Publication:
Are NCCN and EAU active surveillance criteria reliable in patients with ISUP Grade-2 intermediate-risk prostate cancer? a novel model integrating MRI to predict adverse pathology

dc.contributor.coauthorMadendere, Serdar
dc.contributor.coauthorVural, Metin
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorEsen, Barış
dc.contributor.kuauthorKaraarslan, Umut Can
dc.contributor.kuauthorMüdüroğlu, Mustafa
dc.contributor.kuauthorKordan, Yakup
dc.contributor.kuauthorEsen, Tarık
dc.contributor.kuauthorVeznikli, Mert
dc.contributor.kuauthorGürses, Bengi
dc.contributor.kuauthorBaydar, Dilek Ertoy
dc.contributor.kuauthorDemirkol, Mehmet Onur
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2025-12-31T08:19:00Z
dc.date.available2025-12-31
dc.date.issued2025
dc.description.abstractIntroduction To assess adverse pathology (AP) rates in patients with grade group (GG) 2 prostate cancer (PCa) based on biopsy characteristics and treated with radical prostatectomy (RP). Performance of active surveillance (AS) guidelines in distinguishing patients with AP has also been investigated. Methods Records of 345 patients who underwent RP for GG 2 disease detected in prostate biopsy were retrospectively reviewed. Patients with suspicion of extracapsular disease on imaging, PSA >= 20 ng/dL, unavailable biopsy data, and in-bore biopsy were excluded from the study. AP was defined as the presence of ISUP GG >= 3 or extracapsular disease. AP rates in patients meeting the AS criteria of NCCN and EAU guidelines were recorded. A novel model was developed to determine AP predictors by using a multivariable logistic regression analysis and a backward stepwise method. Results Among 231 patients, median age was 64 (45-79), median PSA was 6.1 (1.2-19) ng/dL. According to biopsy and clinical characteristics, 124 patients (53.7%) met the NCCN, 31 patients (13.4%) met the EAU AS criteria. Pathological examination after RP revealed AP in 105 patients (45.5%); GG >= 3 disease in 31 (13.4%), pT3a disease in 78 (33.7%), pT3b disease in 18 (7.8%), and pN1 disease in four patients (1.7%). AP rates in patients meeting NCCN and EAU criteria were 37.9% and 22.6%, respectively. Age ( > 63.5), PSA level ( > 5.04 ng/dL), GG2 PCa-bearing index lesion size on mpMRI ( > 11.5 mm), maximum tumor length/core length ( > 51.5%) and Gleason Pattern 4 percentage (>%17.5) were independent predictors of AP in our new model. Conclusions NCCN AS criteria were associated with nearly a twofold higher rate of AP compared with patients meeting EAU criteria. Our new model, including parameters derived from age, PSA, mpMRI and biopsy characteristics, demonstrated superior performance relative to both NCCN and EAU criteria regarding AP prediction among patients with GG 2 PCa.
dc.description.fulltextYes
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.identifier.doi10.1002/pros.70073
dc.identifier.eissn1097-0045
dc.identifier.embargoNo
dc.identifier.issn0270-4137
dc.identifier.pubmed41051163
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-105017925136
dc.identifier.urihttps://doi.org/10.1002/pros.70073
dc.identifier.urihttps://hdl.handle.net/20.500.14288/31425
dc.identifier.wos001588392600001
dc.keywordsActive surveillance
dc.keywordsMultiparametric magnetic resonance imaging
dc.keywordsProstate cancer
dc.keywordsTargeted biopsy
dc.language.isoeng
dc.publisherWiley
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofProstate
dc.relation.openaccessYes
dc.rightsCC BY-NC-ND (Attribution-NonCommercial-NoDerivs)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectEndocrinology and metabolism
dc.subjectUrology and nephrology
dc.titleAre NCCN and EAU active surveillance criteria reliable in patients with ISUP Grade-2 intermediate-risk prostate cancer? a novel model integrating MRI to predict adverse pathology
dc.typeJournal Article
dspace.entity.typePublication
person.familyNameEsen
person.familyNameKaraarslan
person.familyNameMüdüroğlu
person.familyNameKordan
person.familyNameEsen
person.familyNameVeznikli
person.familyNameGürses
person.familyNameBaydar
person.familyNameDemirkol
person.givenNameBarış
person.givenNameUmut Can
person.givenNameMustafa
person.givenNameYakup
person.givenNameTarık
person.givenNameMert
person.givenNameBengi
person.givenNameDilek Ertoy
person.givenNameMehmet Onur
relation.isOrgUnitOfPublicationd02929e1-2a70-44f0-ae17-7819f587bedd
relation.isOrgUnitOfPublication.latestForDiscoveryd02929e1-2a70-44f0-ae17-7819f587bedd
relation.isParentOrgUnitOfPublication17f2dc8e-6e54-4fa8-b5e0-d6415123a93e
relation.isParentOrgUnitOfPublication.latestForDiscovery17f2dc8e-6e54-4fa8-b5e0-d6415123a93e

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