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Safety Assessment Versus Efficacy Assessment

机译:安全评估与疗效评估

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Many statistical methods have been developed that focus primarily on efficacy. Safety evaluation frequently involves many additional considerations. Randomized controlled trials, especially later phase 3 trials, are infrequently designed based on safety outcomes. Most of these trials are designed based on efficacy outcomes, and therefore have limited power to detect important differences in safety outcomes. Recently, there have been calls to design trials with sufficient power to address known safety concerns. When prevention trials introduce an experimental preventive intervention (e.g., a vaccine) to an otherwise healthy (although at-risk) population, safety considerations can substantially affect the benefit:risk ratio and thus the utility and acceptability of the intervention. Observation of safety outcomes is often less controlled than for efficacy outcomes, particularly for safety concerns that emerge during the course of the trial. When either safety or efficacy outcomes are missing, specific assumptions are required for analysis (e.g., missing completely at random, MCAR), but often these assumptions may not apply. The statistical methods that rely on these assumptions have largely been developed with a focus on efficacy outcomes. Illustrative examples, including meta-analyses, will be presented and the underdeveloped areas highlighted.
机译:许多统计方法已经开发出主要侧重功效。安全性评价往往涉及许多额外的考虑。随机对照试验,尤其是后3期临床试验的基础上,安全性结果不常设计。大多数这些试验都是基于疗效结果设计的,因此具有有限的权力来检测安全成果的重要差异。最近,有人呼吁用足够的功率试验设计,以解决已知的安全问题。当预防试验介绍的实验预防性干预(例如,疫苗)以另外的健康(虽然有风险的)人群中,安全性考虑可以显着影响的好处:风险比,因此实用性和可接受性干预。安全结果的观察往往是小于疗效结果的控制,特别是对安全问题的审判过程中所出现。当任一安全性或有效性的结果丢失,需要用于分析特定假设(例如,丢失的完全随机的,MCAR),但往往这些假设可能不适用。依靠这些假设的统计方法基本上都被开发为重点的疗效结果。说明性的例子,包括荟萃分析,将介绍和不发达地区突出。

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