Foggia Prostate Cancer Risk Calculator 2.0: A Novel Risk Calculator including MRI and Bladder Outlet Obstruction Parameters to Reduce Unnecessary Biopsies

Author:

Falagario Ugo Giovanni1,Busetto Gian Maria1ORCID,Recchia Marco1,Tocci Edoardo1,Selvaggio Oscar1,Ninivaggi Antonella1,Milillo Paola2,Macarini Luca2,Sanguedolce Francesca3,Mancini Vito1,Annese Pasquale1,Bettocchi Carlo1,Carrieri Giuseppe1,Cormio Luigi14

Affiliation:

1. Department of Urology and Organ Transplantation, University of Foggia, 71122 Foggia, Italy

2. Department of Radiology, University of Foggia, 71122 Foggia, Italy

3. Department of Pathology, University of Foggia, 71122 Foggia, Italy

4. Department of Urology, Bonomo Teaching Hospital, 76123 Andria, Italy

Abstract

Risk calculator (RC) combining PSA with other clinical information can help to better select patients at risk of prostate cancer (PCa) for prostate biopsy. The present study aimed to develop a new Pca RC, including MRI and bladder outlet obstruction parameters (BOOP). The ability of these parameters in predicting PCa and clinically significant PCa (csPCa: ISUP GG ≥ 2) was assessed by binary logistic regression. A total of 728 patients were included from two institutions. Of these, 395 (54.3%) had negative biopsies and 161 (22.11%) and 172 (23.6%) had a diagnosis of ISUP GG1 PCa and csPCa. The two RC ultimately included age, PSA, DRE, prostate volume (pVol), post-voided residual urinary volume (PVR), and PIRADS score. Regarding BOOP, higher prostate volumes (csPCa: OR 0.98, CI 0.97,0.99) and PVR ≥ 50 mL (csPCa: OR 0.27, CI 0.15, 0.47) were protective factors for the diagnosis of any PCa and csPCa. AUCs after internal validation were 0.78 (0.75, 0.82) and 0.82 (0.79, 0.86), respectively. Finally, decision curves analysis demonstrated higher benefit compared to the first-generation calculator and MRI alone. These novel RC based on MRI and BOOP may help to better select patient for prostate biopsy after prostate MRI.

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

Reference27 articles.

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2. Do prostate cancer risk models improve the predictive accuracy of PSA screening? A meta-analysis;Louie;Ann. Oncol.,2015

3. Mottet, N., van den Bergh, R.C.N., Briers, E., Cornford, P., De Santis, M., Fanti, S., Gillessen, S., Grummet, J., Henry, A.M., and Lam, T.B. (2020, January 20–24). EAU—ESTRO—ESUR—SIOG Guidelines on Prostate Cancer 2020. European Association of Urology Guidelines 2020 Edition. Proceedings of the EAU Annual Congress Amsterdam 2020, Amsterdam, The Netherlands.

4. A 4K score/MRI-based nomogram for predicting prostate cancer, clinically significant prostate cancer, and unfavorable prostate cancer;Wagaskar;Cancer Rep.,2021

5. Presence and severity of lower urinary tract symptoms are inversely correlated with the risk of prostate cancer on prostate biopsy;Cicione;Minerva Urol. Nefrol.,2017

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