Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review.
Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review.
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DOI：
10.1093/jamia/ocac002
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发表时间：
2022-04-13
影响因子：
6.4
通讯作者：
Rijnbeek, Peter R.
中科院分区：
文献类型：
--
作者：
Yang, Cynthia;Kors, Jan A.;Ioannou, Solomon;John, Luis H.;Markus, Aniek F.;Rekkas, Alexandros;de Ridder, Maria A. J.;Seinen, Tom M.;Williams, Ross D.;Rijnbeek, Peter R.
关键词：
本系统综述旨在进一步深入了解临床预测模型开发和验证的实施和报告。我们专注于评估必要的信息报告，以便其他研究人员进行外部验证。我们搜索了 Embase、Medline、Web-of-Science、Cochrane Library 和 Google Scholar，以确定使用 2009-2019 年期间发布的电子健康记录 (EHR) 数据开发了 1 个或多个多变量预后预测模型的研究。我们确定了 422 项研究，利用 EHR 数据开发了总共 579 个临床预测模型。我们观察到，多年来开发模型的数量急剧增加。同一篇论文中经过外部验证的模型比例保持在 10% 左右。 2009-2019 年期间，对于目标人群和结果定义，为不到 20% 的模型提供了代码列表。对于大约一半使用回归分析开发的模型，最终模型并未完整呈现。总体而言，我们观察到随着时间的推移，临床预测模型开发和验证的实施和报告方面的改进有限。特别是，预测问题的定义往往没有清晰地报告，最终的模型往往没有完整地呈现。仍然迫切需要改进必要的信息报告，以便其他研究人员进行外部验证，以增加已开发模型的临床采用。
This systematic review aims to provide further insights into the conduct and reporting of clinical prediction model development and validation over time. We focus on assessing the reporting of information necessary to enable external validation by other investigators. We searched Embase, Medline, Web-of-Science, Cochrane Library, and Google Scholar to identify studies that developed 1 or more multivariable prognostic prediction models using electronic health record (EHR) data published in the period 2009–2019. We identified 422 studies that developed a total of 579 clinical prediction models using EHR data. We observed a steep increase over the years in the number of developed models. The percentage of models externally validated in the same paper remained at around 10%. Throughout 2009–2019, for both the target population and the outcome definitions, code lists were provided for less than 20% of the models. For about half of the models that were developed using regression analysis, the final model was not completely presented. Overall, we observed limited improvement over time in the conduct and reporting of clinical prediction model development and validation. In particular, the prediction problem definition was often not clearly reported, and the final model was often not completely presented. Improvement in the reporting of information necessary to enable external validation by other investigators is still urgently needed to increase clinical adoption of developed models.
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影响因子：
6.1
作者：
Khalid S;Yang C;Blacketer C;Duarte-Salles T;Fernández-Bertolín S;Kim C;Park RW;Park J;Schuemie MJ;Sena AG;Suchard MA;You SC;Rijnbeek PR;Reps JM
通讯作者：
Reps JM
影响因子：
2.9
作者：
Collins GS;Dhiman P;Andaur Navarro CL;Ma J;Hooft L;Reitsma JB;Logullo P;Beam AL;Peng L;Van Calster B;van Smeden M;Riley RD;Moons KG
通讯作者：
Moons KG
影响因子：
7.2
作者：
Collins, Gary S.;Reitsma, Johannes B.;Moons, Karel G. M.
通讯作者：
Moons, Karel G. M.
影响因子：
4
作者：
Collins GS;de Groot JA;Dutton S;Omar O;Shanyinde M;Tajar A;Voysey M;Wharton R;Yu LM;Moons KG;Altman DG
通讯作者：
Altman DG
DOI：
10.1093/jamia/ocy032
发表时间：
2018-08-01
影响因子：
6.4
作者：
Reps, Jenna M.;Schuemie, Martijn J.;Rijnbeek, Peter R.
通讯作者：
Rijnbeek, Peter R.