Ruan Xiaohao, Huang Da, Huang Jingyi, Huang Jinlun, Zhan Yongle, Wu Yishuo, Ding Qiang, Xu Danfeng, Jiang Haowen, Xue Wei, Na Rong
Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Division of Urology, Department of Surgery, The University of Hong Kong, Hong Kong, China.
J Clin Med. 2023 Feb 8;12(4):1343. doi: 10.3390/jcm12041343.
To date, the combined effect of polygenic risk score (PRS) and prostate health index () on PCa diagnosis in men undergoing prostate biopsy has never been investigated. A total of 3166 patients who underwent initial prostate biopsy in three tertiary medical centers from August 2013 to March 2019 were included. PRS was calculated on the basis of the genotype of 102 reported East-Asian-specific risk variants. It was then evaluated in the univariable or multivariable logistic regression models that were internally validated using repeated 10-fold cross-validation. Discriminative performance was assessed by area under the receiver operating curve (AUC) and net reclassification improvement (NRI) index. Compared with men in the first quintile of age and family history adjusted PRS, those in the second, third, fourth, and fifth quintiles were 1.86 (odds ratio, 95% confidence interval (CI): 1.34-2.56), 2.07 (95%CI: 1.50-2.84), 3.26 (95%CI: 2.36-4.48), and 5.06 (95%CI: 3.68-6.97) times as likely to develop PCa (all < 0.001). Adjustment for other clinical parameters yielded similar results. Among patients with prostate-specific antigen (PSA) at 2-10 ng/mL or 2-20 ng/mL, PRS still had an observable ability to differentiate PCa in the group of prostate health index () at 27-36 ( < 0.05) or >36 ( ≤ 0.001). Notably, men with moderate (27-36) but highest PRS (top 20% percentile) would have a comparable risk of PCa (positive rate: 26.7% or 31.3%) than men with high (>36) but lowest PRS (bottom 20% percentile positive rate: 27.4% or 34.2%). The combined model of PRS, , and other clinical risk factors provided significantly better performance (AUC: 0.904, 95%CI: 0.887-0.921) than models without PRS. Adding PRS to clinical risk models could provide significant net benefit (NRI, from 8.6% to 27.6%), especially in those early onset patients (NRI, from 29.2% to 44.9%). PRS may provide additional predictive value over for PCa. The combination of PRS and that effectively captured both clinical and genetic PCa risk is clinically practical, even in patients with gray-zone PSA.
迄今为止,多基因风险评分(PRS)和前列腺健康指数()对接受前列腺活检的男性前列腺癌(PCa)诊断的联合影响从未被研究过。纳入了2013年8月至2019年3月在三个三级医疗中心接受初次前列腺活检的3166例患者。PRS是根据102个报道的东亚特异性风险变异的基因型计算得出的。然后在单变量或多变量逻辑回归模型中进行评估,这些模型通过重复10倍交叉验证进行内部验证。通过受试者操作特征曲线下面积(AUC)和净重新分类改善(NRI)指数评估判别性能。与年龄和家族史调整后的PRS处于第一五分位数的男性相比,处于第二、第三、第四和第五五分位数的男性患PCa的可能性分别为1.86倍(优势比,95%置信区间(CI):1.34 - 2.56)、2.07倍(95%CI:1.50 - 2.84)、3.26倍(95%CI:2.36 - 4.48)和5.06倍(95%CI:3.68 - 6.97)(所有P < 0.001)。对其他临床参数进行调整后得到了相似的结果。在前列腺特异性抗原(PSA)为2 - 10 ng/mL或2 - 20 ng/mL的患者中,在前列腺健康指数()为27 - 36(P < 0.05)或>36(P ≤ 0.001)的组中,PRS仍具有区分PCa的可观察能力。值得注意的是,前列腺健康指数中等(27 - 36)但PRS最高(前20%百分位数)的男性患PCa的风险(阳性率:26.7%或31.3%)与前列腺健康指数高(>36)但PRS最低(后20%百分位数阳性率:27.4%或34.2%)的男性相当。PRS、和其他临床风险因素的联合模型比不包含PRS的模型表现显著更好(AUC:0.904,95%CI:0.887 - 0.921)。将PRS添加到临床风险模型中可提供显著的净效益(NRI,从8.6%至27.6%),尤其是在那些早发患者中(NRI,从29.2%至44.9%)。PRS可能比在PCa预测方面提供额外的价值。PRS和的组合有效地捕捉了临床和遗传性PCa风险,在临床上是实用的,即使在PSA处于灰色区域的患者中也是如此。