可解释性
可靠性(半导体)
风险分析(工程)
质量(理念)
监管科学
精算学
业务
计算机科学
医学
量子力学
认识论
机器学习
物理
哲学
病理
功率(物理)
作者
Lilly Q. Yue,Gregory Campbell,Nelson Lu,Yunling Xu,Bram Zuckerman
标识
DOI:10.1080/10543406.2016.1226336
摘要
Regulatory decisions are made based on the assessment of risk and benefit of medical devices at the time of pre-market approval and subsequently, when post-market risk-benefit balance needs reevaluation. Such assessments depend on scientific evidence obtained from pre-market studies, post-approval studies, post-market surveillance studies, patient perspective information, as well as other real world data such as national and international registries. Such registries provide real world evidence and are playing a more and more important role in enhancing the safety and effectiveness evaluation of medical devices. While these registries provide large quantities of data reflecting real world practice and can potentially reduce the cost of clinical trials, challenges arise concerning (1) data quality adequate for regulatory decision-making, (2) bias introduced at every stage and aspect of study, (3) scientific validity of study designs, and (4) reliability and interpretability of study results. This article will discuss related statistical and regulatory challenges and opportunities with examples encountered in medical device regulatory reviews.
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