数据质量
临床试验
计算机科学
数据挖掘
食品药品监督管理局
医学物理学
统计
医学
数据科学
数学
病理
工程类
公制(单位)
运营管理
作者
Xiaofeng Wang,Paul Schuette,Matilde Kam
标识
DOI:10.1080/10543406.2024.2330210
摘要
The U.S. Food and Drug Administration (FDA) has broadly supported quality by design initiatives for clinical trials - including monitoring and data validation - by releasing two related guidance documents (FDA 2013 and 2019). Centralized statistical monitoring (CSM) can be a component of a quality by design process. In this article, we describe our experience with a CSM platform as part of a Cooperative Research and Development Agreement between CluePoints and FDA. This agreement's approach to CSM is based on many statistical tests performed on all relevant subject-level data submitted to identify outlying sites. An overall data inconsistency score is calculated to assess the inconsistency of data from one site compared to data from all sites. Sites are ranked by the data inconsistency score (
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