Background: Evidence to help avoid unnecessary prostate biopsies is being actively pursued. Our goal was to develop and internally validate a nomogram for predicting clinically significant prostate cancer (csPC) in men with low suspicion of disease (prostate specific antigen [PSA] < 10 ng/mL, normal digital rectal examination [DRE]), in whom magnetic resonance imaging (MRI) findings are positive. Methods: Patients with no prior prostate cancer diagnosis who underwent MRI–ultrasound fusion biopsy of the prostate were retrospectively analyzed. Inclusion criteria were PSA < 10 ng/mL, normal DRE, Prostate Imaging Reporting And Data System (PIRADS) category ≥ 3, and no extraprostatic extension or seminal vesicle invasion reported on MRI. Associations between csPC diagnosis and patient or lesion characteristics were analyzed, and a multivariable model was developed. Internal validation of the model with 5-fold cross-validation and bootstrapping methods was performed. Results: Among 209 patients, 67 were diagnosed with csPC. Factors incorporated into the model for predicting csPC were age, 5-alpha reductase inhibitor use, PSA, prostate volume, PIRADS > 3, and lesion location in the peripheral zone. The model’s ROC AUC was 0.86, with consistent performance at internal validation (0.84 with cross-validation, 0.82 with bootstrapping). With an empirical threshold of <10% csPC probability to omit biopsy, 72 (50.7%) unnecessary biopsies would have been avoided, at the cost of missing 2 (3.0%) csPC cases. Conclusions: Our nomogram might serve as a valuable tool in refining selection criteria in men considered for prostate biopsy. The major limitation of the study is its retrospective character. Prospective, external validation of the model is warranted.
背景：目前学界正积极寻求避免不必要前列腺活检的证据支持。本研究旨在开发并内部验证一种列线图模型，用于预测疾病低度可疑（前列腺特异性抗原[PSA]＜10 ng/mL、直肠指检正常）但磁共振成像结果阳性的临床显著性前列腺癌患者。方法：回顾性分析既往无前列腺癌诊断史且接受磁共振-超声融合靶向活检的患者。纳入标准包括PSA＜10 ng/mL、直肠指检正常、前列腺影像报告和数据系统评分≥3分，且磁共振成像未报告前列腺外侵犯或精囊侵犯。通过分析临床显著性前列腺癌诊断与患者或病灶特征的关联性，建立多变量预测模型，并采用五折交叉验证和自助法进行内部验证。结果：在209例患者中，67例确诊临床显著性前列腺癌。最终纳入预测模型的变量包括年龄、5α-还原酶抑制剂使用情况、PSA值、前列腺体积、前列腺影像报告和数据系统评分＞3分以及外周带病灶位置。模型受试者工作特征曲线下面积为0.86，内部验证显示性能稳定（交叉验证0.84，自助法验证0.82）。以＜10%临床显著性前列腺癌概率作为避免活检的实证阈值时，可避免72例（50.7%）不必要活检，代价是漏诊2例（3.0%）临床显著性前列腺癌。结论：本列线图模型可作为优化前列腺活检患者筛选标准的重要工具。本研究主要局限在于回顾性设计，需开展前瞻性外部验证以进一步确认模型效能。
肿瘤(癌症)患者之家