Discrepancies in reported results between trial registries and journal articles for AI clinical research.

IF 10 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL EClinicalMedicine Pub Date : 2025-01-20 eCollection Date: 2025-02-01 DOI:10.1016/j.eclinm.2024.103066
Zixuan He, Lan Yang, Xiaofan Li, Jian Du
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Abstract

Background: Complete and unbiased reporting of clinical trial results is essential for evaluating medical advances, yet publication bias and reporting discrepancies in research on the clinical application of artificial intelligence (AI) remain unknown.

Methods: We conducted a comprehensive search of research publications and clinical trial registries focused on the application of AI in healthcare. Our search included publications in Dimensions.ai and pre-registered records from ClinicalTrials.gov and the EU Clinical Trials Registry before 31 December 2023. We linked registered trials to their corresponding publications, analysed the registration, reporting and different dissemination patterns of results, identified discrepancies between clinical trial registries and published literature, and assessed the use of these results in secondary research.

Findings: We identified 28,248 publications related to the use of AI in clinical settings and found 1863 publications that included a clinical trial registration ID. The clinical trial registry search identified 3710 trials evaluating the use of AI in clinical settings, of which 1106 trials are completed, yet only 101 trials have published results. By linking the trials to their corresponding publications, we found that 26 trials had results available from both registries and publications. There were more results in trial registries than in articles, but researchers showed a clear preference for rapid dissemination of results through peer-reviewed articles (37.6% published within one year) over trial registries (15.8%). Discrepancies and omissions of results were common, and no complete agreement was observed between the two sources. Selective reporting of publications occurred in 53.6% of cases, and the underestimation of the incidence of adverse events is alarming.

Interpretation: This research uncovers concerns with the registration and reporting of AI clinical trial results. While trial registries and publications serve distinct yet complementary roles in disseminating research findings, discrepancies between them may undermine the reliability of the evidence. We emphasise adherence to guidelines that promote transparency and standardisation of reporting, especially for investigator-initiated trials (IITs).

Funding: The authors declare no source of funding.

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人工智能临床研究的试验注册和期刊文章之间报告结果的差异。
背景:临床试验结果的完整和公正报告对于评估医学进步至关重要,但人工智能(AI)临床应用研究的发表偏倚和报告差异仍然未知。方法:我们对人工智能在医疗保健中的应用的研究出版物和临床试验注册进行了全面检索。我们的搜索包括《维度》中的出版物。ai和2023年12月31日前从ClinicalTrials.gov和EU临床试验注册中心预注册的记录。我们将注册的试验与其相应的出版物联系起来,分析了结果的注册、报告和不同的传播模式,确定了临床试验注册和已发表文献之间的差异,并评估了这些结果在二级研究中的使用情况。研究结果:我们确定了28,248篇与临床环境中使用人工智能相关的出版物,并发现1863篇出版物包含临床试验注册ID。临床试验注册表检索确定了3710项评估人工智能在临床环境中使用的试验,其中1106项试验已经完成,但只有101项试验发表了结果。通过将试验与其相应的出版物联系起来,我们发现26项试验的结果可从注册库和出版物中获得。试验注册的结果多于文章,但研究人员明显倾向于通过同行评议的文章(一年内发表37.6%)快速传播结果,而不是通过试验注册(15.8%)。结果的差异和遗漏是常见的,并且在两个来源之间没有观察到完全一致。选择性报道出版物的病例占53.6%,对不良事件发生率的低估令人震惊。解释:本研究揭示了对人工智能临床试验结果注册和报告的关注。虽然试验登记和出版物在传播研究结果方面发挥着独特而互补的作用,但它们之间的差异可能会破坏证据的可靠性。我们强调遵守促进报告透明度和标准化的准则,特别是在研究者发起的试验(iit)中。资金来源:作者声明没有资金来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
EClinicalMedicine
EClinicalMedicine Medicine-Medicine (all)
CiteScore
18.90
自引率
1.30%
发文量
506
审稿时长
22 days
期刊介绍: eClinicalMedicine is a gold open-access clinical journal designed to support frontline health professionals in addressing the complex and rapid health transitions affecting societies globally. The journal aims to assist practitioners in overcoming healthcare challenges across diverse communities, spanning diagnosis, treatment, prevention, and health promotion. Integrating disciplines from various specialties and life stages, it seeks to enhance health systems as fundamental institutions within societies. With a forward-thinking approach, eClinicalMedicine aims to redefine the future of healthcare.
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