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@ARTICLE{Haider:304845,
      author       = {M. Haider and J. J. Leow and T. Nordström and A. Mortezavi
                      and P. Albers$^*$ and R. Heer and P. Rajan},
      title        = {{E}merging tools for the early detection of prostate
                      cancer.},
      journal      = {BJUI compass},
      volume       = {6},
      number       = {9},
      issn         = {2688-4526},
      address      = {[Hoboken, NJ]},
      publisher    = {Wiley},
      reportid     = {DKFZ-2025-01951},
      pages        = {e70081},
      year         = {2025},
      abstract     = {Prostate cancer (PCa) is the second most common cancer in
                      men globally, with a rising incidence. Early detection
                      through population-based screening by Prostate Specific
                      Antigen (PSA) testing improves survival outcomes, at the
                      expense of overdiagnosis and overtreatment of clinically
                      insignificant disease. Here, we explore emerging tools for
                      more effective PCa early detection and evaluate their
                      potential roles for PCa screening.Key articles on emerging
                      adjuncts and alternatives to PSA for PCa early detection
                      were identified.Multiparametric MRI (mpMRI) remains the gold
                      standard modality for identifying clinically significant PCa
                      and has been evaluated for screening. Newer imaging
                      strategies incorporating biparametric MRI (bpMRI) or
                      multiparametric ultrasound (mpUS) potentially offer similar
                      accuracy to mpMRI. Saliva-derived polygenic risk scores
                      (PRS) hold potential as a non-invasive screening tool to
                      identify at-risk patient groups. Blood-based biomarker tests
                      can improve risk stratification, reducing unnecessary
                      biopsies while maintaining detection of clinically
                      significant cancers compared to PSA alone. Urine-based
                      biomarker tests have been examined for the early detection
                      and risk stratification of clinically significant disease as
                      adjuncts to PSA testing.PSA is commonly used to detect early
                      PCa, but its lack of specificity and associated
                      overdiagnosis risk has led to controversy over its use for
                      population-based screening. Imaging modalities such as mpMRI
                      have reduced detection of clinically insignificant PCa, and
                      emerging cost-effective alternatives, such as bpMRI and
                      mpUS, show promise. Molecular biomarkers and PRS for risk
                      stratification may help target imaging-based early detection
                      more effectively to at-risk populations. Prospective
                      randomised clinical trials are urgently needed to evaluate
                      the performance of different modalities for population-wide
                      screening. Future developments may involve technologies such
                      as artificial intelligence and diagnostic tests that
                      incorporate circulating tumour markers.},
      subtyp        = {Review Article},
      keywords     = {4 K score (Other) / AI (Other) / ExoDx prostate (Other) /
                      MRI (Other) / MyProstateScore (Other) / PRS (Other) / PSA
                      (Other) / SelectMDx (Other) / Stockholm 3 (Other) / early
                      diagnosis (Other) / polygenic risk score (Other) / prostate
                      cancer (Other) / prostate health index (Other) / screening
                      (Other) / ultrasound (Other)},
      cin          = {C130},
      ddc          = {610},
      cid          = {I:(DE-He78)C130-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40979549},
      pmc          = {pmc:PMC12446083},
      doi          = {10.1002/bco2.70081},
      url          = {https://inrepo02.dkfz.de/record/304845},
}