Salloum Osama, Taciuc Iulian-Alexandru, Dick Alexandru, Petcu Costin, Gingu Costin, Sanda Nicoleta, Marinescu Andreea Nicoleta, Serboiu Crenguta, Costache Adrian
Pathology Department, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania.
Nuclear Medicine Department, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania.
Healthcare (Basel). 2025 Sep 4;13(17):2214. doi: 10.3390/healthcare13172214.
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. 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. 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 ( < 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%. 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.
提高前列腺癌（PCa）的检测率仍然是一个关键的临床目标。虽然多参数磁共振成像（mp-MRI）融合引导活检已显示出优于系统随机活检的优势，但不同研究之间仍存在差异。本研究旨在比较融合引导活检和随机活检技术的检测率，并评估临床风险因素的综合预测价值。我们回顾性分析了138例年龄在50 - 82岁、前列腺特异性抗原（PSA）< 25 ng/mL且同时接受mp-MRI融合引导活检和系统随机活检的男性患者。采用前列腺影像报告和数据系统（PI-RADS）v2.1进行病变评估。患者数据包括PSA、前列腺体积、PI-RADS评分和年龄。评估了多重共线性，并建立了多变量逻辑回归模型。通过ROC分析评估预测性能。融合引导活检在68.1%（95%置信区间：60.3 - 75.9%）的病例中检测到癌症，随机活检为76.1%（95%置信区间：68.9 - 83.2%），联合方法为88.4%（95%置信区间：83.1 - 93.7%）。McNemar检验证实，两种方法联合使用时检测率有显著提高（< 0.001）。PSA表现出最强的个体预测能力（曲线下面积[AUC] = 0.782，95%置信区间：0.70 - 0.86），其次是前列腺体积（AUC = 0.631，95%置信区间：0.53 - 0.73）、PI-RADS评分（AUC = 0.619，95%置信区间：0.51 - 0.72）和年龄（AUC = 0.572，95%置信区间：0.46 - 0.68）。多变量模型的AUC为0.751（95%置信区间：~0.66 - 0.83），准确率为89.6%。与单独使用任何一种方法相比，融合引导活检和随机活检技术联合使用可提高前列腺癌的检测率。PSA、前列腺体积、PI-RADS评分和年龄对风险预测有独立贡献。未来的研究将致力于完善分层模型并探索家族性癌症风险因素。
