Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/48480

Registo completo
Campo DCValorIdioma
dc.contributor.authorCicione, Antoniopor
dc.contributor.authorCormio, Luigipor
dc.contributor.authorCantiello, Francescopor
dc.contributor.authorPalumbo, Italo M.por
dc.contributor.authorDe Nunzio, Cosimopor
dc.contributor.authorLima, Estêvão Augusto Rodrigues depor
dc.contributor.authorUcciero, Giuseppepor
dc.contributor.authorCarrieri, Giuseppepor
dc.contributor.authorDamiano, Roccopor
dc.date.accessioned2017-12-21T09:49:33Z-
dc.date.issued2017-10-
dc.identifier.citationCicione A, Cormio L, Cantiello F, Palumbo IM, De Nunzio C, Lima E, et al. Presence and severity of lower urinary tract symptoms are inversely correlated with the risk of prostate cancer on prostate biopsy. Minerva Urol Nefrol 2017;69:486-92. DOI: 10.23736/S0393-2249.17.02737-0por
dc.identifier.issn0393-2249-
dc.identifier.urihttps://hdl.handle.net/1822/48480-
dc.description.abstractBACKGROUND: The assessment of lower urinary tract symptoms (LUTS) is common part of urological investigation. Furthermore, patients bother of prostate cancer (PCa) when they are affected of LUTS. This study was aimed to determine whether the presence and severity of LUTS, as assessed by the International Prostate Symptoms Score (IPSS), could help to identify patients at higher risk of prostate cancer (PCa) on prostate biopsy (PBx). In this effort, an initial PCa predictive model was calculated and IPSS was subsequently added. The diagnostic accuracy of both models was compared. METHODS: The analysis of prospectively collected data of patients scheduled for PBx at four academic hospitals between January 2012 and June 2015 was performed. Univariate and multivariate analysis assessed the correlation between the IPSS and the risk of being diagnosed with PCa; Receiver operator characteristic curve (ROC) analysis evaluated the predictive models including or not the IPSS. RESULTS: Of the 1366 enrolled patients, 706 (52%) were diagnosed with PCa. Patients with PCa had a significantly lower IPSS (10.6 +/- 7.4 vs. 12.7 +/- 8.1) than those with benign diagnosis. Multivariate logistic regression analysis showed that age, prostate-specific antigen (PSA), prostate volume and IPSS were the most significant predictors of PBx outcome, (OR 1.61, P=0.001; OR 1.20, P=0.001; OR 0.97, P=0.001; OR 0.74, P=0.004; respectively). ROC curve analysis showed that the addition of IPSS to the predictive model based on age, PSA, DRE and prostate volume significantly improved the model diagnostic accuracy (AUC: 0.776 vs. 0.652; P=0.001). CONCLUSIONS: Presence and severity of LUTS are inversely correlated with the risk of being diagnosed with PCa at PBx. Incorporating the IPSS into predictive models may reduce the risk of unnecessary PBxs.por
dc.language.isoengpor
dc.publisherEdizioni Minerva Medicapor
dc.rightsopenAccess-
dc.subjectLower urinary tract symptomspor
dc.subjectBiopsypor
dc.subjectProstatic neoplasmspor
dc.titlePresence and severity of lower urinary tract symptoms are inversely correlated with the risk of prostate cancer on prostate biopsypor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://www.minervamedica.it/en/journals/minerva-urologica-nefrologica/article.php?cod=R19Y2017N05A0486por
oaire.citationStartPage486por
oaire.citationEndPage492por
oaire.citationIssue5por
oaire.citationVolume69por
dc.date.updated2017-12-18T12:18:22Z-
dc.identifier.eissn1827-1758-
dc.identifier.doi10.23736/S0393-2249.17.02737-0por
dc.identifier.pmid28124868por
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
dc.subject.wosScience & Technologypor
sdum.journalMinerva Urologica e Nefrologicapor
Aparece nas coleções:ICVS - Artigos em revistas internacionais / Papers in international journals

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
18.pdf496,47 kBAdobe PDFVer/Abrir

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID