基于MRI的鹿特丹前列腺癌风险计算器应用于中国前列腺癌患者的性能评估与验证

Performance Evaluation and Validation of the Rotterdam Prostate Cancer Risk Calculator Based on MRI in Chinese Prostate Cancer Patients

目的评估鹿特丹前列腺癌风险计算器(RPCRC)在中国前列腺癌(PCa)患者人群的应用性能。方法回顾性分析2020年2月至2022年8月300例具备多参数磁共振成像(mpMRI)、前列腺特异性抗原(PSA)、直肠指检(DRE)、前列腺影像报告和数据系统(PI-RADS)评分、病理资料、病历等完整PCa患者资料,使用RPCRC(Ver.3.2.3,含MRI评估项)评估罹患PCa和临床显著性前列腺癌(csPCa)的风险,使用受试者工作特征(ROC)曲线、校准曲线和决策曲线评估其性能、校准度及临床净获益。结果最终155例纳入研究,其中43例(28%)为PCa,36例(21%)为csPCa。RPCRC对PCa风险预测的曲线下面积(AUC)(AUC=0.94)高于单独应用PI-RADS评分(AUC=0.79)和单独应用血清总前列腺特异性抗原(tPSA)(AUC=0.60),且差异有统计学意义;RPCRC对csPCa风险预测的AUC(AUC=0.91)高于单独应用PI-RADS评分(AUC=0.86)和单独应用tPSA(AUC=0.65),且差异有统计学意义;RPCRC对PCa和csPCa风险预测的AUC间差异没有统计学意义(P>0.05)。校准曲线显示RPCRC对概率的估计没有明显的系统性偏倚。决策曲线显示RPCRC预测PCa的表现好于预测csPCa。结论RPCRC在预测中国人群PCa及csPCa风险方面有很好的表现,有利于扩大PCa筛查范围,助力PCa的早期诊断、合理治疗,但其对于csPCa的预测能力略低于Pca,在csPCa的准确预测和避免过度干预方面还有待进一步改进。

Objective To evaluate the performance of the Rotterdam Prostate Cancer Risk Calculator(RPCRC)in Chinese prostate cancer patients.Methods A retrospective analysis was performed on 300 Chinese cases from February 2020to August 2022 with comprehensive data,including multiparametric Magnetic Resonance Imaging(mpMRI),Prostate Specific Antigen(PSA),Digital Rectal Examination(DRE),PI-RADS score,pathological data,and medical records.The RPCRC(Ver.3.2.3,incorporating MRI evaluation)was used to assess the risk of developing Prostate Cancer(PCa)and Clinically Significant Prostate Cancer(csPCa).The ROC curve,calibration curve,and decision curve were used to evaluate its performance,calibration,and clinical net benefit.Results Out of the cases,155 were included in the study,of which43(28%)were diagnosed with PCa and 36(21%)with csPCa.The AUC of RPCRC for predicting PCa risk(0.94)was significantly higher than using PI-RADS score alone(0.79)and using tPSA alone(0.60).The AUC of RPCRC for predicting csPCa risk(0.91)was significantly higher than using PIRADS score alone(0.86)and using tPSA alone(0.65).There was no statistically significant difference in the AUCs of RPCRC for predicting PCa and csPCa risks(P>0.05).The calibration curve revealed that the RPCRC s estimation of probabilities did not have significant systematic biases.The decision curve showed that RPCRC performed better in predicting PCa than csPCa.Conclusion The RPCRC performs well in predicting the risks of PCa and csPCa in the Chinese population,facilitating the expansion of prostate cancer screening and aiding early diagnosis and rational treatment of prostate cancer.However,its predictive ability for csPCa is slightly lower than for PCa,and further improvements are needed for accurate prediction of csPCa and to avoid overtreatment.