Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis

Abstract Purpose To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim was to predict individual risks for developing CRF. Methods Two pre-existing datasets were used. The Nivel-Primary Care Database and the Netherlands Cancer Registry (NCR) formed the Primary Secondary Cancer Care Registry (PSCCR). NCR data with Patient Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship (PR... Mehr ...

Verfasser: Beenhakker, Lian
Wijlens, Kim A. E.
Witteveen, Annemieke
Heins, Marianne
Korevaar, Joke C.
de Ligt, Kelly M.
Bode, Christina
Vollenbroek-Hutten, Miriam M. R.
Siesling, Sabine
Dokumenttyp: Artikel
Erscheinungsdatum: 2023
Reihe/Periodikum: Journal of Cancer Survivorship ; ISSN 1932-2259 1932-2267
Verlag/Hrsg.: Springer Science and Business Media LLC
Schlagwörter: Oncology (nursing) / Oncology
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26680770
Datenquelle: BASE; Originalkatalog
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Link(s) : http://dx.doi.org/10.1007/s11764-023-01491-1