Liu Haohan, Yan Yongcong, Chen Ruibing, Zhu Mengdi, Lin Jianhong, He Chuanchao, Shi Bingchao, Wen Kai, Mao Kai, Xiao Zhiyu
1Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120 China.
2Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120 China.
Cancer Cell Int. 2020 Apr 29;20:140. doi: 10.1186/s12935-020-01216-9. eCollection 2020.
The primary tumor, regional lymph nodes and distant metastasis (TNM) stage is an independent risk factor for 1-year hepatocellular carcinoma (HCC) recurrence but has insufficient predictive efficiency. We attempt to develop and validate a nomogram to predict 1-year recurrence in HCC and improve the predictive efficiency of the TNM stage.
A total of 541 HCC patients were enrolled in the study. The risk score (RS) model was established with the logistic least absolute shrinkage and selector operation algorithm. The predictive nomogram was further validated in the internal testing cohort and external validation cohort. The area under the receiver operating characteristic curves (AUCs), decision curves and clinical impact curves were used to evaluate the predictive accuracy and clinical value of the nomogram.
In the training cohort, we identified a RS model consisting of five stage-related genes (NUP62, EHMT2, RANBP1, MSH6 and FHL2) for recurrence at 1 year. The 1-year disease-free survival of patients was worse in the high-risk group than in the low-risk group (< 0.0001), and 1-year recurrence was more likely in the high-risk group (Hazard ratio: 3.199, < 0.001). The AUC of the nomogram was 0.739, 0.718 and 0.693 in the training, testing and external validation cohort, respectively, and these values were larger than the corresponding AUC of the TNM stage (0.681, 0.688 and 0.616, respectively).
A RS model consisting of five stage-related genes was successfully identified for predicting 1-year HCC recurrence. Then, a novel nomogram based on the RS model and TNM stage to predict 1-year HCC recurrence was also developed and validated.
原发性肿瘤、区域淋巴结和远处转移(TNM)分期是肝细胞癌(HCC)1年复发的独立危险因素,但预测效率不足。我们试图开发并验证一种列线图,以预测HCC的1年复发情况,并提高TNM分期的预测效率。
本研究共纳入541例HCC患者。采用逻辑最小绝对收缩和选择算子算法建立风险评分(RS)模型。在内部测试队列和外部验证队列中进一步验证预测列线图。采用受试者操作特征曲线下面积(AUC)、决策曲线和临床影响曲线来评估列线图的预测准确性和临床价值。
在训练队列中,我们确定了一个由五个与分期相关的基因(NUP62、EHMT2、RANBP1、MSH6和FHL2)组成的RS模型,用于预测1年复发情况。高危组患者的1年无病生存率低于低危组(<0.0001),高危组1年复发的可能性更大(风险比:3.199,<0.001)。列线图在训练、测试和外部验证队列中的AUC分别为0.739、0.718和0.693,这些值均大于TNM分期相应的AUC(分别为0.681、0.688和0.616)。
成功确定了一个由五个与分期相关的基因组成的RS模型,用于预测HCC的1年复发情况。然后,还开发并验证了一种基于RS模型和TNM分期的新型列线图,用于预测HCC的1年复发情况。