000129994 001__ 129994
000129994 005__ 20240118092026.0
000129994 0247_ $$2doi$$a10.1007/s00345-019-02946-w
000129994 0248_ $$2sideral$$a113268
000129994 037__ $$aART-2020-113268
000129994 041__ $$aeng
000129994 100__ $$0(orcid)0000-0003-0178-4567$$aBorque Fernando, Ángel$$uUniversidad de Zaragoza
000129994 245__ $$aHow to implement magnetic resonance imaging before prostate biopsy in clinical practice: nomograms for saving biopsies
000129994 260__ $$c2020
000129994 5060_ $$aAccess copy available to the general public$$fUnrestricted
000129994 5203_ $$aPurpose To combine multiparametric MRI (mpMRI) findings and clinical parameters to provide nomograms for diagnosing different scenarios of aggressiveness of prostate cancer (PCa).MethodsA cohort of 346 patients with suspicion of PCa because of abnormal finding in digital rectal examination (DRE) and/or high prostate specific antigen (PSA) level received mpMRI prior to prostate biopsy (PBx). A conventional 12-core transrectal PBx with two extra cores from suspicious areas in mpMRI was performed by cognitive fusion. Multivariate logistic regression analysis was performed combining age, PSA density (PSAD), DRE, number of previous PBx, and mpMRI find-ings to predict three different scenarios: PCa, significant PCa (ISUP-group = 2), or aggressive PCa (ISUP-group = 3). We validate models by ROC curves, calibration plots, probability density functions (PDF), and clinical utility curves (CUC). Cut-off probabilities were estimated for helping decision-making in clinical practice.ResultsOur cohort showed 39.6% incidence of PCa, 32.6% of significant PCa, and 23.4% of aggressive PCa. The AUC of predictive models were 0.856, 0.883, and 0.911, respectively. The PDF and CUC showed 11% missed diagnoses of significant PCa (35 cases of 326 significant PCa expected in 1000 proposed Bx) when choosing < 18% as the cutoff of probability for not performing PBx; the percentage of saved PBx was 47% (474 avoided PBx in 1000 proposed).ConclusionWe developed clinical and mpMRI-based nomograms with a high discrimination ability for three different sce-narios of PCa aggressiveness (https ://urost atist icals oluti ons.shiny apps.io/MRIfu sionP CPred ictio n/). Specific clinical cutoff points allow us to save a high number of PBx with a minimum of missed diagnoses.
000129994 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000129994 590__ $$a4.226$$b2020
000129994 591__ $$aUROLOGY & NEPHROLOGY$$b21 / 89 = 0.236$$c2020$$dQ1$$eT1
000129994 592__ $$a1.552$$b2020
000129994 593__ $$aUrology$$c2020$$dQ1
000129994 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000129994 700__ $$0(orcid)0000-0002-3007-302X$$aEsteban Escaño, Luis Mariano
000129994 700__ $$aCelma, Ana
000129994 700__ $$aRoche, Sarai
000129994 700__ $$aPlanas, Jacques
000129994 700__ $$aRegis, Lucas
000129994 700__ $$ade Torres, Inés
000129994 700__ $$aSemidey, María Eugenia
000129994 700__ $$aTrilla, Enrique
000129994 700__ $$aMorote, Juan
000129994 7102_ $$11013$$2817$$aUniversidad de Zaragoza$$bDpto. Cirugía$$cÁrea Urología
000129994 773__ $$g38 (2020), 1481-1491$$pWorld j. urol.$$tWORLD JOURNAL OF UROLOGY$$x0724-4983
000129994 8564_ $$s2471401$$uhttps://zaguan.unizar.es/record/129994/files/texto_completo.pdf$$yPostprint
000129994 8564_ $$s1640823$$uhttps://zaguan.unizar.es/record/129994/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000129994 909CO $$ooai:zaguan.unizar.es:129994$$particulos$$pdriver
000129994 951__ $$a2024-01-18-09:04:38
000129994 980__ $$aARTICLE