What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications
Introduction It is known that only a limited proportion of developed clinical prediction models (CPMs) are implemented and/or used in clinical practice. This may result in a large amount of research waste, even when considering that some CPMs may demonstrate poor performance. Cross-sectional estimat...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2023-05-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/13/5/e073174.full |
| _version_ | 1797824625754767360 |
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| author | Laura Elizabeth Cowley Laure Wynants Banafsheh Arshi Eline Rijnhart Kelly Reeve Luc J Smits |
| author_facet | Laura Elizabeth Cowley Laure Wynants Banafsheh Arshi Eline Rijnhart Kelly Reeve Luc J Smits |
| author_sort | Laura Elizabeth Cowley |
| collection | DOAJ |
| description | Introduction It is known that only a limited proportion of developed clinical prediction models (CPMs) are implemented and/or used in clinical practice. This may result in a large amount of research waste, even when considering that some CPMs may demonstrate poor performance. Cross-sectional estimates of the numbers of CPMs that have been developed, validated, evaluated for impact or utilized in practice, have been made in specific medical fields, but studies across multiple fields and studies following up the fate of CPMs are lacking.Methods and analysis We have conducted a systematic search for prediction model studies published between January 1995 and December 2020 using the Pubmed and Embase databases, applying a validated search strategy. Taking random samples for every calendar year, abstracts and articles were screened until a target of 100 CPM development studies were identified. Next, we will perform a forward citation search of the resulting CPM development article cohort to identify articles on external validation, impact assessment or implementation of those CPMs. We will also invite the authors of the development studies to complete an online survey to track implementation and clinical utilization of the CPMs.We will conduct a descriptive synthesis of the included studies, using data from the forward citation search and online survey to quantify the proportion of developed models that are validated, assessed for their impact, implemented and/or used in patient care. We will conduct time-to-event analysis using Kaplan-Meier plots.Ethics and dissemination No patient data are involved in the research. Most information will be extracted from published articles. We request written informed consent from the survey respondents. Results will be disseminated through publication in a peer-reviewed journal and presented at international conferences.OSF registration (https://osf.io/nj8s9). |
| first_indexed | 2024-03-13T10:41:46Z |
| format | Article |
| id | doaj.art-241681ac4b9343ba800eba3e1c40f72f |
| institution | Directory Open Access Journal |
| issn | 2044-6055 |
| language | English |
| last_indexed | 2024-03-13T10:41:46Z |
| publishDate | 2023-05-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj.art-241681ac4b9343ba800eba3e1c40f72f2023-05-18T02:30:06ZengBMJ Publishing GroupBMJ Open2044-60552023-05-0113510.1136/bmjopen-2023-073174What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publicationsLaura Elizabeth Cowley0Laure Wynants1Banafsheh Arshi2Eline Rijnhart3Kelly Reeve4Luc J Smits54 Division of Population Medicine, School of Medicine, Cardiff University, Cardiff, UKDepartment of Development and Regeneration, KU Leuven, Leuven, BelgiumDepartment of Epidemiology, CAPHRI School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The NetherlandsDepartment of Epidemiology, CAPHRI School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The NetherlandsDepartment of Epidemiology, Biostatistics and Prevention Institute, Department of Biostatistics, University of Zurich, Hirschengraben 84, CH-8001 Zurich, SwitzerlandDepartment of Epidemiology, CAPHRI School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The NetherlandsIntroduction It is known that only a limited proportion of developed clinical prediction models (CPMs) are implemented and/or used in clinical practice. This may result in a large amount of research waste, even when considering that some CPMs may demonstrate poor performance. Cross-sectional estimates of the numbers of CPMs that have been developed, validated, evaluated for impact or utilized in practice, have been made in specific medical fields, but studies across multiple fields and studies following up the fate of CPMs are lacking.Methods and analysis We have conducted a systematic search for prediction model studies published between January 1995 and December 2020 using the Pubmed and Embase databases, applying a validated search strategy. Taking random samples for every calendar year, abstracts and articles were screened until a target of 100 CPM development studies were identified. Next, we will perform a forward citation search of the resulting CPM development article cohort to identify articles on external validation, impact assessment or implementation of those CPMs. We will also invite the authors of the development studies to complete an online survey to track implementation and clinical utilization of the CPMs.We will conduct a descriptive synthesis of the included studies, using data from the forward citation search and online survey to quantify the proportion of developed models that are validated, assessed for their impact, implemented and/or used in patient care. We will conduct time-to-event analysis using Kaplan-Meier plots.Ethics and dissemination No patient data are involved in the research. Most information will be extracted from published articles. We request written informed consent from the survey respondents. Results will be disseminated through publication in a peer-reviewed journal and presented at international conferences.OSF registration (https://osf.io/nj8s9).https://bmjopen.bmj.com/content/13/5/e073174.full |
| spellingShingle | Laura Elizabeth Cowley Laure Wynants Banafsheh Arshi Eline Rijnhart Kelly Reeve Luc J Smits What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications BMJ Open |
| title | What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications |
| title_full | What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications |
| title_fullStr | What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications |
| title_full_unstemmed | What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications |
| title_short | What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications |
| title_sort | what proportion of clinical prediction models make it to clinical practice protocol for a two track follow up study of prediction model development publications |
| url | https://bmjopen.bmj.com/content/13/5/e073174.full |
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