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The Predictive Value of Albumin-bilirubin Score Combined with Liver Function Index and CEA for Liver Metastasis of Colorectal Cancer
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摘要: 目的 探讨白蛋白-胆红素评分（albumin-bilirubin,ALBI）联合肝功能指标及癌胚抗原（carcinoembryonic antigen，CEA）对结直肠癌肝转移的预测价值。 方法 回顾性分析2016年1月至2021年7月于兰州大学第二医院接受手术治疗且随访满24个月的结直肠癌患者临床资料，依据随访结果将入组患者分为肝转移组和非肝转移组，并按2:1比例随机分为建模组与验证组。分析结直肠癌患者发生肝转移的风险因素，采用Lasso-Logistic回归构建预测模型，采用Bootstrap法进行内部验证，应用受试者工作特征曲线、校准曲线和临床决策曲线评价预测模型的可靠性，最后绘制列线图展示预测结果。 结果 共入选符合纳入和排除标准的患者195例，其中建模组130例，验证组65例；通过Lasso回归变量筛选及Logistic回归分析，结果显示ALBI（OR=8.062,95%： 2.545～25.540）、丙氨酸氨基转移酶（alanine transaminase ，ALT）（OR=1.037,95% CI： 1.004～1.071）与CEA （OR=1.025，95% CI： 1.008～1.043）是结直肠癌发生肝转移的独立预测因素；建模组三者联合预测结直肠癌发生肝转移的曲线下面积（area under curve，AUC）为0.921，灵敏度为78.0%，特异度为95.0%，C-index为0.921，H-L拟合度曲线X2=0.851,P=0.654,校准曲线斜率接近1，提示该模型准确度较高，DCA曲线显示该模型具有良好的临床应用价值。对建模组数据，采用Bootstrap法进行1000次重抽样的内部验证，准确性为0.869，kappa一致性为0.709，AUC为0.913；应用ALBI、ALT与CEA单独诊断结直肠癌肝转移时，CEA的AUC最大(0.897)，三者联合诊断结直肠癌肝转移的效能最高。验证组三者联合预测结直肠癌发生肝转移的AUC为0.918，灵敏度为85.0%，特异度为95.6%，C-index为0.918，H-L拟合度曲线X2=0.586,P=0.746。 结论 ALBI、ALT与CEA对结直肠癌肝转移有一定预测价值，三者联合预测结直肠癌肝转移的效能较高，通过其构建的风险预测模型具有良好的临床应用前景。Abstract: Objective To investigate the predictive value of albumin-bilirubin (ALBI) score combined with liver function index and carcinoembryonic antigen (CEA) for liver metastasis of colorectal cancer. Methods The clinical data of patients with colorectal cancer who underwent surgical treatment in the Second Hospital of Lanzhou University from January 2016 to July 2021 and were followed up for 24 months were retrospectively analyzed. According to the follow-up results, the enrolled patients were divided into liver metastasis group and non-liver metastasis group, and were randomly divided into modeling group and validation group according to the ratio of 2:1. The risk factors of liver metastasis in patients with colorectal cancer were analyzed. Lasso-Logistic regression was used to construct the prediction model. Bootstrap method was used for internal verification. Receiver operating characteristic curve, calibration curve and clinical decision curve were used to evaluate the reliability of the prediction model. Finally, a nomogram was drawn to show the prediction results. Results A total of 195 patients who met the inclusion and exclusion criteria were enrolled, including 130 in the modeling group and 65 in the validation group. Through Lasso regression variable screening and Logistic regression analysis, the results showed that ALBI (OR=8.062,95% CI:2.545~25.540), alanine transaminase (ALT) (OR=1.037,95% CI:1.004~1.071) and CEA (OR=1.025,95% CI:1.008~1.043) were independent predictors of liver metastasis in colorectal cancer. The area under curve (AUC) of the combined prediction of liver metastasis of colorectal cancer in the modeling group was 0.921, the sensitivity was 78%, the specificity was 95%, the C-index was 0.921, the H-L fitting curve X2=0.851, P=0.654, and the slope of the calibration curve was close to 1, suggesting that the accuracy of the model was high, and the DCA curve showed that the model had good clinical application value. For the data of the modeling group, the Bootstrap method was used for internal verification of 1000 resamplings. The accuracy was 0.869, the kappa consistency was 0.709, and the AUC was 0.913. When ALBI, ALT and CEA were used to diagnose liver metastasis of colorectal cancer alone, the AUC of CEA was the largest (0.897), and the combination of the three had the highest efficacy in the diagnosis of liver metastasis of colorectal cancer. In the validation group, the AUC, sensitivity, specificity, Cindex and H-L curve of the combined prediction of liver metastasis of colorectal cancer were 0.918, 85%, 95.6%, 0.918, X2=0.586, P=0.746, respectively. Conclusion ALBI, ALT and CEA have certain predictive value for liver metastasis of colorectal cancer. The combined diagnosis of liver metastasis of colorectal cancer has high efficacy, and the risk prediction model constructed by them has a good predictive effect.
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Key words:
- albumin-bilirubin score /
- CEA /
- colorectal cancer /
- liver metastasis /
- predictive value
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