Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review

Yang, C (通讯作者),Erasmus Univ, Dept Med Informat, Med Ctr, Dr Molewaterpl 40, NL-3015 GD Rotterdam, Netherlands.
2022-4-13
Objectives 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. Materials and Methods 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. Results 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. Discussion 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. Conclusion 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.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
卷号:29|期号:5|页码:983-989
ISSN:1067-5027|收录类别:SCIE
语种
英语
来源机构
Erasmus University Rotterdam; Erasmus MC
资助信息
This work has received support from the European Health Data & Evidence Network (EHDEN) project. EHDEN has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement no 806968. The JU receives support from the European Union's Horizon 2020 research and innovation program and EFPIA.
被引频次(WOS)
2
被引频次(其他)
2
180天使用计数
1
2013以来使用计数
6
EISSN
1527-974X
出版年
2022-4-13
DOI
10.1093/jamia/ocac002
学科领域
循证公共卫生
关键词
clinical prediction model electronic health record external validation machine learning clinical decision support
资助机构
European Health Data & Evidence Network (EHDEN) project Innovative Medicines Initiative 2 Joint Undertaking (JU) European Union(European Commission) EFPIA
WOS学科分类
Computer Science, Information Systems Computer Science, Interdisciplinary Applications Health Care Sciences & Services Information Science & Library Science Medical Informatics