| 基于预后免疫-炎症-营养评分胃癌根治术患者预后预测模型的构建 |
| 投稿时间：2024-12-25 修订日期：2025-02-15 点此下载全文 |
| 引用本文：罗鑫婷,王红兵,掌辕轩,陈岩,杨飞虎,席元晟.基于预后免疫-炎症-营养评分胃癌根治术患者预后预测模型的构建[J].医学研究杂志,2025,54(7):152-157, 84 |
| DOI：
10.11969/j.issn.1673-548X.2025.07.027 |
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| 中文摘要:目的 探讨预后免疫-炎症-营养(prognostic immune-inflammatory-nutritional,PIIN)评分对胃癌根治术患者的生存预测价值,并构建预后预测模型。方法 回顾性分析406例胃癌根治术患者的临床资料,基于纤维蛋白原(fibrinogen,FIB)、中性粒细胞与淋巴细胞比值(neutrophil to lymphocyte ratio,NLR)、全身免疫炎症指数(systemic immune-inflammation index,SII)、白蛋白-胆红素(albumin-bilirubin,ALBI)评分和预后营养指数(prognostic nutritional index,PNI)计算PIIN评分,根据PIIN评分的阈值为31.4906分将患者分为高PIIN评分组和低PIIN评分组。采用单因素和多因素COX回归分析胃癌患者总生存率的影响因素,绘制随时间变化的受试者工作特征(time receiver operating characteristic,TIME ROC)曲线,比较各评分系统的预测价值；构建基于PIIN评分的列线图进行风险分组及生存分析。结果 多因素COX回归分析显示,神经是否侵犯、分化程度、T分期、N分期、是否辅助化疗、PIIN评分是胃癌患者总生存率的独立影响因素。TIME ROC曲线分析显示,PIIN评分在预测胃癌根治术患者生存方面优于其他评分系统。列线图的1年、3年和5年ROC曲线下面积(area under the curve,AUC)分别为0.788、0.794、0.854,且不同风险分组患者生存预后差异有统计学意义(P<0.0001)。结论 基于PIIN评分构建的列线图预测模型对胃癌根治术患者的生存预测具有较好的预测效能。 |
| 中文关键词:胃癌 预后 免疫 炎症 营养 |
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| Construction of Prognostic Prediction Model of Patients Undergoing Radical Gastrectomy of Gastric Cancer Based on the Prognostic Immune-Inflammation-Nutrition Score. |
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| Abstract:Objective To explore the survival prediction value of the prognostic immune-inflammatory-nutritional (PIIN) score for patients undergoing radical gastrectomy and construct a prognostic prediction model. Methods To retrospectively analyze the clinical data of 406 patients who underwent radical gastrectomy. Calculate the PIIN score based on fibrinogen (FIB), neutrophil to lymphocyte ratio (NLR), systemic immune-inflammation index (SII), albumin-bilirubin (ALBI) score, and prognostic nutritional index (PNI). According to the threshold of 31.4906, the patients were divided into the high-PIIN group and the low-PIIN group. Conduct univariate and multivariate analyses using COX regression analysis, draw the time-dependent receiver operating characteristic (TIME ROC) curve, and compare the prognostic values of various scoring systems. To construct a nomogram based on the PIIN score for risk grouping and survival analysis. Results Multivariate analysis showed that nerve invasion or not, degree of differentiation, T stage, N stage, adjuvant chemotherapy status, and PIIN score were independent independent factors for the overall survival rate of gastric cancer patients. TIME ROC curve analysis indicated that the PIIN score was superior to other scoring systems in predicting survival. The areas under the curves (AUC) of the 1-year, 3-year, and 5-year ROC curvesof the nomogram were 0.788,0.794 and 0.854 respectively. Moreover, there was a statistically significant difference in survival prognosis among different risk groups (P<0.0001). Conclusion The nomogram model based on the PIIN score has good predictive ability in predicting the survival of patients undergoing radical gastrectomy for gastric cancer. |
| keywords:Gastric cancer Prognosis Immunity Inflammation Nutrition |
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