Updating Clinical Prediction Models: An Illustrative Case Study

Hendrik Jan Mijderwijk*, Stefan van Beek, Daan Nieboer

*Corresponding author for this work

Research output: Chapter/Conference proceedingChapterAcademic

2 Citations (Scopus)

Abstract

The performance of clinical prediction models tends to deteriorate over time. Researchers often develop a new prediction if an existing model performs poorly at external validation. Model updating is an efficient technique and promising alternative to the de novo development of clinical prediction models. Model updating has been recommended by the TRIPOD guidelines. To illustrate several model updating techniques, a case study is provided for the development and updating of a clinical prediction model assessing postoperative anxiety in data coming from two double-blinded placebo-controlled randomized controlled trials with a very similar methodological framework. Note that the developed model and updated model are for didactic purposes only. This paper discusses some common considerations and caveats for researchers to be aware of when planning or applying updating of a prediction model.

Original languageEnglish
Title of host publicationActa Neurochirurgica, Supplementum
PublisherSpringer Science+Business Media
Pages109-113
Number of pages5
DOIs
Publication statusPublished - 4 Dec 2021

Publication series

SeriesActa Neurochirurgica, Supplementum
Volume134
ISSN0065-1419

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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