评估临床研究中极值的影响-一种潜在变量方法

Zhengning Lin
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引用次数: 0

摘要

在许多肺动脉高压(PAH)和神经肌肉疾病临床试验中,使用6分钟步行距离(6MWD)测试评估运动能力的变化一直是主要终点。然而,在疗效良好的安慰剂对照研究中,6MWD分析的主要终点观察到较大的功率损失。其中一项研究是2015年drisapersen的新药申请(NDA)。drisapersen NDA包括3项安慰剂对照研究,以证明Duchenne肌营养不良症的疗效,这是一种罕见的进行性神经肌肉疾病,对年轻的男孩来说最终是致命的。6MWD的变化是主要终点。虽然两个较小的概念验证试点研究显示了一致的治疗差异,但较大且唯一有效的安慰剂对照研究未能发现治疗差异。基于假设数据正态分布的混合模型重复测量(MMRM)参数化模型,由于标准偏差从计划的55 m增加到实际的87 m,使得预先计划的初步分析的统计能力从计划的90%降低到只有53%。
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Assessing the impact of extreme values in clinical studies−a latent variable approach
Assessment of change in exercise capacity using the 6-minute walk distance (6MWD) tests has been the primary endpoint in many pulmonary arterial hypertension (PAH) and neuromuscular disorder clinical trials. However, large power losses were observed in the primary endpoint of 6MWD analysis in well-powered placebo-controlled studies. One study is a new drug application (NDA) of drisapersen in 2015. The drisapersen NDA included 3 placebo-controlled studies to demonstrate efficacy for Duchenne Muscular Dystrophy, a rare progressive neuromuscular disorder that is ultimately fatal for boys at a young age. Change in 6MWD is the primary endpoint. While the two smaller proof-of-concept pilot studies showed consistent treatment differences, the larger and only well-powered placebo-controlled study failed to detect a treatment difference. The statistical power of the pre-planned primary analysis was reduced from the planned 90% to only 53% as a result of the increased standard deviation from the planned 55 meters to the actual 87 meters, based on the parametric model of mixed model repeated measurement (MMRM) assuming normal data distribution.
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