背景与目的:肝内胆管癌(ICC)起病隐匿,进展迅速,患者诊断时往往错过最佳手术时机.ICC的发生机制尚不明确,可能与多种因素有关,目前发现血脂异常可能是风险因素之一.因此,本研究探讨血脂异常及其他危险因素与ICC发生风险的关联,并构建列线图预测模型,以期对ICC高危人群实现早期预防并最终降低发病率. 方法:回顾性分析2015年1月—2023年1月于浙江大学医学院附属邵逸夫医院普通外科就诊的5 906例肝脏手术患者,其中ICC患者和非癌症患者分别设为病例组和对照组,收集患者治疗前基本资料和生化指标,将血脂指标和其余风险因素纳入单因素、多因素回归分析,筛选ICC发生的独立风险因素,构建列线图预测模型评估各因素影响程度,采用受试者工作特征曲线(ROC)、校准曲线和决策曲线评估列线图模型临床预测效能. 结果:共纳入351例ICC患者和2 145例非癌症患者,单因素分析显示,两组患者的性别、年龄与糖尿病、高血压、肝硬化、乙肝、胆管结石病史、血吸虫病史比例,以及血清甘油三酯、血清总胆固醇、血清高密度脂蛋白胆固醇(HDL-C)水平的差异均有统计学意义(均P＜0.05).Logistic多因素回归分析显示,年龄、高血压、糖尿病、乙肝、肝硬化、低HDL-C血症(＜0.83 mmol/L)是ICC发生的独立危险因素,而肝内胆管结石病史为ICC发生的保护因素(均P＜0.05).根据上述风险因素构建预测ICC发生的列线图预测模型,绘制ROC曲线下面积为0.771(95％CI=0.744～0.797,P＜0.001),校准曲线中预测曲线与实际曲线基本拟合,决策曲线提示该模型在风险阈值约0.1～0.4时具有良好临床收益且效能优于单一指标. 结论:低HDL-C血症与ICC的发生密切相关,基于低HDL-C血症与另外6个因素构建的列线图预测模型可为ICC的预防和临床诊疗提供一定的参考.
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.
徐铮澳;梁霄
浙江大学医学院附属邵逸夫医院普通外科,浙江杭州 310000||浙江省肝脏疾病多组学精准诊治重点实验室,浙江杭州 310000
临床医学
胆管肿瘤;胆管,肝内;血脂异常;危险因素;列线图
Bile Duct Neoplasms;Bile Ducts,Intrahepatic;Dyslipidemias;Risk Factors;Nomograms
《中国普通外科杂志》 2024 (002)
219-226 / 8
国家自然科学基金基金资助项目(82072625);浙江省科技厅"领雁"计划基金资助项目(2024C03049);浙江省卫生健康重大科技计划重大基金资助项目(WKJ-ZJ-2407);浙江省杭州市科技局农业与社会发展领域重点基金资助项目(20231203A09).
10.7659/j.issn.1005-6947.2024.02.008
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