Developing and validating clinical prediction models in hepatology - An overview for clinicians.

Autor: Strandberg R; Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden. Electronic address: rickard.strandberg@ki.se., Jepsen P; Department of Hepatology and Gastroenterology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark., Hagström H; Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden; Division of Hepatology, Department of Upper GI, Karolinska University Hospital, Stockholm, Sweden.
Jazyk: angličtina
Zdroj: Journal of hepatology [J Hepatol] 2024 Jul; Vol. 81 (1), pp. 149-162. Date of Electronic Publication: 2024 Mar 24.
DOI: 10.1016/j.jhep.2024.03.030
Abstrakt: Prediction models are everywhere in clinical medicine. We use them to assign a diagnosis or a prognosis, and there have been continuous efforts to develop better prediction models. It is important to understand the fundamentals of prediction modelling, thus, we herein describe nine steps to develop and validate a clinical prediction model with the intention of implementing it in clinical practice: Determine if there is a need for a new prediction model; define the purpose and intended use of the model; assess the quality and quantity of the data you wish to develop the model on; develop the model using sound statistical methods; generate risk predictions on the probability scale (0-100%); evaluate the performance of the model in terms of discrimination, calibration, and clinical utility; validate the model using bootstrapping to correct for the apparent optimism in performance; validate the model on external datasets to assess the generalisability and transportability of the model; and finally publish the model so that it can be implemented or validated by others.
(Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: