Center for Data Science, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama, 236-0027, Japan.
Department of Clinical Research, National Center for Global Health and Medicine, Tokyo, Japan.
Trials. 2021 Nov 8;22(1):788. doi: 10.1186/s13063-021-05763-y.
There are several challenges in designing clinical trials for the treatment of novel infectious diseases, such as COVID-19. In particular, the definition of endpoints related to the severity, time frame, and clinical course remains unclear. Therefore, we conducted a cross-sectional analysis of phase III randomized trials for COVID-19 registered at ClinicalTrials.gov .
We collected the data from ClinicalTrials.gov on March 31, 2021, by specifying the following search conditions under Advanced Search: Condition or disease: (COVID-19) OR (SARS-CoV-2); Study type: Interventional Studies; Study Results: All Studies; Recruitment: Not yet recruiting, Recruiting, Enrolling by invitation, Active, Not recruiting, Suspended, Completed; Sex: All; and Phase: Phase 3. From the downloaded search results, we selected trials that met the following criteria: Primary Purpose: Treatment; Allocation: Randomized. We manually transcribed information not included in the downloaded file, such as Primary Outcome Measures, Secondary Outcome Measures, Time Frame, and Inclusion Criteria. In the analysis, we examined primary and secondary endpoints in trials with severe and non-severe patients, including the types of endpoints, time frame, clinical course, and sample size.
A total of 406 trials were included in the analysis. The median numbers of endpoints in trials with severe and non-severe patients were 9 and 7, respectively. Approximately 25% of the trials used multiple primary endpoints. Regardless of the type of endpoint, the time frames were longer in the trials with severe patients than in the trials with non-severe patients. In the evaluation of the clinical course, worsening was often considered in binary endpoints, and improvement was considered in time-to-event endpoints. The sample size was the largest in clinical trials using binary endpoints.
Endpoints can differ with respect to severity, and the clinical course and time frame are important for defining endpoints. This study provides information that can facilitate the achievement of a consensus for the endpoints in evaluating COVID-19 treatments.
针对新型传染病(如 COVID-19)的治疗进行临床试验设计存在诸多挑战。特别是,与严重程度、时间框架和临床病程相关的终点定义仍不明确。因此,我们对 ClinicalTrials.gov 上注册的 COVID-19 三期随机临床试验进行了横断面分析。
我们于 2021 年 3 月 31 日通过在高级检索中指定以下搜索条件,从 ClinicalTrials.gov 中收集数据:条件或疾病:(COVID-19)或(SARS-CoV-2);研究类型:干预性研究;研究结果:所有研究;招募:尚未招募,招募,受邀招募,进行中,尚未招募,暂停,完成;性别:所有;阶段:三期。从下载的搜索结果中,我们选择了符合以下标准的试验:主要目的:治疗;分配:随机。我们手动转录了下载文件中未包含的信息,如主要终点、次要终点、时间框架和纳入标准。在分析中,我们检查了严重和非严重患者试验中的主要和次要终点,包括终点类型、时间框架、临床病程和样本量。
共有 406 项试验纳入分析。严重和非严重患者试验的终点中位数分别为 9 和 7。约 25%的试验使用了多个主要终点。无论终点类型如何,严重患者试验的时间框架都长于非严重患者试验。在临床病程评估中,恶化通常在二分类终点中考虑,而在生存时间终点中考虑改善。使用二分类终点的临床试验样本量最大。
终点可能因严重程度而异,临床病程和时间框架对于定义终点很重要。本研究提供了有助于就 COVID-19 治疗评估达成终点共识的信息。