基于炎症反应评分系统构建胃癌患者预后的列线图预测模型. (Chinese)

Objective: To construct the inflammatory response score (IRS) system according to the expression levels of neutrophil to lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) in patients with gastric cancer before operation, and to analyze the influence of IRS on postoperative prognosis of patients with gastric cancer and construct a nomogram prediction model. Methods: The clinical data of 211 gastric cancer patients admitted to the Department of General Surgery of Yichun People's Hospital between January 2016 and January 2020 were collected, 198 among whom were successfully followed up. According to their survival status 3 years after surgery, these 198 patients were divided into the death group (n=93) and the survival group (n=105). The general clinical data of the two groups were compared. rThe independent risk factors affecting the prognosis of patients with gastric cancer were analyzed by multivariate COX regression risk model, and the nomogram prediction model was constructed by the R Package rms. Results: There were significant differences in maximum tumor diameter, pathological stage, T stage, differentiation degree, nerve invasion, vascular invasion, NLR, PLR and LMR between the 2 groups (all P<0.05). According to the construction criteria of NLP, PLR and LMR-IRS (NPL-IRS), the OS rate of gastric cancer patients with different scores showed a certain grade trend difference (%2=61.129, P<0.01). Pathological stage III, low differentiation, vascular invasion, NPL-IRS>1 score were independent risk factors for the prognosis of gastric cancer patients (P<0.05). Decision curve analysis showed that this predictive model could provide significant additional clinical net benefit at a risk threshold of >0.16. Conclusion: The nomogram prediction model based on pathological stage III, low differentiation, vascular invasion, and NPL-IRS> 1 score can provide important strategic guidance for the prognosis assessment of gastric cancer patients. [ABSTRACT FROM AUTHOR]

目的:根据胃癌患者术前中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)、淋巴细胞与单核细胞比 值(LMR)的表达水平构建炎症反应评分(IRS)系统,分析IRS对胃癌患者术后预后的影响并构建列线图预测模型。方法:选取 2016年1月至2020年1月宜春市人民医院普外科收治的211例胃癌患者的临床资料,根据随访成功的198例患者术后3年生存状 态分为死亡组(n=93)和生存组(n=105)。比较两组患者的一般临床资料,多因素COX冋归风险模型分析影响胃癌患者预后的独 立风险因素,R语言rms包构建列线图预测模型。结果:两组胃癌患者肿瘤最大直径、病理分期、T分期、分化程度、神经侵犯、脉 管侵犯、NLR、PLR、L MR比较差异均有统计学意义(均P< 0.05)。依据NLP、PLR、LMR-IRS(NPL-IRS)构建标准,不同分值的胃癌患 者OS率表现出一定的等级趋势差异(才=61.129,P<0.01)。病理分期III期、分化程度低、脉管侵犯、NPL-IRS>1分是影响胃癌患者 预后的独立危险因素(P<0.05)。决策曲线分析显示,风险阈值>0.16时,此预测模型可以提供显著额外的临床净收益。结论:基 于病理分期III期、分化程度低、脉管侵犯、NPL-IRS>1分构建的列线图预测模型可以为胃癌患者预后评估提供重要的策略指导. [ABSTRACT FROM AUTHOR]

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