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Updated: Jan 13, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Past and present of prostate cancer screening in the European Union
J Gómez Rivas1, P Gómez Dávila2, A M Tarrazo Antelo3
1Servicio de Urología, Hospital Clínico San Carlos, Madrid, Spain; Instituto de Investigación Sanitaria, Hospital Clínico San Carlos, Madrid, Spain; Facultad de Medicina, Universidad Complutense de Madrid, Spain.
Introduction:
Prostate cancer (PCa) screening based on prostate-specific antigen (PSA) testing has represented a major milestone in early detection; however, it has also prompted considerable debate due to the risks of overdiagnosis and overtreatment. This review examines the evolution of PCa screening, highlighting its main challenges and emerging approaches aimed at achieving more accurate and individualized detection.
Methods:
A narrative review of the literature was conducted using databases such as PubMed and Google Scholar, applying MeSH terms related to screening, overdiagnosis, and prostate cancer. Clinical studies, systematic reviews, and recent guidelines pertinent to the topic were included.
Results:
The PLCO, ERSPC, and Göteborg trials provide complementary insights into the impact of PSA-based screening, with outcomes ranging from limited benefit to significant reductions in PCa-specific mortality. Based on these this findings, a paradigm shift toward risk-stratified screening strategies has been advocated. The incorporation of new tools such as magnetic resonance imaging, blood and urine biomarkers, risk calculators, and artificial intelligence-based algorithms has improved diagnostic accuracy. These strategies reduce unnecessary biopsies and focus on the detection of clinically significant disease. Current guidelines recommend individualized assessment based on factors such as age, baseline PSA levels, family history, and comorbidities.
Conclusion:
The future of PCa screening resides in personalized medicine, in which the integration of clinical, imaging, and molecular parameters will enable a more efficient approach, minimizing unnecessary interventions and improving overall patient outcomes.
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