首页|基于脂代谢标志物的肝细胞癌微血管浸润术前预测模型的建立与验证

基于脂代谢标志物的肝细胞癌微血管浸润术前预测模型的建立与验证

扫码查看
目的 探讨脂质代谢等指标与肝细胞癌中微血管浸润的关联并由此建立一个术前预测模型方法 回顾性分析2017年1月至2023年3月期间在兰州大学第一医院接受肝切除术的389例肝细胞癌患者的临床病理资料.389例患者按7∶3的比例分别纳入训练组(n=272)和验证组(n=117),通过单因素和多因素logistic回归分析确定微血管浸润(microvascular invasion,MVI)的独立危险因素并构建MVI预测模型,通过校准曲线、受试者工作特征(receiver operating characteristic,ROC)曲线及决策曲线分析验证该模型的预测效能.结果 单因素和多因素logistic回归分析结果显示:术前与MVI独立相关的风险因素包括总胆固醇、乳酸脱氢酶、体质量指数、甲胎蛋白、糖类抗原125、乙肝DNA、最大肿瘤直径和白蛋白-胆红素评分.根据上述8个风险因素构建的MVI预测模型在训练组和验证组的ROC曲线下面积分别为0.79[95%CI为(0.74,0.84)]和0.75[95%CI为(0.66,0.84)];校准曲线分析表明,预测曲线与标准曲线拟合良好;ROC曲线分析表明,MVI预测模型的预测效能较高;决策曲线分析证实MVI预测模型具有较高的临床应用价值.结论 本研究结果提示了总胆固醇等指标和MVI之间的独立相关关系,并基于这些指标成功地构建和验证了 MVI预测模型,可以帮助医生在术前有效地识别肝细胞癌患者中的MVI高风险人群,从而帮助我们选择更合理的治疗方案.
Development and validation of a preoperative predictive model for microvascular invasion in hepatocellular carcinoma based on lipid metabolism markers
Objective To investigate the association of lipid metabolism and other markers with microvascular invasion in hepatocellular carcinoma(HCC)and to develop a preoperative prediction model from it.Methods Data from 389 HCC patients who underwent hepatectomy at First Hospital of Lanzhou University between January 2017 and March 2023 were retrospectively analyzed.These patients were divided into training group(n=272)and validation group(n=117)with a ratio of 7∶3.The independent risk factors of microvascular invasion(MVI)were determined by univariate and multivariate logistic regression analysis,and the MVI prediction model was established.The prediction efficiency of the model was verified by the analysis of calibration curve,receiver operating characteristic(ROC)curve and decision curve.Results Univariate and multivariate logistic regression analysis showed that the risk factors independently related to MVI before operation included total cholesterol,lactate dehydrogenase,body mass index,alpha-fetoprotein,carbohydrate antigen 125,hepatitis B DNA,maximum tumor diameter and albumin-bilirubin score.MVI prediction model was established based on the above eight risk factors,and its area under ROC curve in the training group and the validation group were 0.79[95%CI(0.74,0.84)]and 0.75[95%CI(0.66,0.84)]respectively.Calibration curve analysis showed that the prediction curve fitted well with the standard curve.ROC curve analysis showed that the MVI prediction model was efficient.Decision curve analysis confirmed that the MVI prediction model had significant clinical applications.Conclusion This study identified independent correlations between total cholesterol levels,among other things,and MVI,and successfully developed and validated novel predictive model based on these indicators that can help physicians effectively identify individuals at high risk for MVI in patients with hepatocellular carcinoma preoperatively,leading to more rational treatment choices.

lipid metabolismmicrovascular invasionpredictive modelhepatocellular carcinoma

徐龄聪、郑燕、龚天乐、周永强、闫洁熙、丁方回、李汛

展开 >

兰州大学第一临床医学院(兰州 730000)

兰州大学第一医院普外科(兰州 730000)

兰州大学第一医院精准医学中心(兰州 730000)

甘肃省生物治疗与再生医学重点实验室(兰州 730000)

展开 >

脂质代谢 微血管浸润 预测模型 肝细胞癌

2024

中国普外基础与临床杂志
四川大学华西医院

中国普外基础与临床杂志

CSTPCD
影响因子:0.858
ISSN:1007-9424
年,卷(期):2024.31(3)
  • 30