Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.
Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
J Urol. 2020 Feb;203(2):292-298. doi: 10.1097/JU.0000000000000518. Epub 2019 Sep 3.
We sought to develop a triage strategy to reduce negative and indeterminate multiparametric magnetic resonance imaging scans in patients at risk for prostate cancer.
In this retrospective study we evaluated 865 patients with no prior prostate cancer diagnosis who underwent prostate multiparametric magnetic resonance imaging between 2009 and 2017. Age, prostate volume, prostate specific antigen and prostate specific antigen density were assessed as predictors of positive multiparametric magnetic resonance imaging, defined as PI-RADS™ (Prostate Imaging Reporting and Data System) version 2/Likert score 4 or greater. The cohort was split into a training cohort of 605 patients and a validation cohort of 260. The optimal threshold to rule out positive multiparametric magnetic resonance imaging was chosen to achieve a negative predictive value greater than 90%.
All clinical variables were significant predictors of positive multiparametric magnetic resonance imaging (p <0.05). Prostate specific antigen density outperformed other parameters in diagnostic accuracy and did not significantly differ compared to a multivariate model (AUC=0.74 vs 0.75). At prostate specific antigen density greater than 0.078 ng/ml sensitivity, specificity, positive and negative predictive values were 94%, 29%, 22% and 95%, respectively, resulting in 25% fewer scans (64 of 260). In the multivariate model sensitivity, specificity, positive and negative predictive values were 85%, 32%, 22% and 91%, respectively, resulting in 29% fewer scans (75 of 260). Biopsies in men who would not have undergone multiparametric magnetic resonance imaging according to our proposed strategies revealed 2 clinically significant prostate cancers using prostate specific antigen density and 1 using the multivariate model.
In patients at risk for prostate cancer applying a multivariate prediction model or a prostate specific antigen density cutoff of 0.078 ng/ml resulted in 25% to 29% fewer multiparametric magnetic resonance imaging scans performed while missing only a minimal number of clinically significant prostate cancers. Further prospective validation is required.
我们旨在制定一种分诊策略，以减少前列腺癌风险患者的阴性和不确定的多参数磁共振成像扫描。
在这项回顾性研究中，我们评估了 2009 年至 2017 年间接受前列腺多参数磁共振成像检查的 865 例无前列腺癌既往病史的患者。年龄、前列腺体积、前列腺特异性抗原和前列腺特异性抗原密度被评估为多参数磁共振成像阳性的预测因素，定义为 PI-RADS™（前列腺成像报告和数据系统）版本 2/利克特评分 4 或更高。该队列分为训练队列 605 例和验证队列 260 例。选择排除多参数磁共振成像阳性的最佳阈值，以获得大于 90%的阴性预测值。
所有临床变量均为多参数磁共振成像阳性的显著预测因素（p<0.05）。前列腺特异性抗原密度在诊断准确性方面优于其他参数，与多变量模型相比差异无统计学意义（AUC=0.74 比 0.75）。前列腺特异性抗原密度大于 0.078ng/ml 时，灵敏度、特异性、阳性和阴性预测值分别为 94%、29%、22%和 95%，可减少 25%的扫描（260 例中有 64 例）。在多变量模型中，灵敏度、特异性、阳性和阴性预测值分别为 85%、32%、22%和 91%，可减少 29%的扫描（260 例中有 75 例）。根据我们提出的策略，在多参数磁共振成像中未行前列腺特异性抗原密度或多变量模型的男性中，活检发现 2 例临床显著前列腺癌。
在前列腺癌风险患者中，应用多变量预测模型或前列腺特异性抗原密度截断值 0.078ng/ml 可减少 25%至 29%的多参数磁共振成像扫描，而仅遗漏少数临床显著前列腺癌。需要进一步前瞻性验证。
