Wilkinson Jack, Heal Calvin, Antoniou George A, Flemyng Ella, Avenell Alison, Barbour Virginia, Bordewijk Esmee M, Brown Nicholas J L, Clarke Mike, Dumville Jo, Grohmann Steph, Gurrin Lyle C, Hayden Jill A, Hunter Kylie E, Lam Emily, Lasserson Toby, Li Tianjing, Lensen Sarah, Liu Jianping, Lundh Andreas, Meyerowitz-Katz Gideon, Mol Ben W, O'Connell Neil E, Parker Lisa, Redman Barbara, Seidler Anna Lene, Sheldrick Kyle, Sydenham Emma, Dahly Darren L, van Wely Madelon, Bero Lisa, Kirkham Jamie J
Centre for Biostatistics, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Centre for Biostatistics, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
J Clin Epidemiol. 2024 Nov;175:111512. doi: 10.1016/j.jclinepi.2024.111512. Epub 2024 Aug 31.
Randomized controlled trials (RCTs) inform health-care decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesize all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INveStigating ProblEmatic Clinical Trials in Systematic Reviews (INSPECT-SR) project is developing a tool to identify problematic RCTs in systematic reviews of health care-related interventions. The tool will guide the user through a series of 'checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion.
We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorized these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list.
Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool.
A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.
随机对照试验（RCTs）为医疗保健决策提供依据。遗憾的是，一些已发表的随机对照试验包含虚假数据，还有一些似乎是完全编造的。进行系统评价旨在识别和综合针对特定主题开展的所有随机对照试验。这意味着这些“问题研究”中的任何一项都可能被纳入，但目前尚无公认的识别方法。“在系统评价中调查有问题的临床试验（INSPECT-SR）”项目正在开发一种工具，用于在对医疗保健相关干预措施的系统评价中识别有问题的随机对照试验。该工具将引导用户进行一系列“检查”，以确定一项研究的真实性。开发过程的首要目标是汇编一份全面的检查清单以供考虑纳入。
我们汇编了一份用于评估研究真实性的初始检查清单，不限于随机对照试验，并将其分为五个领域：检查论文中的结果；检查研究团队；检查实施、管理和透明度；检查文本及发表细节；检查个体参与者数据。我们将此清单作为在线调查实施，并通过专业网络和在线论坛邀请具有评估潜在问题研究专业知识和经验的人员参与。邀请参与者对清单上的检查提供反馈，并要求他们描述所知的清单中未列出的任何其他检查。
来自五大洲16个国家的71名参与者对102项检查的初始清单提供了广泛反馈。在五个领域共提出了14项新检查，并对初始清单上的检查措辞提出了建议。构建了一份更新的检查清单，包括116项检查。许多参与者表示对统计检查不熟悉，并强调了该工具可行性的重要性。
已编制了一份全面的可信度检查清单。将对这些检查进行评估，以确定哪些应纳入INSPECT-SR工具。
