Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China.
School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong Province, China.
Int J Surg. 2022 Sep;105:106889. doi: 10.1016/j.ijsu.2022.106889. Epub 2022 Sep 6.
Gastric cancer (GC) is a major health problem worldwide, with high prevalence and mortality. The present GC staging system provides inadequate prognostic information and does not reflect the chemotherapy benefit of GC.
Two hundred fifty-five patients who underwent surgical resection were enrolled in our study (training cohort = 212, internal validation cohort = 43). Nine clinicopathologic features were obtained to construct an support vector machine (SVM) model. The cohorts from 4 domestic centres and The Cancer Genome Atlas (TCGA) were used for external validation.
In the training cohort, the AUCs were 0.773 (95% CI 0.708-0.838) for 5-year overall survival (OS) and 0.751 (95% CI 0.683-0.820) for 5-year disease-free survival (DFS); in the domestic validation cohort, the AUCs were 0.852 (95% CI 0.810-0.894) and 0.837 (95% CI 0.792-0.882), respectively. The model performed better than the TNM staging system according to the receiver operator characteristic(ROC) curve. GC patients were significantly divided into low, moderate and high risk based on the SVM. High-risk TNM stage Ⅱ and Ⅲ patients were more likely to benefit from adjuvant chemotherapy than low-risk patients.
The SVM-based model may be used to predict OS and DFS in GC patients and the benefit of adjuvant chemotherapy in TNM stage Ⅱ and Ⅲ GC patients.
胃癌（GC）是全球范围内的一个主要健康问题，具有较高的患病率和死亡率。目前的 GC 分期系统提供的预后信息不足，并且不能反映 GC 的化疗获益。
本研究纳入了 255 例接受手术切除的患者（训练队列=212 例，内部验证队列=43 例）。获得了 9 种临床病理特征来构建支持向量机（SVM）模型。来自 4 个国内中心和癌症基因组图谱（TCGA）的队列用于外部验证。
在训练队列中，5 年总生存率（OS）和 5 年无病生存率（DFS）的 AUC 分别为 0.773（95%CI 0.708-0.838）和 0.751（95%CI 0.683-0.820）；在国内验证队列中，AUC 分别为 0.852（95%CI 0.810-0.894）和 0.837（95%CI 0.792-0.882）。根据接受者操作特征（ROC）曲线，该模型的性能优于 TNM 分期系统。根据 SVM，GC 患者可明显分为低、中和高危。高危 TNM Ⅱ期和Ⅲ期患者比低危患者更有可能从辅助化疗中获益。
SVM 模型可用于预测 GC 患者的 OS 和 DFS，以及 TNM Ⅱ期和Ⅲ期 GC 患者辅助化疗的获益。
