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Abstract：
BACKGROUND: Faced with the high cost and limited efficiency of classical randomized controlled trials, researchers are increasingly applying adaptive designs to speed up the development of new drugs. However, the application of adaptive design to drug randomized controlled trials (RCTs) and whether the reporting is adequate are unclear. Thus, this study aimed to summarize the epidemiological characteristics of the relevant trials and assess their reporting quality by the Adaptive designs CONSORT Extension (ACE) checklist.
METHODS: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov from inception to January 2020. We included drug RCTs that explicitly claimed to be adaptive trials or used any type of adaptative design. We extracted the epidemiological characteristics of included studies to summarize their adaptive design application. We assessed the reporting quality of the trials by Adaptive designs CONSORT Extension (ACE) checklist. Univariable and multivariable linear regression models were used to the association of four prespecified factors with the quality of reporting.
RESULTS: Our survey included 108 adaptive trials. We found that adaptive design has been increasingly applied over the years, and was commonly used in phase II trials (n = 45, 41.7%). The primary reasons for using adaptive design were to speed the trial and facilitate decision-making (n = 24, 22.2%), maximize the benefit of participants (n = 21, 19.4%), and reduce the total sample size (n = 15, 13.9%). Group sequential design (n = 63, 58.3%) was the most frequently applied method, followed by adaptive randomization design (n = 26, 24.1%), and adaptive dose-finding design (n = 24, 22.2%). The proportion of adherence to the ACE checklist of 26 topics ranged from 7.4 to 99.1%, with eight topics being adequately reported (i.e., level of adherence ≥ 80%), and eight others being poorly reported (i.e., level of adherence ≤ 30%). In addition, among the seven items specific for adaptive trials, three were poorly reported: accessibility to statistical analysis plan (n = 8, 7.4%), measures for confidentiality (n = 14, 13.0%), and assessments of similarity between interim stages (n = 25, 23.1%). The mean score of the ACE checklist was 13.9 (standard deviation [SD], 3.5) out of 26. According to our multivariable regression analysis, later published trials (estimated β = 0.14, p < 0.01) and the multicenter trials (estimated β = 2.22, p < 0.01) were associated with better reporting.
CONCLUSIONS: Adaptive design has shown an increasing use over the years, and was primarily applied to early phase drug trials. However, the reporting quality of adaptive trials is suboptimal, and substantial efforts are needed to improve the reporting.
METHODS: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov from inception to January 2020. We included drug RCTs that explicitly claimed to be adaptive trials or used any type of adaptative design. We extracted the epidemiological characteristics of included studies to summarize their adaptive design application. We assessed the reporting quality of the trials by Adaptive designs CONSORT Extension (ACE) checklist. Univariable and multivariable linear regression models were used to the association of four prespecified factors with the quality of reporting.
RESULTS: Our survey included 108 adaptive trials. We found that adaptive design has been increasingly applied over the years, and was commonly used in phase II trials (n = 45, 41.7%). The primary reasons for using adaptive design were to speed the trial and facilitate decision-making (n = 24, 22.2%), maximize the benefit of participants (n = 21, 19.4%), and reduce the total sample size (n = 15, 13.9%). Group sequential design (n = 63, 58.3%) was the most frequently applied method, followed by adaptive randomization design (n = 26, 24.1%), and adaptive dose-finding design (n = 24, 22.2%). The proportion of adherence to the ACE checklist of 26 topics ranged from 7.4 to 99.1%, with eight topics being adequately reported (i.e., level of adherence ≥ 80%), and eight others being poorly reported (i.e., level of adherence ≤ 30%). In addition, among the seven items specific for adaptive trials, three were poorly reported: accessibility to statistical analysis plan (n = 8, 7.4%), measures for confidentiality (n = 14, 13.0%), and assessments of similarity between interim stages (n = 25, 23.1%). The mean score of the ACE checklist was 13.9 (standard deviation [SD], 3.5) out of 26. According to our multivariable regression analysis, later published trials (estimated β = 0.14, p < 0.01) and the multicenter trials (estimated β = 2.22, p < 0.01) were associated with better reporting.
CONCLUSIONS: Adaptive design has shown an increasing use over the years, and was primarily applied to early phase drug trials. However, the reporting quality of adaptive trials is suboptimal, and substantial efforts are needed to improve the reporting.
摘要：
背景：面对经典随机对照试验的高成本和有限的效率，研究人员越来越多地应用自适应设计来加快新药的开发。然而,适应性设计在药物随机对照试验(RCT)中的应用以及报告是否充分尚不清楚.因此，本研究旨在总结相关试验的流行病学特征,并通过自适应设计CONSORT扩展(ACE)检查表评估其报告质量.
方法：我们搜索了MEDLINE，EMBASE,Cochrane中央对照试验登记册（CENTRAL）和ClinicalTrials.gov从开始到2020年1月。我们纳入了明确宣称为适应性试验或使用任何类型适应性设计的药物随机对照试验。我们提取了纳入研究的流行病学特征，以总结其适应性设计应用。我们通过自适应设计CONSORTExtension（ACE）检查表评估了试验的报告质量。使用单变量和多变量线性回归模型将四个预设因素与报告质量相关联。
结果：我们的调查包括108项适应性试验。我们发现自适应设计多年来得到越来越多的应用，并常用于II期试验（n=45，41.7%）。使用自适应设计的主要原因是加快试验速度和促进决策（n=24，22.2%），最大化参与者的利益(n=21，19.4%)，并减少总样本量(n=15，13.9%)。组序贯设计(n=63，58.3%)是最常用的方法，其次是自适应随机化设计(n=26，24.1%)，和适应性剂量发现设计（n=24，22.2%）。26个主题的ACE检查表的遵守比例从7.4％到99.1％不等，有八个主题得到充分报告(即，依从性水平≥80%)，和其他八个报告不佳(即，粘附水平≤30%)。此外,在适应性试验的七个项目中，三个报告不佳：统计分析计划的可及性(n=8，7.4%)，保密措施(n=14，13.0%)，和评估中间阶段之间的相似性(n=25，23.1%)。ACE检查表的平均得分为13.9(标准偏差[SD]，3.5）中的26个。根据我们的多元回归分析，后来发表的试验(估计β=0.14,p<0.01)和多中心试验(估计β=2.22,p<0.01)与更好的报告相关.
结论：多年来，自适应设计的使用越来越多，主要应用于早期药物试验。然而,适应性试验的报告质量欠佳，需要作出巨大努力来改进报告。
方法：我们搜索了MEDLINE，EMBASE,Cochrane中央对照试验登记册（CENTRAL）和ClinicalTrials.gov从开始到2020年1月。我们纳入了明确宣称为适应性试验或使用任何类型适应性设计的药物随机对照试验。我们提取了纳入研究的流行病学特征，以总结其适应性设计应用。我们通过自适应设计CONSORTExtension（ACE）检查表评估了试验的报告质量。使用单变量和多变量线性回归模型将四个预设因素与报告质量相关联。
结果：我们的调查包括108项适应性试验。我们发现自适应设计多年来得到越来越多的应用，并常用于II期试验（n=45，41.7%）。使用自适应设计的主要原因是加快试验速度和促进决策（n=24，22.2%），最大化参与者的利益(n=21，19.4%)，并减少总样本量(n=15，13.9%)。组序贯设计(n=63，58.3%)是最常用的方法，其次是自适应随机化设计(n=26，24.1%)，和适应性剂量发现设计（n=24，22.2%）。26个主题的ACE检查表的遵守比例从7.4％到99.1％不等，有八个主题得到充分报告(即，依从性水平≥80%)，和其他八个报告不佳(即，粘附水平≤30%)。此外,在适应性试验的七个项目中，三个报告不佳：统计分析计划的可及性(n=8，7.4%)，保密措施(n=14，13.0%)，和评估中间阶段之间的相似性(n=25，23.1%)。ACE检查表的平均得分为13.9(标准偏差[SD]，3.5）中的26个。根据我们的多元回归分析，后来发表的试验(估计β=0.14,p<0.01)和多中心试验(估计β=2.22,p<0.01)与更好的报告相关.
结论：多年来，自适应设计的使用越来越多，主要应用于早期药物试验。然而,适应性试验的报告质量欠佳，需要作出巨大努力来改进报告。
