The Individual Participant Data Integrity Tool for assessing the integrity of randomised trials

IF 5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Research Synthesis Methods Pub Date : 2024-08-13 DOI:10.1002/jrsm.1738
Kylie E. Hunter, Mason Aberoumand, Sol Libesman, James X. Sotiropoulos, Jonathan G. Williams, Jannik Aagerup, Rui Wang, Ben W. Mol, Wentao Li, Angie Barba, Nipun Shrestha, Angela C. Webster, Anna Lene Seidler
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Abstract

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.

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用于评估随机试验完整性的个人参与者数据完整性工具。
人们对研究可信度的担忧与日俱增,这促使人们呼吁对研究的个体参与者数据(IPD)进行仔细检查,但却缺乏如何进行检查的指导。为此,我们开发了 IPD 完整性工具,用于筛查随机对照试验 (RCT) 的完整性问题。该工具的开发过程包括文献综述、咨询专家顾问组、在两项IPD荟萃分析(包括73项IPD试验)中进行试点、在13个存在和不存在已知完整性问题的数据集上进行初步验证,以及进行评估,为迭代改进提供信息。IPD完整性工具包括31个项目(13个研究层面的项目和18个IPD特定项目)。IPD 特定项目尽可能实现自动化,并分为八个领域,包括异常数据模式、基线特征、相关性、日期违规、分配模式、内部和外部不一致性以及数据的可信度。用户根据决策规则将每个项目评定为 "无问题"、"有/少问题 "或 "多/大问题",并记录每个评定的理由。总之,该工具通过确定一项试验是没有问题、有一些问题需要进一步信息,还是有重大问题需要排除在证据综合或发表之外,来指导决策。在我们的初步验证检查中,该工具准确识别了所有五项存在已知诚信问题的研究。IPD完整性工具使用户能够通过检查IPD来评估RCT的完整性。该工具可供证据综合人员、编辑和其他人员使用,以确定一项研究性试验是否值得信赖,从而为政策和实践的证据基础做出贡献。
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来源期刊
Research Synthesis Methods
Research Synthesis Methods MATHEMATICAL & COMPUTATIONAL BIOLOGYMULTID-MULTIDISCIPLINARY SCIENCES
CiteScore
16.90
自引率
3.10%
发文量
75
期刊介绍: Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines. Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines. By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.
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