NHMRC Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia.
Department of Obstetrics and Gynaecology, Monash University, Clayton, Victoria, Australia.
Res Synth Methods. 2024 Nov;15(6):917-939. doi: 10.1002/jrsm.1738. Epub 2024 Aug 13.
Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature review, consultation with an expert advisory group, piloting on two IPD meta-analyses (including 73 trials with IPD), preliminary validation on 13 datasets with and without known integrity issues, and evaluation to inform iterative refinements. The IPD Integrity Tool comprises 31 items (13 study-level, 18 IPD-specific). IPD-specific items are automated where possible, and are grouped into eight domains, including unusual data patterns, baseline characteristics, correlations, date violations, patterns of allocation, internal and external inconsistencies, and plausibility of data. Users rate each item as having either no issues, some/minor issue(s), or many/major issue(s) according to decision rules, and justification for each rating is recorded. Overall, the tool guides decision-making by determining whether a trial has no concerns, some concerns requiring further information, or major concerns warranting exclusion from evidence synthesis or publication. In our preliminary validation checks, the tool accurately identified all five studies with known integrity issues. The IPD Integrity Tool enables users to assess the integrity of RCTs via examination of IPD. The tool may be applied by evidence synthesists, editors and others to determine whether an RCT should be considered sufficiently trustworthy to contribute to the evidence base that informs policy and practice.
人们越来越关注研究的可信度,这促使人们呼吁仔细审查研究的个体参与者数据 (IPD),但缺乏对此类审查的指导。为了解决这个问题,我们开发了 IPD 完整性工具来筛选随机对照试验 (RCT) 中的完整性问题。该工具的开发涉及文献回顾、咨询专家咨询小组、对两项 IPD 荟萃分析进行试点(包括 73 项具有 IPD 的试验)、对 13 个具有和不具有已知完整性问题的数据集进行初步验证,并进行评估以提供迭代改进。IPD 完整性工具包括 31 个项目(13 个研究级,18 个 IPD 特定)。尽可能实现 IPD 特定项目的自动化,并将其分为八个领域,包括异常数据模式、基线特征、相关性、日期违规、分配模式、内部和外部不一致以及数据的合理性。用户根据决策规则将每个项目评为无问题、有一些/轻微问题或有很多/主要问题,并记录每个评级的理由。总的来说,该工具通过确定试验是否没有问题、有一些需要进一步信息的问题还是有重大问题需要排除在证据综合或出版之外,来指导决策。在我们的初步验证检查中,该工具准确地识别了所有五篇具有已知完整性问题的研究。IPD 完整性工具使用户能够通过检查 IPD 来评估 RCT 的完整性。该工具可由证据综合者、编辑和其他人员应用,以确定 RCT 是否被认为足够可信,可作为为政策和实践提供信息的证据基础的一部分。