Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort study

PURPOSE: We aim to examine the long-term outcomes of patients who underwent multiparametric prostate magnetic resonance imaging (mp-MRI) for suspected prostate cancer (PCa), specifically based on their initial Prostate Imaging Reporting and Data System (PI-RADS) categories and various clinical factors. Our secondary aim is to evaluate the prognostic value of the PI-RADS through the National Comprehensive Cancer Network (NCCN) risk group distribution. METHODS: This research was conducted as a single-center retrospective cohort study in a tertiary care hospital. A total of 1,359 cases having at least one histopathological examination after the initial mp-MRI and/or adequate clinical/radiological follow-up data were included in the clinically significant PCa (cs-PCa) diagnosis-free survival analysis. Initial mp-MRI dates were accepted as the start of follow-up for the time-to-event analysis. The event was defined as cs-PCa diagnosis (International Society of Urological Pathology ≥2). Patients who were not diagnosed with cs-PCa during follow-up were censored according to predefined literature-based criteria at the end of the maximum follow-up duration with no reasonable suspicion of PCa and no biopsy indication. The impact of various factors on survival was assessed using a log-rank test and multivariable Cox regression. Subsequently, 394 cases diagnosed with PCa during follow-up were evaluated, based on initial PI-RADS categories and NCCN risk groups. RESULTS: = 0.005). CONCLUSION: The PI-RADS category has a significant impact on patient management and provides important diagnostic and prognostic information. Higher initial PI-RADS categories are associated with decreased follow-up losses, a shorter time to PCa diagnosis, increased biopsy rates, a higher likelihood of developing cs-PCa during follow-up, and a worse PCa prognosis. Combining mPSAD with PI-RADS categories could enhance diagnostic stratification in the identification of cs-PCa.