医学
列线图
无线电技术
单变量
内科学
多元分析
肿瘤科
癌症
化疗
阶段(地层学)
单变量分析
放射科
比例危险模型
多元统计
机器学习
古生物学
计算机科学
生物
作者
Junmeng Li,Chao Zhang,Jia We,Peiming Zheng,Hui Zhang,Yi Xie,Junwei Bai,Zhonglin Zhu,Kangneng Zhou,Xiaokun Liang,Yaoqin Xie,Tao Qin
出处
期刊:Social Science Research Network
[Social Science Electronic Publishing]
日期:2020-01-01
被引量:1
摘要
Background: We evaluated the ability of radiomic analysis from intratumoral and peritumoral regions on preoperative gastric cancer (GC) contrast-enhanced CT imaging to predict disease-free survival (DFS) and chemotherapy response in stage II/III GC. Methods: This study consisted of 739 consecutive patients with stage II/III GC. Within the intratumoral and peritumoral regions of CT images, a total of 584 radiomic features were computed at portal venous-phase. A radiomics signature was generated by using support vector machine (SVM)–based methods. Univariate and multivariate Cox proportional hazards model and Kaplan–Meier analysis were used to determine the association of the radiomics signature and clinicopathological variables with DFS. A radiomics nomogram combining the radiomics signature and clinicopathological findings was constructed for individualized DFS estimation. Results: The radiomics signature consisted of 26 features and were significantly associated with DFS in both the training and validation sets (both P <0.0001). Multivariate analysis demonstrated that the radiomics signature was an independent prognostic factor. The signature had higher predictive accuracy than TNM stage, single radiomics feature and clinicopathological factors. Further analysis revealed that stage II and III GC patients with high scores were likely to benefit from adjuvant chemotherapy. Conclusions: The newly developed radiomics signature is a powerful predictor of DFS, and it may predict which patients with stage II and III GC benefit from chemotherapy.Funding Statement: This study was supported by the project of Medical Service Capacity Improvement of Henan provinical (2019), and Youth project of National Natural Science Foundation of China (No.81802094).Declaration of Interests: The authors have no conflicts of interest to declare.Ethics Approval Statement: Ethical approval was obtained for this retrospective analysis at the institutional review board of the hospital, and the informed consent requirement was waived.
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