Personalized Dynamic Prediction Model for Biopsy Timing in Patients With Prostate Cancer During Active Surveillance
In this prognostic study, the developed dynamic risk model effectively identified patients at low risk of PC reclassification during AS. After prospective validation, this model may support personalized, risk-based AS and reduce the burden of unnecessary biopsies.
Authors
- Mieke Van Hemelrijck (ORCID: https://orcid.org/0000-0002-7317-0858)
- Anders Bjartell (ORCID: https://orcid.org/0000-0002-5761-3786)
- Daan Nieboer (ORCID: https://orcid.org/0000-0002-4403-6537)
- Antti Rannikko (ORCID: https://orcid.org/0000-0002-4261-3484)
- Monique J. Roobol (ORCID: https://orcid.org/0000-0001-6967-1708)
- Mark Frydenberg (ORCID: https://orcid.org/0000-0003-4445-3573)
- Ivo I. de Vos (ORCID: https://orcid.org/0000-0001-9000-7457)
- Christian P. Pavlovich (ORCID: https://orcid.org/0000-0002-8532-0251)
- Lui Shiong Lee (ORCID: https://orcid.org/0000-0002-8208-0635)
- Axel Semjonow
- Ewout W. Steyerberg (ORCID: https://orcid.org/0000-0002-7787-0122)
Institutions
- University of Helsinki (FI)
- Johns Hopkins University (US)
- King's College London (GB)
- Guy's and St Thomas' NHS Foundation Trust (GB)
- Leiden University Medical Center (NL)
- Helsinki University Hospital (FI)
- Cabrini Hospital (AU)
- Skåne University Hospital (SE)
- Erasmus MC Cancer Institute (NL)
- Sengkang General Hospital (SG)
- Monash University (AU)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2025-01-16
- DOI
- https://doi.org/10.1001/jamanetworkopen.2024.54366
- Citations
- 5
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 7.59