Epidemiological description and trajectories of patients with prostate cancer in Denmark: an observational study of 7448 patients

Victoria Blanes-Vidal*, Ashkan Tashk, Manuella Lech Cantuaria, Rasmus Søgaard Hansen, Charlotte A. Poulsen, Mads Hvid Aaberg Poulsen, Marie-Louise Krogh, Søren Paludan Sheikh, Esmaeil Nadimi

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Objective: Identification of patients at high risk of aggressive prostate cancer is a major clinical challenge. With the view of developing artificial intelligence-based methods for identification of these patients, we are constructing a comprehensive clinical database including 7448 prostate cancer (PCa) Danish patients. In this paper we provide an epidemiological description and patients’ trajectories of this retrospective observational population, to contribute to the understanding of the characteristics and pathways of PCa patients in Denmark. Results: Individuals receiving a PCa diagnosis during 2008–2014 in Region Southern Denmark were identified, and all diagnoses, operations, investigations, and biochemistry analyses, from 4 years prior, to 5 years after PCa diagnosis were obtained. About 85.1% were not diagnosed with metastatic PCa during the study period (unaggressive PCa); 9.2% were simultaneously diagnosed with PCa and metastasis (aggressive-advanced PCa), while 5.7% were not diagnosed with metastatic PCa at first, but they were diagnosed with metastasis at some point during the 5 years follow-up (aggressive-not advanced PCa). Patients with unaggressive PCa had more clinical investigations directly related to PCa detection (prostate ultrasounds and biopsies) during the 4 years prior to PCa diagnosis, compared to patients with aggressive PCa, which may have contributed to the early detection of PCa.

Original languageEnglish
Article number341
JournalBMC Research Notes
Volume16
Issue number1
Number of pages6
ISSN1756-0500
DOIs
Publication statusPublished - 16. Nov 2023

Keywords

  • Clinical data
  • Prostate cancer
  • Survival
  • Trajectory
  • Denmark/epidemiology
  • Early Detection of Cancer
  • Prostatic Neoplasms/diagnosis
  • Artificial Intelligence
  • Humans
  • Male
  • Retrospective Studies

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