Objective: To evaluate predictors of prostatic chronic inflammation (PCI) and prostate cancer (PCa) in patients undergoing transperineal baseline random prostatic needle biopsies (BNB). Patient and methods: According to BNB outcomes, patients were divided into four groups: cases without PCI or PCa (Control group), cases with PCI only (PCI group), cases with PCa and PCI (PCa+PCI group) and cases with PCa only (PCa group). A multinomial logistic regression model was used to evaluate the association of clinical factors with BNB outcomes. Additionally, clinical factors associated with the risk of PCa in the overall population were investigated using a multivariable logistic regression model (univariate and multivariate analysis). Results: Overall, 945 patients were evaluated and grouped as follows: Control group, 308 patients (32.6%); PCI group, 160 (16.9%); PCa+PCI group, 45 (4.8%); and PCa group, 432 (45.7%). Amongst these, PCa was independently predicted by age (odds ratio [OR] 1.081), prostate specific-antigen level (PSA; OR 1.159), transition zone volume (TZV; OR 0.916), and abnormal digital rectal examination (DRE; OR 1.962). PCa and PCI (4.8%) were independently predicted by age (OR 1.081), PSA level (OR 1.122) and TZV (OR 0.954). In the group without PCa, the PSA level was the only factor associated with the risk of PCI when compared to the control group (OR 1.051, P = 0.042). Among patients with PCa, independent factors associated with the risk of only PCa compared to cases with PCA+PCI were TZV (OR 0.972) and number of positive cores (OR 1.149). In the overall population, PCI was the strongest predictor of a decreased risk of PCa (multivariate model, OR 0.212; P < 0.001) Conclusions: At BNB, PCI was associated with both a decreased risk of PCa and less aggressive tumour biology amongst patients with PCa. The presence of PCI on biopsy cores should be reported because of its implications in clinical practice.
|Titolo:||Prostatic chronic inflammation and prostate cancer risk at baseline random biopsy: Analysis of predictors|
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||01.01 Articolo in Rivista|