CHARMS and PROBAST at your fingertips: a template for data extraction and risk of bias assessment in systematic reviews of predictive models


Por: Fernandez-Felix B.M., López-Alcalde J., Roqué M., Muriel A., Zamora J.

Publicada: 1 ene 2023 Ahead of Print: 17 feb 2023
Resumen:
Background: Systematic reviews of studies of clinical prediction models are becoming increasingly abundant in the literature. Data extraction and risk of bias assessment are critical steps in any systematic review. CHARMS and PROBAST are the standard tools used for these steps in these reviews of clinical prediction models. Results: We developed an Excel template for data extraction and risk of bias assessment of clinical prediction models including both recommended tools. The template makes it easier for reviewers to extract data, to assess the risk of bias and applicability, and to produce results tables and figures ready for publication. Conclusion: We hope this template will simplify and standardize the process of conducting a systematic review of prediction models, and promote a better and more comprehensive reporting of these systematic reviews. © 2023, The Author(s).

Filiaciones:
Fernandez-Felix B.M.:
 Clinical Biostatistics Unit, Hospital Universitario Ramón y Cajal. IRYCIS, Madrid, Spain

 CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain

López-Alcalde J.:
 Clinical Biostatistics Unit, Hospital Universitario Ramón y Cajal. IRYCIS, Madrid, Spain

 CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain

 Institute for Complementary and Integrative Medicine, University Hospital Zurich and University of Zurich, Zurich, Switzerland

 Faculty of Health Sciences, Universidad Francisco de Vitoria (UFV), Madrid, Spain

Roqué M.:
 CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain

 Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain

Muriel A.:
 Clinical Biostatistics Unit, Hospital Universitario Ramón y Cajal. IRYCIS, Madrid, Spain

 CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain

 Department of Nursing and Physiotherapy, Universidad de Alcala de Henares, Alcala de Henares, Spain

Zamora J.:
 Clinical Biostatistics Unit, Hospital Universitario Ramón y Cajal. IRYCIS, Madrid, Spain

 CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain

 Institute of Metabolism and Systems Research, WHO Collaborating Centre for Global Women’s Health, University of Birmingham, Birmingham, United Kingdom
ISSN: 14712288
Editorial
BMC, CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND, Reino Unido
Tipo de documento: Article
Volumen: 23 Número: 1
Páginas: 44-44
WOS Id: 000935936200003
ID de PubMed: 36800933
imagen gold, Green Published, All Open Access; Gold

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