From the Department of Urology (S.L., F.A.M., E.D.T., M.L.P., M.F., O.D.C., G.M.), Division of Radiology (A.C., S.A., P.E.S., F.Z., M.B.), Department of Experimental Oncology (S.R., S.V.), Division of Pathology (N.F.), and Precision Imaging and Research Unit, Department of Medical Imaging and Radiation Sciences (G.P.), European Institute of Oncology (IEO), IRCCS, Via Giuseppe Ripamonti 435, 20141 Milan, Italy; Department of Oncology and Hematology-Oncology (S.L., F.A.M., N.F., O.D.C., G.M., G.P.) and Postgraduate School in Radiodiagnostics (E.R., L.D.M., E.D., A.S., R.M.), University of Milan, Milan, Italy; and Radiology and Radiotherapy Unit, Department of Precision Medicine, University of Campania L. Vanvitelli, Naples, Italy (A.C.).
Radiology. 2023 Nov;309(2):e223349. doi: 10.1148/radiol.223349.
Background Current predictive tools to estimate the risk of biochemical recurrence (BCR) after treatment of prostate cancer do not consider multiparametric MRI (mpMRI) information. Purpose To develop a risk prediction tool that considers mpMRI findings to assess the risk of 5-year BCR after radical prostatectomy. Materials and Methods In this retrospective single-center analysis in 1459 patients with prostate cancer who underwent mpMRI before radical prostatectomy (in 2012-2015), the outcome of interest was 5-year BCR (two consecutive prostate-specific antigen [PSA] levels > 0.2 ng/mL [0.2 µg/L]). Patients were randomly divided into training (70%) and test (30%) sets. Kaplan-Meier plots were applied to the training set to estimate survival probabilities. Multivariable Cox regression models were used to test the relationship between BCR and different sets of exploratory variables. The C-index of the final model was calculated for the training and test sets and was compared with European Association of Urology, University of California San Francisco Cancer of the Prostate Risk Assessment, Memorial Sloan-Kettering Cancer Center, and Partin risk tools using the partial likelihood ratio test. Five risk categories were created. Results The median duration of follow-up in the whole cohort was 59 months (IQR, 32-81 months); 376 of 1459 (25.8%) patients had BCR. A multivariable Cox regression model (referred to as PIPEN, and composed of PSA density, International Society of Urological Pathology grade group, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extraprostatic extension score, nodes) fitted to the training data yielded a C-index of 0.74, superior to that of other predictive tools (C-index 0.70 for all models; ≤ .01) and a median higher C-index on 500 test set replications (C-index, 0.73). Five PIPEN risk categories were identified with 5-year BCR-free survival rates of 92%, 84%, 71%, 56%, and 26% in very low-, low-, intermediate-, high-, and very high-risk patients, respectively (all < .001). Conclusion A five-item model for predicting the risk of 5-year BCR after radical prostatectomy for prostate cancer was developed and internally verified, and five risk categories were identified. © RSNA, 2023 See also the editorial by Aguirre and Ortegón in this issue.
背景 目前用于预测前列腺癌治疗后生化复发 (BCR) 风险的预测工具均未考虑多参数 MRI (mpMRI) 信息。目的 开发一种考虑 mpMRI 结果的风险预测工具，以评估前列腺癌根治性前列腺切除术后 5 年 BCR 的风险。
材料与方法 本回顾性单中心研究纳入了 1459 例于 2012-2015 年接受 mpMRI 检查的前列腺癌患者，研究终点为 5 年 BCR（连续两次前列腺特异性抗原 [PSA] 水平 >0.2ng/mL[0.2μg/L]）。患者被随机分为训练集（70%）和测试集（30%）。Kaplan-Meier 图被用于训练集以评估生存概率。多变量 Cox 回归模型用于检验 BCR 与不同探索变量集之间的关系。最终模型的 C 指数在训练集和测试集进行计算，并通过似然比检验与欧洲泌尿外科学会、加利福尼亚大学旧金山分校前列腺癌风险评估、纪念斯隆-凯特琳癌症中心和 Partin 风险工具进行比较。创建了五个风险类别。
结果 全队列的中位随访时间为 59 个月（IQR，32-81 个月）；1459 例患者中有 376 例（25.8%）发生 BCR。多变量 Cox 回归模型（称为 PIPEN，由 PSA 密度、国际泌尿病理协会分级分组、前列腺影像报告和数据系统分类、欧洲泌尿生殖放射学会前列腺外延伸评分、淋巴结组成）拟合训练数据得出的 C 指数为 0.74，优于其他预测工具（所有模型的 C 指数为 0.70；≤0.01），在 500 次测试集重复中也具有更高的中位 C 指数（C 指数为 0.73）。确定了五个 PIPEN 风险类别，极低、低、中、高和极高风险患者的 5 年 BCR 无复发生存率分别为 92%、84%、71%、56%和 26%（均<0.001）。
结论 为预测前列腺癌根治性前列腺切除术后 5 年 BCR 风险，我们开发并内部验证了一种五因素模型，并确定了五个风险类别。
