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
gold, Green Published, All Open Access; Gold
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