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随机III期临床试验中假阳性的控制

Control of false positives in randomized phase III clinical trials.

作者信息

Shen Changyu, Liu Ziyue, Xu Huiping, Liu Hai, Yue Cynthia

机构信息

a Department of Biostatistics, School of Medicine, Richard M. Fairbanks School of Public Health , Indiana University , Indianapolis , IN , USA.

b Yale College , CT , USA.

出版信息

J Biopharm Stat. 2017;27(5):719-731. doi: 10.1080/10543406.2016.1222536. Epub 2016 Sep 22.

Abstract

Randomized Phase III clinical trials serve as the gold-standard for the evaluation of the efficacy of a medical intervention. Although research and development in earlier stages together with rigorous statistical examination assure a small probability of false positive for a given trial, it is unclear how many false positives were generated from the large number of randomized Phase III trials from the biopharmaceutical industry in the United States. The proportion of comparisons in Phase III trials where the medical intervention has null or negative efficacy, or proportion of null or negative (PNN), is at the central position for the estimation and control of the number of false positives. We seek to estimate PNN using a new Bayesian deconvolution method. Using data from clinicaltrials.gov and other data sources, we identified 1393 trials completed in 2008-2012 that meet our study entry criteria, which are dominated by trials on drugs for treatment purpose. Among the 1221 trials with results available on the selected comparisons, 789 (64.6%) show statistically significant superiority of the intervention, with 561 (45.9%) having a two-sided p-value less than 0.001. The PNN is estimated to be no more than 7-9%. Based on the PNN, we estimated that 18-22% of the trials have at least one comparison with null or negative efficacy, leading to an expectation of no more than 6-8 trials with at least one false positive comparison over a 5-year period.

摘要

随机III期临床试验是评估医学干预疗效的金标准。尽管早期的研发工作以及严格的统计检验确保了特定试验出现假阳性的概率较小,但尚不清楚美国生物制药行业大量的随机III期试验产生了多少假阳性结果。III期试验中医疗干预无效或疗效为阴性的比较比例,即无效或阴性比例(PNN),在估计和控制假阳性数量方面处于核心地位。我们试图使用一种新的贝叶斯反卷积方法来估计PNN。利用来自clinicaltrials.gov和其他数据源的数据,我们确定了2008 - 2012年完成的1393项符合我们研究纳入标准的试验,这些试验主要是关于治疗目的药物的试验。在1221项有选定比较结果的试验中,789项(64.6%)显示干预具有统计学上的显著优势,其中561项(45.9%)的双侧p值小于0.001。估计PNN不超过7 - 9%。基于PNN,我们估计18 - 22%的试验至少有一项比较的疗效为无效或阴性,这意味着在5年期间预计出现至少一项假阳性比较的试验不超过6 - 8项。

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