Incorporating Lower Urinary Tract Symptoms to Predict the Risk of Positive Prostate Magnetic Resonance Imaging.

Area of Science:

• Urology
• Oncology
• Medical Imaging

Background:

• Many men referred for prostate cancer (PCa) screening via magnetic resonance imaging (MRI) have normal results, indicating a need for better risk stratification.
• Optimizing the referral process in primary care can decrease unnecessary hospital visits and MRI procedures.

Purpose of the Study:

• To develop a predictive model using the International Prostate Symptom Score (IPSS) to enhance MRI risk stratification for biopsy-naïve men with suspected PCa.
• To reduce the number of unnecessary referrals and MRIs in primary care settings.

Main Methods:

• A prospective cohort of men with suspected PCa was identified in a Dutch teaching hospital (2022-2023).
• The study included upfront biparametric MRI and IPSS, excluding men with abnormal digital rectal examinations (DRE).
• Multivariable logistic regression identified predictors of Prostate Imaging Reporting and Data System (PI-RADS) ≥ 4, with model performance assessed by AUC and clinical utility by decision curve analysis.

Main Results:

• In the development cohort (334 men), 30% had PI-RADS ≥ 4, with 59% of these having significant PCa (ISUP grade group ≥ 2).
• Prostate-specific antigen (PSA) and IPSS were independent predictors of PI-RADS ≥ 4 (AUC = 0.68).
• At a 20% threshold, the model could avoid 23% of MRIs, with a 3.9% referral rate for patients with positive MRIs, including eight missed significant PCa cases.

Conclusions:

• Integrating IPSS into primary care risk stratification for suspected PCa in biopsy-naïve men improves diagnostic accuracy.
• This approach offers a practical method to optimize diagnostic pathways and reduce unnecessary MRI utilization.