胰腺癌术后胰瘘风险预测模型构建及验证-现代医学

胰腺癌术后胰瘘风险预测模型构建及验证

单位：南京医科大学附属南京医院/南京市第一医院普外科, 江苏南京 210006

分类号：R735.9

出版年·卷·期（页码）：2024·52·第七期（1038-1043）

摘要：

目的：构建胰腺癌患者临床相关性术后胰瘘(CR-POPF)的预测模型，并验证该模型的预测效能及校准度。方法：收集2021年1月至2023年12月本院115例胰腺癌患者的临床资料，所有患者均行胰十二指肠切除术(PD)治疗，根据术后有无发生CR-POPF分为CR-POPF组(24例)和无CR-POPF组(91例)。收集胰腺癌患者体质量指数(BMI)、腹部总脂肪面积(TFA)、主胰管直径(MPDD)、细胞外体积(ECV)分数、术后第1天腹腔引流液淀粉酶(ADFA₁)等临床资料，通过Logistic回归分析筛选胰腺癌患者发生CR-POPF的影响因素，构建CR-POPF预测模型，绘制受试者工作特征(ROC)曲线评价模型预测价值，Hosmer-Lemeshow拟合优度检验预测模型的有效性。结果：单因素分析显示，BMI、TFA、MPDD、ECV分数、ADFA₁与胰腺癌患者CR-POPF发生有关(P＜0.05)。二元Logistic回归分析显示，TFA、MPDD、ECV分数、ADFA₁是胰腺癌患者发生CR-POPF的独立影响因素(P＜0.05)。依据TFA、MPDD、ECV分数、ADFA₁构建胰腺癌CR-POPF预测模型，拟合优度检测显示，模型鉴别能力良好(χ²=1.472，P=0.993)。ROC曲线分析显示，该模型预测下曲线下面积为0.986(95%CI 0.970～1.000)，敏感度为95.83%，特异度为89.01%。结论：TFA、MPDD、ECV分数、ADFA₁是胰腺癌患者发生CR-POPF的影响因素，基于上述因素建立的CR-POPF模型具有良好的预测效能，对临床早期诊疗有重要意义。

Objective: To construct a prediction model of clinically relevant postoperative pancreatic fistula(CR-POPF) in patients with pancreatic cancer, and verify the prediction efficiency and calibration degree of the model. Methods: The clinical data of 115 patients with pancreatic cancer in our hospital from January 2021 to December 2023 were collected. All patients underwent pancreaticoduodenectomy(PD). According to the presence or absence of CR-POPF after operation, they were divided into CR-POPF group(24 cases) and non-CR-POPF group(91 cases). Clinical data such as body mass index(BMI), total abdominal fat area(TFA), main pancreatic duct diameter(MPDD), extracellular volume(ECV) fraction, and abdominal drainage fluid amylase on postoperative day 1(ADFA₁) were collected. Logistic regression analysis was used to screen the influencing factors of CR-POPF in patients with pancreatic cancer, and a CR-POPF prediction model was constructed. The receiver operating characteristic(ROC) curve was drawn to evaluate the predictive value of the model, and the Hosmer-Lemeshow goodness of fit test was used to test the validity of the prediction model. Results: Univariate analysis showed that BMI, TFA, MPDD, ECV fraction and ADFA₁ were associated with CR-POPF occurrence in pancreatic cancer patients(P<0.05). Binary Logistic regression analysis showed that TFA, MPDD, ECV scores, ADFA₁were independent influencing factors for CR-POPF in pancreatic cancer patients(P<0.05). The CR-POPF prediction model of pancreatic cancer was constructed based on TFA, MPDD, ECV score and ADFA₁. The goodness of fit test showed that the model had good discrimination ability(χ²=1.472, P=0.993). The ROC curve analysis showed that the area under curve predicted by the model was 0.986(95% CI 0.970-1.000), the sensitivity was 95.83%, and the specificity was 89.01%. Conclusion: TFA, MPDD, ECV fraction and ADFA₁ are influencing factors for the occurrence of CR-POPF in patients with pancreatic cancer. The CR-POPF model established based on these factors has good prediction efficiency and has great significance for early clinical diagnosis and treatment.

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