小野寺预后营养指数与胆囊癌患者预后的相关性及列线图模型的建立与验证-现代医学

小野寺预后营养指数与胆囊癌患者预后的相关性及列线图模型的建立与验证

单位：咸阳市中心医院肝胆外科, 陕西咸阳 712000

分类号：R735.8

出版年·卷·期（页码）：2023·51·第六期（788-795）

摘要：

目的：探讨术前小野寺预后营养指数(PNI)在胆囊癌患者预后的意义，并建立预测胆囊癌预后的列线图模型。方法:回顾性分析咸阳市中心医院肝胆外科2010年1月至2022年6月收治的接受手术治疗的98例胆囊癌患者的临床资料。PNI按以下公式计算：PNI=血清白蛋白(g·L^-1)+5×淋巴细胞计数(×10⁹·L^-1)。通过绘制预测生存的受试者工作特征(ROC)曲线确定PNI的最佳临床临界值为49.25，根据该值将患者分为高PNI组(n=36)和低PNI组(n=62)。绘制Kaplan-Meier生存曲线，对两组患者的总生存时间进行分析。单因素、多因素Cox回归模型确定影响胆囊癌患者预后的独立危险因素，并依据独立危险因素绘制相应的列线图预测模型，并通过校准曲线及一致性曲线进行验证。结果：Kaplan-Meier生存曲线显示，高PNI组的术后生存率显著高于低PNI组(P<0.05)。多因素Cox回归分析显示，T分期、是否出现淋巴结转移、糖类抗原199(CA-199)、癌胚抗原(CEA)以及PNI是胆囊癌患者预后的独立危险因素(P<0.05)。选择T分期、是否出现淋巴结转移、CA-199、CEA以及PNI等指标进行构建预测总生存率的列线图。该模型的预测能力采用C指数(C-index=0.813)进行评估。校准图显示了良好的性能。结论：PNI可以作为预测胆囊癌患者预后的新型指标，术前外周血PNI越高，患者预后越好；以此为基础构建的列线图预测模型有助于临床医生对胆囊癌患者提供更好的个体化治疗方案和随访策略。

Objective: To explore the significance of preoperative Onodera's prognostic nutrition index(PNI) in the prognosis of gallbladder cancer patients, and a nomogram model for predicting the prognosis of gallbladder cancer was established. Methods: The clinical data of 98 gallbladder cancer patients who underwent surgical treatment in the department of hepatobiliary surgery of Xianyang Central Hospital from January 2010 to June 2022 were analyzed retrospectively. PNI is calculated according to the following formula:serum albumin(g·L^-1)+5×lymphocyte count(×10⁹·L^-1). The optimal clinical cut-off value for PNI was determined by drawing the receiver operating characteristic(ROC) curve for predicting survival, which was 49.25. According to this value, patients were divided into high PNI group(n=36) and low PNI group(n=62). Kaplan-Meier survival curve was drawn and the total survival time of the two groups was analyzed. Single-factor and multi-factor Cox regression model determined the independent risk factors that affected the prognosis of patients with gallbladder cancer, and drew the corresponding nomogram prediction model according to the above independent risk factors, which was verified by calibration curve and consistency curve. Results: The Kaplan-Meier survival curve showed that the postoperative survival rate in the high PNI group was significantly higher than that in the low PNI group(P<0.05). Multivariate Cox regression analysis showed that T stage, lymph node metastasis, CA-199, CEA and PNI were independent risk factors for the prognosis of gallbladder cancer patients(P<0.05). T stage, lymph node metastasis, CA-199, CEA, PNI and other indicators were selected to construct a nomogram predicting the overall survival rate. The prediction ability of this model was evaluated by C-index(0.813). The calibration chart shows good performance. Conclusion: PNI can be used as a new indicator to predict the prognosis of gallbladder cancer patients. The higher the PNI in peripheral blood before surgery, the better the prognosis of patients. The nomogram prediction model constructed on this basis helps clinicians to provide better individualized treatment plans and follow-up strategies for gallbladder cancer patients.

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