Diagnostic Yield of Fusion-Guided and Randomized Biopsies in Prostate Cancer: Evidence for an Integrated Approach

Background/Objectives: Improving prostate cancer (PCa) detection remains a key clinical goal. While multiparametric MRI (mp-MRI) fusion-guided biopsy has shown advantages over systematic randomized biopsy, variability persists across studies. This study aimed to compare detection rates between fusion-guided and randomized biopsy techniques and assess the combined predictive value of clinical risk factors. Methods: We retrospectively analyzed 138 male patients aged 50-82 years with PSA (prostate-specific antigen) < 25 ng/mL, undergoing both mp-MRI fusion-guided and systematic randomized biopsies. PI-RADS v2.1 was used for lesion assessment. The patient data included PSA, prostate volume, PI-RADS score, and age. Multicollinearity was evaluated, and a multivariate logistic regression model was developed. ROC analysis assessed predictive performance. Results: Fusion-guided biopsy detected cancer in 68.1% (95% CI: 60.3-75.9%) of cases, randomized biopsy in 76.1% (95% CI: 68.9-83.2%), and the combined approach in 88.4% (95% CI: 83.1-93.7%). McNemar's test confirmed a significant improvement when combining both methods (p < 0.001). PSA exhibited the strongest individual predictive power (AUC = 0.782, 95% CI: ~0.70-0.86), followed by prostate volume (AUC = 0.631, 95% CI: ~0.53-0.73), PI-RADS score (AUC = 0.619, 95% CI: ~0.51-0.72), and age (AUC = 0.572, 95% CI: ~0.46-0.68). The multivariate model achieved an AUC of 0.751 (95% CI: ~0.66-0.83) and an accuracy of 89.6%. Conclusions: Combining fusion-guided and randomized biopsy techniques enhances prostate cancer detection compared with either method alone. PSA, prostate volume, PI-RADS score, and age contribute independently to risk prediction. Future studies will aim to refine stratification models and explore familial cancer risk factors.