Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy.
Meta-Research Innovation Center at Stanford, Stanford University, Stanford, California.
JAMA Netw Open. 2023 Nov 1;6(11):e2343425. doi: 10.1001/jamanetworkopen.2023.43425.
IMPORTANCE: Industry involvement is prominent in influential clinical trials, and commitments to transparency of trials are highly variable. OBJECTIVE: To evaluate the modes of industry involvement and the transparency features of the most cited recent clinical trials across medicine. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study was a meta-research assessment including randomized and nonrandomized clinical trials published in 2019 or later. The 600 trials of any type of disease or setting that attracted highest number of citations in Scopus as of December 2022 were selected for analysis. Data were analyzed from March to September 2023. MAIN OUTCOMES AND MEASURES: Outcomes of interest were industry involvement (sponsor, author, and analyst) and transparency (protocols, statistical analysis plans, and data and code availability). RESULTS: Among 600 trials with a median (IQR) sample size of 415 (124-1046) participants assessed, 409 (68.2%) had industry funding and 303 (50.5%) were exclusively industry-funded. A total of 354 trials (59.0%) had industry authors, with 280 trials (46.6%) involving industry analysts and 125 trials (20.8%) analyzed exclusively by industry analysts. Among industry-funded trials, 364 (89.0%) reached conclusions favoring the sponsor. Most trials (478 trials [79.7%]) provided a data availability statement, and most indicated intention to share the data, but only 16 trials (2.7%) had data already readily available to others. More than three-quarters of trials had full protocols (482 trials [82.0%]) or statistical analysis plans (446 trials [74.3%]) available, but only 27 trials (4.5%) explicitly mentioned sharing analysis code (8 readily available; 19 on request). Randomized trials were more likely than nonrandomized studies to involve only industry analysts (107 trials [22.9%] vs 18 trials [13.6%]; P = .02) and to have full protocols (405 studies [86.5%] vs 87 studies [65.9%]; P < .001) and statistical analysis plans (373 studies [79.7%] vs 73 studies [55.3%]; P < .001) available. Almost all nonrandomized industry-funded studies (90 of 92 studies [97.8%]) favored the sponsor. Among industry-funded trials, exclusive industry funding (odds ratio, 2.9; 95% CI, 1.5-5.4) and industry-affiliated authors (odds ratio, 2.9; 95% CI, 1.5-5.6) were associated with favorable conclusions for the sponsor. CONCLUSIONS AND RELEVANCE: This cross-sectional study illustrates how industry involvement in the most influential clinical trials was prominent not only for funding, but also authorship and provision of analysts and was associated with conclusions favoring the sponsor. While most influential trials reported that they planned to share data and make both protocols and statistical analysis plans available, raw data and code were rarely readily available.
重要性:业界参与在有影响力的临床试验中很突出,而对试验透明度的承诺则差异很大。
目的:评估医学领域最近最具影响力的临床试验中行业参与的模式和透明度特征。
设计、环境和参与者:这是一项元研究评估,包括 2019 年或之后发表的随机和非随机临床试验。从截至 2022 年 12 月在 Scopus 中引用次数最多的 600 种类型的疾病或设置的试验中选择进行分析。数据于 2023 年 3 月至 9 月进行分析。
主要结果和措施:感兴趣的结果是行业参与(赞助商、作者和分析师)和透明度(方案、统计分析计划以及数据和代码可用性)。
结果:在评估的 600 项具有中位数(IQR)样本量为 415(124-1046)参与者的试验中,409 项(68.2%)有行业资助,303 项(50.5%)是独家行业资助。共有 354 项试验(59.0%)有行业作者,其中 280 项试验(46.6%)涉及行业分析师,125 项试验(20.8%)由行业分析师独家分析。在行业资助的试验中,364 项(89.0%)得出了有利于赞助商的结论。大多数试验(478 项 [79.7%])提供了数据可用性声明,并表示打算共享数据,但只有 16 项试验(2.7%)已经有数据可供他人使用。超过四分之三的试验有完整的方案(482 项 [82.0%])或统计分析计划(446 项 [74.3%]),但只有 27 项试验(4.5%)明确提到了共享分析代码(8 项随时可用;19 项按需提供)。随机试验比非随机研究更有可能只涉及行业分析师(107 项 [22.9%] 与 18 项 [13.6%];P = .02),并且更有可能有完整的方案(405 项 [86.5%] 与 87 项 [65.9%];P < .001)和统计分析计划(373 项 [79.7%] 与 73 项 [55.3%];P < .001)。几乎所有非随机的行业资助研究(92 项中的 90 项 [97.8%])都支持赞助商。在行业资助的试验中,独家行业资助(比值比,2.9;95%CI,1.5-5.4)和行业关联作者(比值比,2.9;95%CI,1.5-5.6)与赞助商有利的结论相关。
结论和相关性:这项横断面研究表明,在最具影响力的临床试验中,行业参与不仅表现在资助方面,还表现在作者和分析师的提供方面,并且与支持赞助商的结论有关。虽然大多数有影响力的试验报告称他们计划共享数据并提供方案和统计分析计划,但很少有原始数据和代码随时可用。
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