Clinical factors stratifying the risk of tumor upgrading to high-grade disease in low-risk prostate cancer. Issue 2 (March 2018)

• Record Type: Journal Article
• Authors: Porcaro, Antonio B.; Siracusano, Salvatore; Luyk, Nicolò de; Corsi, Paolo; Sebben, Marco; Tafuri, Alessandro; Processali, Tania; Cerasuolo, Mattia; Mattevi, Daniele; Inverardi, Davide; Cerruto, Maria A.; Brunelli, Matteo; Artibani, Walter
• Is Part Of: Tumori. Volume 104:Issue 2(2018)
• Page Start: 111
• Page End: 115
• Publication Date: 2018-03
• Subjects: Gleason score system -- Prostate cancer -- Tumor grade -- Tumor upgrading; Cancer -- Periodicals; 616.994
• DOI: 10.5301/tj.5000580
• Languages: English
• ISSNs: 0300-8916

Abstract

Purpose: To identify clinical factors stratifying the risk of tumor upgrading to increasing patterns of the tumor grading system in low-risk prostate cancer (PCa). Methods: We evaluated the records of 438 patients who underwent radical prostatectomy. Associations between clinical factors and tumor upgrading were assessed by the univariate and multivariate multinomial logistic regression model. Results: Low-risk PCa included 170 cases (38.8%) and tumor upgrading was detected in 111 patients (65.3%): 72 (42.4%) had pathology Gleason pattern (pGP) 3 + 4, 27 (15.9%) pGP 4 + 3, and 12 (7.1%) pGP 4 + 4. Prostate- specific antigen (PSA) and proportion of positive cores (P+) were independent predictors of upgrading to high-risk disease. These factors also stratified the risk of tumor upgrading to the increasing patterns of the tumor grading system. The model allowed the identification of pGP 4 + 4. The main difference between high-risk PCa and other upgraded tumors related to PSA load (odds ratio 2.4) that associated with high volume disease in the specimen. Conclusions: Low-risk PCa is a heterogeneous population with significant rates of tumor upgrading. Significant clinical predictors stratifying the risk of tumor upgrading to increasing patterns of the grading system included PSA and P+. These factors allowed the identification of the subset hiding high-grade disease requiring further investigations before delivering active treatments.