Treatment-Free Survival and the Pattern of Follow-Up Treatments After Curative Prostate Cancer Treatment, a Real-World Analysis of Big Data from Electronic Health Records from a Tertiary Center
<b>Background:</b> Prospective trials provide robust evidence for prostate cancer (PCa) treatment but often include highly selective populations, limiting generalizability. Real-world data (RWD) can address these gaps and inform personalized care. <b>Objectives</b>: This study aimed to evaluate treatment-free survival (TFS) and secondary treatment sequences after initial curative therapy for PCa using electronic health record (EHR) data and to analyze associated medication profiles. <b>Methods</b>: We studied 3024 patients treated with radical prostatectomy (RP), brachytherapy (BT), or curative radiotherapy (RT) at Erasmus MC (2009-2023), the Netherlands. Outcomes included TFS, treatment sequences, and medication patterns across treatment lines. <b>Results</b>: Median age at diagnosis was 65 years (IQR 61-69) for RP, 68 (62-73) for BT, and 72 (68-76) for RT. At 10 years, TFS was 89% (95% CI: 84.9-94.1) for BT, 85% (95% CI: 83-87) for RT, and 71% (95% CI: 65.7-75.8) for RP. Most patients remained treatment-free, but up to five treatment lines occurred, mainly in patients with low comorbidity scores. Medication profiles reflected treatment-related morbidity: alpha-blocker use increased after BT and RT, while bladder relaxants were common after RP. Comorbidity-related medication use remained low among patients undergoing multiple sequenced treatments. <b>Conclusions</b>: These findings highlight the real-world application of multiple secondary treatments after different primary curative therapy options for PCa and associated comorbidity and medication use patterns. They confirm the durability and long-term effectiveness of curative treatments in real-world PCa care. By combining treatment trajectories and medication profiles, RWD provides insights for personalized counseling, helping clinicians and patients anticipate long-term treatment needs, and enabling informed decisions aligned with health status and preferences.
Authors
- Leonard P. Bokhorst (ORCID: https://orcid.org/0000-0003-1154-4794)
- Roderick C N van den Bergh
- Frederique Denijs (ORCID: https://orcid.org/0009-0008-3306-9297)
- Sebastiaan Remmers
- Monique J. Roobol
Institutions
- Medisch Centrum Haaglanden (NL)
- Erasmus MC Cancer Institute (NL)
Publication Details
- Journal
- Journal of Personalized Medicine
- Published
- 2026-01-04
- DOI
- https://doi.org/10.3390/jpm16010022
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00