Number of Publications on New Clinical Prediction Models: A Bibliometric Review

Arshi, Banafsheh; Wynants, Laure; Rijnhart, Eline; Reeve, Kelly; Cowley, Laura; Smits, Luc J

doi:10.2196/62710

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Number of Publications on New Clinical Prediction Models: A Bibliometric Review

Banafsheh Arshi

, Laure Wynants

, Eline Rijnhart

, Kelly Reeve

, Laura Cowley, Luc J Smits

JMIR Medical Informatics, Volume: 13, Start page: e62710

Swansea University Author: Laura Cowley

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© Banafsheh Arshi, Laure Wynants, Eline Rijnhart, Kelly Reeve, Laura Elizabeth Cowley, Luc J Smits. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
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DOI (Published version): 10.2196/62710

Abstract

Concerns have been expressed about the abundance of new clinical prediction models (CPMs) proposed in the literature. However, the extent of this proliferation in prediction research remains unclear. This study aimed to estimate the total and annual number of CPM development-related publications ava...

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Published in:	JMIR Medical Informatics
ISSN:	2291-9694
Published:	JMIR Publications 2025
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa69987

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Using a validated search strategy, we conducted a systematic search of literature for prediction model studies published in Pubmed and Embase between 1995 and the end of 2020. By taking random samples for each year, we identified eligible studies that developed a multivariable model (ie, diagnostic or prognostic) for individual-level prediction of a health outcome across all medical fields. Exclusion criteria included development of models with a single predictor, studies not involving humans, methodological studies, conference abstracts, articles with unavailable full text, and those not available in English. We estimated the total and annual number of published regression-based multivariable CPM development articles, based on the total number of publications, proportion of included articles, and the search sensitivity. Furthermore, we used an adjusted Poisson regression to extrapolate our results to the period 1950-2024. Additionally, we estimated the number of articles that developed CPMs using techniques other than regression (eg, machine learning). From a random sample of 10,660 articles published between 1995 and 2020, 109 regression-based CPM development articles were included. We estimated that 82,772 (95% CI 65,313-100,231) CPM development articles using regression were published, with an acceleration in model development from 2010 onward. With the addition of articles that developed non-regression-based CPMs, the number increased to 147,714 (95% CI 125,201-170,226). After extrapolation to the years 1950-2024, the number of articles increased to 156,673 and 248,431 for regression-based models and total CPMs, respectively. Based on a representative sample of publications from the literature, we estimated that nearly 250,000 articles reporting the development of CPMs across all medical fields were published until 2024. CPM development-related publications continue to increase in number. 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spelling	2025-07-17T10:34:52.2545484 v2 69987 2025-07-17 Number of Publications on New Clinical Prediction Models: A Bibliometric Review a80501f280e89fee276510b25fc68e77 Laura Cowley Laura Cowley true false 2025-07-17 MEDS Concerns have been expressed about the abundance of new clinical prediction models (CPMs) proposed in the literature. However, the extent of this proliferation in prediction research remains unclear. This study aimed to estimate the total and annual number of CPM development-related publications available across all medical fields. Using a validated search strategy, we conducted a systematic search of literature for prediction model studies published in Pubmed and Embase between 1995 and the end of 2020. By taking random samples for each year, we identified eligible studies that developed a multivariable model (ie, diagnostic or prognostic) for individual-level prediction of a health outcome across all medical fields. Exclusion criteria included development of models with a single predictor, studies not involving humans, methodological studies, conference abstracts, articles with unavailable full text, and those not available in English. We estimated the total and annual number of published regression-based multivariable CPM development articles, based on the total number of publications, proportion of included articles, and the search sensitivity. Furthermore, we used an adjusted Poisson regression to extrapolate our results to the period 1950-2024. Additionally, we estimated the number of articles that developed CPMs using techniques other than regression (eg, machine learning). From a random sample of 10,660 articles published between 1995 and 2020, 109 regression-based CPM development articles were included. We estimated that 82,772 (95% CI 65,313-100,231) CPM development articles using regression were published, with an acceleration in model development from 2010 onward. With the addition of articles that developed non-regression-based CPMs, the number increased to 147,714 (95% CI 125,201-170,226). After extrapolation to the years 1950-2024, the number of articles increased to 156,673 and 248,431 for regression-based models and total CPMs, respectively. Based on a representative sample of publications from the literature, we estimated that nearly 250,000 articles reporting the development of CPMs across all medical fields were published until 2024. CPM development-related publications continue to increase in number. To prevent research waste and close the gap between research and clinical practice, focus should shift away from developing new CPMs to facilitating model validation and impact assessment of the plethora of existing CPMs. Limitations of this study include restriction of search to articles available in English and development of the validated search strategy prior to the popularity of artificial intelligence and machine learning models. Journal Article JMIR Medical Informatics 13 e62710 JMIR Publications 2291-9694 prediction modeling; model development; external validation; public health; research waste; clinical prediction; clinical practice; online databases; health outcomes; publication records; publication 4 7 2025 2025-07-04 10.2196/62710 Review COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee 2025-07-17T10:34:52.2545484 2025-07-17T10:07:58.3598836 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Banafsheh Arshi 0000-0003-0223-7872 1 Laure Wynants 0000-0002-3037-122X 2 Eline Rijnhart 0000-0001-5300-998X 3 Kelly Reeve 0000-0001-9325-6467 4 Laura Cowley 5 Luc J Smits 0000-0003-0785-1345 6 69987__34782__475fc5eb8ed5401985252bd2d494ddfd.pdf 69987.VOR.pdf 2025-07-17T10:31:52.3355404 Output 508254 application/pdf Version of Record true © Banafsheh Arshi, Laure Wynants, Eline Rijnhart, Kelly Reeve, Laura Elizabeth Cowley, Luc J Smits. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). true eng https://creativecommons.org/licenses/by/4.0/
title	Number of Publications on New Clinical Prediction Models: A Bibliometric Review
spellingShingle	Number of Publications on New Clinical Prediction Models: A Bibliometric Review Laura Cowley
title_short	Number of Publications on New Clinical Prediction Models: A Bibliometric Review
title_full	Number of Publications on New Clinical Prediction Models: A Bibliometric Review
title_fullStr	Number of Publications on New Clinical Prediction Models: A Bibliometric Review
title_full_unstemmed	Number of Publications on New Clinical Prediction Models: A Bibliometric Review
title_sort	Number of Publications on New Clinical Prediction Models: A Bibliometric Review
author_id_str_mv	a80501f280e89fee276510b25fc68e77
author_id_fullname_str_mv	a80501f280e89fee276510b25fc68e77_***_Laura Cowley
author	Laura Cowley
author2	Banafsheh Arshi Laure Wynants Eline Rijnhart Kelly Reeve Laura Cowley Luc J Smits
format	Journal article
container_title	JMIR Medical Informatics
container_volume	13
container_start_page	e62710
publishDate	2025
institution	Swansea University
issn	2291-9694
doi_str_mv	10.2196/62710
publisher	JMIR Publications
college_str	Faculty of Medicine, Health and Life Sciences
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department_str	Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science
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description	Concerns have been expressed about the abundance of new clinical prediction models (CPMs) proposed in the literature. However, the extent of this proliferation in prediction research remains unclear. This study aimed to estimate the total and annual number of CPM development-related publications available across all medical fields. Using a validated search strategy, we conducted a systematic search of literature for prediction model studies published in Pubmed and Embase between 1995 and the end of 2020. By taking random samples for each year, we identified eligible studies that developed a multivariable model (ie, diagnostic or prognostic) for individual-level prediction of a health outcome across all medical fields. Exclusion criteria included development of models with a single predictor, studies not involving humans, methodological studies, conference abstracts, articles with unavailable full text, and those not available in English. We estimated the total and annual number of published regression-based multivariable CPM development articles, based on the total number of publications, proportion of included articles, and the search sensitivity. Furthermore, we used an adjusted Poisson regression to extrapolate our results to the period 1950-2024. Additionally, we estimated the number of articles that developed CPMs using techniques other than regression (eg, machine learning). From a random sample of 10,660 articles published between 1995 and 2020, 109 regression-based CPM development articles were included. We estimated that 82,772 (95% CI 65,313-100,231) CPM development articles using regression were published, with an acceleration in model development from 2010 onward. With the addition of articles that developed non-regression-based CPMs, the number increased to 147,714 (95% CI 125,201-170,226). After extrapolation to the years 1950-2024, the number of articles increased to 156,673 and 248,431 for regression-based models and total CPMs, respectively. Based on a representative sample of publications from the literature, we estimated that nearly 250,000 articles reporting the development of CPMs across all medical fields were published until 2024. CPM development-related publications continue to increase in number. To prevent research waste and close the gap between research and clinical practice, focus should shift away from developing new CPMs to facilitating model validation and impact assessment of the plethora of existing CPMs. Limitations of this study include restriction of search to articles available in English and development of the validated search strategy prior to the popularity of artificial intelligence and machine learning models.
published_date	2025-07-04T05:30:09Z
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Number of Publications on New Clinical Prediction Models: A Bibliometric Review

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