Du Qian-Cheng, Wang Xin-Yu, Hu Cheng-Kai, Zhou Ling, Fu Zheng, Liu Shun, Wang Jian, Ma Ying-Ying, Liu Meng-Yao, Yu Hua
Department of Thoracic Surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Department of General Surgery, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
World J Clin Cases. 2022 Nov 26;10(33):12077-12088. doi: 10.12998/wjcc.v10.i33.12077.
Every year, esophageal cancer is responsible for 509000 deaths and around 572000 new cases worldwide. Although esophageal cancer treatment options have advanced, patients still have a dismal 5-year survival rate.
To investigate the relationship between genes associated to platelets and the prognosis of esophageal cancer.
We searched differentially expressed genes for changes between 151 tumor tissues and 653 normal, healthy tissues using the "limma" package. To develop a prediction model of platelet-related genes, a univariate Cox regression analysis and least absolute shrinkage and selection operator Cox regression analysis were carried out. Based on a median risk score, patients were divided into high-risk and low-risk categories. A nomogram was created to predict the 1-, 2-, and 3-year overall survival (OS) of esophageal cancer patients using four platelet-related gene signatures, TNM stages, and pathological type. Additionally, the concordance index, receiver operating characteristic curve, and calibration curve were used to validate the nomogram.
The prognosis of esophageal cancer was associated to , , , and according to univariate Cox regression analysis and least absolute shrinkage and selection operator regression analysis. Patients with esophageal cancer at high risk had substantially shorter OS than those with cancer at low risk, according to a Kaplan-Meier analysis ( < 0.05). TNM stage (hazard ratio: 2.187, 95% confidence interval: 1.242-3.852, = 0.007) in both univariate and multivariate Cox regression and risk score were independently correlated with OS (hazard ratio: 2.451, 95% confidence interval: 1.599-3.756, 0.001).
A survival risk score model and independent prognostic variables for esophageal cancer have been developed using , , , and . OS for esophageal cancer might be predicted using the nomogram based on TNM stage, pathological type, and risk score. The nomogram demonstrated strong predictive ability, as shown by the concordance index, receiver operating characteristic curve, and calibration curve.
每年，食管癌在全球导致509000人死亡，约572000例新发病例。尽管食管癌的治疗方案有所进步，但患者的5年生存率仍然很低。
研究与血小板相关基因和食管癌预后之间的关系。
我们使用“limma”软件包在151个肿瘤组织和653个正常健康组织之间搜索差异表达基因。为了建立血小板相关基因的预测模型，进行了单变量Cox回归分析和最小绝对收缩和选择算子Cox回归分析。根据中位风险评分，将患者分为高风险和低风险类别。使用四个血小板相关基因特征、TNM分期和病理类型创建了一个列线图，以预测食管癌患者1年、2年和3年的总生存期（OS）。此外，一致性指数、受试者工作特征曲线和校准曲线用于验证列线图。
根据单变量Cox回归分析和最小绝对收缩和选择算子回归分析，食管癌的预后与 、 、 和 相关。根据Kaplan-Meier分析，食管癌高风险患者的总生存期明显短于低风险患者（ < 0.05）。在单变量和多变量Cox回归中，TNM分期（风险比：2.187，95%置信区间：1.242 - 3.852， = 0.007）和风险评分均与总生存期独立相关（风险比：2.451，95%置信区间：1.599 - 3.756， 0.001）。
利用 、 、 和 建立了食管癌的生存风险评分模型和独立预后变量。基于TNM分期、病理类型和风险评分的列线图可用于预测食管癌的总生存期。一致性指数、受试者工作特征曲线和校准曲线表明，列线图具有很强的预测能力。
