定何时以及应进行何种类型的BICR,偏差(准确性),可变性和盲化范例之间的关系,以及使用BICR解释非成像主观临床试验数据的标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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