Prostatic chronic inflammation and prostate cancer risk at baseline random biopsy: Analysis of predictors

Alessandro Tafuri; Marco Sebben; Giovanni Novella; Marco Pirozzi; Tania Processali; Aliasger Shakir; Riccardo Rizzetto; Nelia Amigoni; Riccardo Bernasconi; Matteo Brunelli; Maria A Cerruto; Salvatore Siracusano; Alessandro Antonelli; Walter Artibani; Antonio B Porcaro

doi:10.1080/2090598X.2020.1757335

Prostatic chronic inflammation and prostate cancer risk at baseline random biopsy: Analysis of predictors

Arab J Urol. 2020 May 13;18(3):148-154. doi: 10.1080/2090598X.2020.1757335.

Authors

Alessandro Tafuri^{1

2

3}, Marco Sebben¹, Giovanni Novella¹, Marco Pirozzi¹, Tania Processali¹, Aliasger Shakir³, Riccardo Rizzetto¹, Nelia Amigoni¹, Riccardo Bernasconi⁴, Matteo Brunelli⁴, Maria A Cerruto¹, Salvatore Siracusano¹, Alessandro Antonelli¹, Walter Artibani¹, Antonio B Porcaro¹

Affiliations

¹ Department of Urology, University of Verona, Azienda Ospedaliera Universitaria Integrata Verona, Verona, Italy.
² Department of Neuroscience, Imaging and Clinical Science, Physiology and Pathophisiology, "G. D'Annunzio" University, Chieti, Italy.
³ USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California (USC), Los Angeles, California, USA.
⁴ Department of Pathology, University of Verona, Azienda Ospedaliera Universitaria Integrata Verona, Verona, Italy.

Abstract

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.

Abbreviations: BGG: biopsy Gleason Group; BPC: biopsy positive (cancer) cores; BMI: body mass index; FGF-2: fibroblast growth factor 2; IL: interleukin; ISUP: International Society of Urologic Pathology; NIH: National Institutes of Health; OR: odds ratio; PCa: prostate cancer; PCI: prostatic chronic inflammation; TGF: transforming growth factor; TPV: total prostate volume; TZV: transition zone volume.

Keywords: Prostate cancer; prostate biopsy; prostate cancer tumour grade; prostate-specific antigen; prostatic chronic inflammation.