Probabilistic ratiocination of hepatocellular carcinoma after resection: evaluation of expected to be promising approaches.
Probabilistic ratiocination of hepatocellular carcinoma after resection: evaluation of expected to be promising approaches.
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肝细胞癌切除后的概率推理：评估预期有前途的方法
DOI：
10.21037/atm-20-4828
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发表时间：
2021-05
影响因子：
--
通讯作者：
Liu H
中科院分区：
文献类型：
--
作者：
Dong W;Guo X;Liu F;Zhang W;Wang Z;Tian T;Tao Q;Hou G;Zhou W;Jeong S;Xia Q;Liu H
背景：对于病死率较高的疾病，准确预测治疗后的生存时间具有重要意义。RNA测序数据和深度学习方法有望成为未来预测模型发展的有前途的方法。我们的目标是评估手术切除的肝细胞癌患者的最佳协变量和方法学。方法应用COX比例风险回归模型和DL方法建立包含临床变量、遗传变量以及临床和遗传变量的预测模型，用于预测肝细胞癌切除术后患者的生存。分别来自东方肝胆外科医院和仁济医院的2163例和601例患者中，共有1114例和184例患者进入本研究。这些模型通过随机抽样进行了内部验证，并在临床队列中进行了外部验证。模型间的比较从综合判别改善和净重分类指数两个方面进行。结果分别采用7个独立的预后因素(总胆红素、凝血酶原时间、肿瘤大小、肿瘤个数、淋巴结转移、血管侵犯)和22个临床因素建立了COX和DL临床模型。在推导[曲线下面积(AUC)：0.75比0.77]和验证(AUC：0.83比0.80)集方面，COX临床模型和DL临床模型都表现出了优异的表现。包含6个显著预后基因的COX遗传模型不如包含686个基因的DL模型有效。临床和遗传学相结合的方法改进了COX和DL模型的性能。DL临床模型的综合辨别力改善和净重分类指数总体上好于Cox临床模型。结论我们的COX临床模型能够为肝细胞癌切除术后患者的生存提供准确的预测。它可以作为一种准确和经济的工具来预测此类患者的生存。
Background Precise prediction of survival after treatment is of great importance for patients with diseases with high mortality. RNA sequencing data and deep learning (DL) methods are expected to become promising approaches in the development of prediction models in the future. We aimed to evaluate the optimal covariates and methodology for patients with hepatocellular carcinoma (HCC) undergoing surgical resection. Methods The Cox proportional hazards regression model and the DL approach were used to develop prediction models incorporating clinical, genetic, and combined clinical and genetic variables for survival prediction in patients with HCC after resection. A total of 1,114 patients and 184 patients were enrolled in the present study from 2,163 and 601 patients from Eastern Hepatobiliary Surgery Hospital and Renji Hospital, respectively. The models were internally validated through random sampling and externally validated in clinical cohorts. Between-model comparisons were carried out in terms of the integrated discrimination improvement and net reclassification index. Results The Cox and DL clinical models were developed by adopting 7 independent prognostic factors (total bilirubin, prothrombin time, tumor size, tumor number, lymph node metastasis, and vascular invasion) and 22 clinical factors, respectively. Both the Cox clinical model and the DL clinical model showed excellent performances in the derivation [area under the curve (AUC): 0.75 vs. 0.77] and validation (AUC: 0.83 vs. 0.80) sets. The derived Cox genetic model with 6 significant prognostic genes was not as effective as the DL approach involving 686 genes. A combined clinical and genetic approach modified the performances of both the Cox and DL models. The integrated discrimination improvement and net reclassification index of the DL clinical model were generally better than those of the Cox clinical model. Conclusions Our Cox clinical model sufficiently provided precise survival prediction in patients with HCC after resection. It may serve as an accurate and cost-effective tool for predicting survival in such patients.
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影响因子：
2.6
作者：
Flatley, Christopher;Gibbons, Kristen;Kumar, Sailesh
通讯作者：
Kumar, Sailesh
影响因子：
--
作者：
Jia, Xiaona;Baig, Mirza Mansoor;GholamHosseini, Hamid
通讯作者：
GholamHosseini, Hamid
影响因子：
3.2
作者：
Beal, Eliza W.;Mehta, Rittal;Pawlik, Timothy M.
通讯作者：
Pawlik, Timothy M.
影响因子：
2.9
作者：
Yang, Hui;Zhou, Li;Qian, Jun
通讯作者：
Qian, Jun
用于术前预测结直肠癌淋巴结转移的放射组学列线图的开发和验证
影响因子：
45.3
作者：
Huang, Yan-qi;Liang, Chang-hong;Liu, Zai-yi
通讯作者：
Liu, Zai-yi