关于新临床预测模型的出版物数量:一个图书统计审查
Banafsheh Arshi1,2, Laure Wynants1,3,4, Eline Rijnhart1
1Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Peter Debyeplein 1, P.O. Box 616, Maastricht, 6200 MD, The Netherlands, 31 433882821.
JMIR medical informatics
|July 4, 2025
概括
发表的临床预测模型 (CPM) 的数量迅速增加,到2024年将有近25万篇文章. 未来的研究应该优先考虑验证现有的CPM,而不是开发新的CPM.
科学领域:
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 人们越来越担心临床预测模型 (CPM) 在科学文献中的普及.
- 预测研究增加的确切程度尚不清楚.
- 了解CPM开发的数量对于评估研究趋势和潜在的浪费至关重要.
研究的目的:
- 估计所有医学学科中专注于CPM开发的出版物的总和年度数量.
- 为预测模型研究的增长轨迹提供全面的概述.
- 为未来关于CPM的研究优先事项提供信息.
主要方法:
- 在PubMed和Embase (1995-2020) 的系统文献搜索中,使用了用于预测模型研究的验证策略.
- 包括开发多变量诊断或预后模型的研究,以预测个人级别的健康结果.
- 通过采样,回归分析和推算到1950-2024年,包括非回归模型,估计出版物数量.
主要成果:
- 在1995年至2020年期间,估计有82,772篇基于回归的CPM开发文章发表,2010年后的发展加速.
- 包括非回归模型 (例如,机器学习),总共达到了147,714篇文章.
- 到2024年的推算表明,大约有156,673篇基于回归的文章和248,431篇CPM开发文章.
结论:
- 到2024年,关于CPM发展的近25万篇文章已经发表,持续增长.
- 这些发现突出了在CPM开发方面的大量研究.
- 建议将重点从开发新的CPM转移到验证现有的CPM并评估其临床影响,以减少研究浪费.
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