基于血脂异常及相关因素的肝内胆管癌发生风险列线图预测模型构建OA北大核心CSTPCD

Background and Aims:Intrahepatic cholangiocarcinoma(ICC)is insidious in onset and progresses rapidly,often causing patients to miss the optimal surgical window when diagnosed.The mechanism underlying ICC occurrence remains unclear,potentially involving multiple factors,and dyslipidemia currently is identified as one of the risk factors.Therefore,this study was conducted to investigate the association between dyslipidemia and other risk factors with the occurrence of ICC,and to construct a nomogram prediction model,so as to facilitate early prevention for high-risk individuals for ICC and ultimately reduce the incidence rate. Methods:A retrospective analysis was conducted on 5 906 liver surgery patients admitted in the Department of General Surgery of Sir Run Run Shaw Hospital,Zhejiang University School of Medicine,from January 2015 to January 2023.Among them,ICC patients and non-cancer patients were designated as the case group and control group,respectively.Basic data and biochemical indicators were collected before treatment.Lipid indexes and other risk factors were included in univariate and multivariate regression analyses to identify independent risk factors for ICC occurrence.A nomogram prediction model was constructed to assess the impact of each factor.The clinical predictive performance of the nomogram model was evaluated using receiver operating characteristic(ROC)curve,calibration curve,and decision curve. Results:A total of 351 ICC patients and 2 145 non-cancer patients were included.Univariate analysis showed that the sex,age,and the proportion of diabetes,hypertension,cirrhosis,hepatitis B,history of bile duct stones,and history of schistosomiasis,as well as the serum triglycerides,serum total cholesterol,and serum high-density lipoprotein cholesterol(HDL-C)levels were significantly different between the two groups(all P＜0.05).Logistic multivariate regression analysis revealed that age,hypertension,diabetes,hepatitis B,cirrhosis,and low blood HDL-C(＜0.83 mmol/L)were independent risk factors for ICC occurrence,while a history of intrahepatic bile duct stones was a protective factor against ICC occurrence(all P＜0.05).A nomogram prediction model for ICC occurrence constructed based on these risk factors had an area under the ROC curve of 0.771(95％CI=0.744-0.797,P＜0.001).The calibration curve showed good fit between the predicted and actual curves,and the decision curve indicated that the model had good clinical benefits and efficacy at risk thresholds of approximately 0.1-0.4,and its performance surpassed that of a single indicator. Conclusion:Low blood HDL-C is closely associated with ICC occurrence.The nomogram prediction model constructed based on low blood HDL-C and other six factors can provide references for the prevention and clinical treatment of ICC.