A novel nomogram to predict clinically significant prostate cancer in MR assisted lesion biopsies: Turkish urooncology association nomogram

Abstract

ObjectiveThis study aimed to develop a novel nomogram to predict clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion biopsies, addressing the challenges in deciding on biopsy for patients with PI-RADS 3 lesions and follow-up strategies for patients with negative PI-RADS 4 or 5 lesions. Materials and methodsA retrospective case-control study was conducted using the Turkish Urooncology Association Databases (UROCaD). The final dataset included 2428 lesion biopsy data. Univariate analysis, logistic regression, and validation were performed, with 1942 and 486 lesion biopsy data in the training and validation datasets, respectively. ResultsAge, initial total PSA value, PSA density, prostate volume, lesion length, DRE findings, and PI-RADS score were significantly different between benign or non-significant cancer and clinically significant prostate cancer groups. The developed nomogram incorporated PSA density, age, PI-RADS score, lesion length, and DRE findings. The mean area under the curve for the 6-fold cross-validation was 0.836, while the area under the curve values for the training and validation datasets were 0.827 and 0.861, respectively. The nomogram demonstrated a sensitivity of 75.6% and a specificity of 74.8% at a cut-off score of 24.9, with positive and negative predictive values of 42.2% and 92.6%, respectively. ConclusionThe TUA nomogram, based on PSA density, age, PI-RADS score, lesion length, and DRE findings, provides a reliable and accurate prediction tool for detecting clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion (fusion) biopsies, potentially improving patient management and reducing unnecessary biopsies.