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Performance of magnetic resonance imaging-based prostate cancer risk calculators and decision strategies in two large European medical centres.
Davik, Petter; Remmers, Sebastiaan; Elschot, Mattijs; Roobol, Monique J; Bathen, Tone Frost; Bertilsson, Helena.
Afiliação
  • Davik P; Department of Urology, St Olavs Hospital, Trondheim, Norway.
  • Remmers S; Department of Clinical and Molecular Medicine (IKOM), Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
  • Elschot M; Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Roobol MJ; Department of Radiology and Nuclear Medicine, St Olavs Hospital, Trondheim, Norway.
  • Bathen TF; Department of Circulation and Medical Imaging (ISB), Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
  • Bertilsson H; Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
BJU Int ; 133(3): 278-288, 2024 Mar.
Article em En | MEDLINE | ID: mdl-37607322
ABSTRACT

OBJECTIVES:

To compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa). PATIENTS AND

METHODS:

We retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs csPCa cases missed, before and after recalibration, at risk thresholds of 5%-20%.

RESULTS:

A total of 940 men were included, 507 (54%) had csPCa. The median (interquartile range) age, prostate-specific antigen (PSA) level, and PSA density (PSAD) were 68 (63-72) years, 9 (7-15) ng/mL, and 0.20 (0.13-0.32) ng/mL2 , respectively. In all, 18 multivariable risk calculators (MRI-RCs) and dichotomous biopsy decision strategies based on MRI findings and PSAD thresholds were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (area under the receiver operating characteristic curve 0.86) of the MRI-RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, whilst the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCas. These multivariable models outperformed all dichotomous decision strategies based only on MRI-findings and PSAD.

CONCLUSIONS:

Even in this high-risk cohort, biopsy decision support tools would avoid many prostate biopsies, whilst missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI-RCs outperformed and should be favoured over decision strategies based only on MRI and PSAD.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Antígeno Prostático Específico Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans / Male Idioma: En Revista: BJU Int Assunto da revista: UROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Noruega

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Antígeno Prostático Específico Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans / Male Idioma: En Revista: BJU Int Assunto da revista: UROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Noruega