基于自身抗体指标构建原发性胆汁性胆管炎患者预后的列线图预测模型

摘要/Abstract

摘要： 目的基于自身抗体指标构建原发性胆汁性胆管炎(PBC)患者预后的列线图预测模型。方法回顾性选取我院在2018年1月至2022年3月收治的112例PBC患者并纳入研究,对患者进行至少2年的随访观察预后,分析预后影响因素,并构建列线图预测模型,应用受试者工作特征(ROC)曲线分析预测效能。结果预后不良组年龄≥65岁占比(52.78% vs. 28.95%)、总胆红素(TBil)水平≥22.2 μmol/L占比(72.22% vs. 42.11%)、腹水占比(55.56% vs. 32.89%)、Child-Pugh分级为B/C级占比(41.67%/30.56% vs. 32.86%/15.79%)、抗gp210抗体阳性占比(52.78% vs. 15.79%)、抗sp100抗体阳性占比(47.22% vs. 19.74%)均高于预后良好组,预后不良组熊去氧胆酸(UDCA)应答占比(50.00% vs. 80.26%)低于预后良好组(P<0.05)。Logistic回归分析显示,TBil(OR=3.652,95%CI:1.315~10.139)、抗sp100抗体阳性(OR=4.716,95%CI:2.018~11.019)、UDCA应答(OR=0.185,95%CI:0.099~0.342)、抗gp210抗体阳性(OR=6.245,95%CI:3.035~12.846)是预后的独立影响因素(P<0.05)。基于logistic回归分析结果建立的列线图模型C-index指数为0.826(95%CI:0.741~0.910),校正曲线趋近于理想曲线(P>0.05)。ROC曲线显示,预测的特异度为85.50%,灵敏度为86.10%,曲线下面积(AUC)0.872(95%CI:0.800~0.945)(P<0.05)。结论基于自身抗体指标抗gp210抗体阳性、抗sp100抗体阳性构建的列线图模型可较好地预测PBC患者不良预后风险。

关键词: 原发性胆汁性胆管炎, 自身抗体, 预后, 预测模型, 列线图

Abstract: Objective To construct a nomogram predictive model for the prognosis of patients with primary biliary cholangitis (PBC) based on autoantibody markers. Methods A total of 112 PBC patients admitted to our hospital from January 2018 to March 2022 were retrospectively selected and included in the study. The patients were followed up for at least 2 years to assess the prognosis, analyze the prognostic factors, and construct a nomogram predictive model. The area under the receiver operating characteristic (ROC) was used to analyze the prediction efficiency. Results The proportion of age ≥65 years (52.78% vs. 28.95%), total bilirubin (TBil) level ≥22.2 μmol/L (72.22% vs. 42.11%), ascites (55.56% vs. 32.89%), Child-Pugh grade B/C (41.67%/30.56% vs. 32.86%/15.79%), anti-gp210 antibody positive (52.78% vs. 15.79%) and anti-sp100 antibody positive (47.22% vs. 19.74%) in the poor prognosis group were higher than those in the good prognosis group. The proportion of ursodeoxycholic acid (UDCA) response (50.00% vs. 80.26%) in the good prognosis group was lower than that in the good prognosis group (P<0.05). Logistic regression analysis showed that TBil (OR=3.652, 95%CI:1.315~10.139), anti-SP100 antibody positive (OR=4.716, 95%CI:2.018~11.019), UDCA response (OR=0.185, 95%CI:0.099~0.342) and anti-gp210 antibody positive (OR=6.245, 95%CI:3.035~12.846) were independent prognostic factors (P<0.05). The C-index of the nomogram model established based on the results of logistic regression was 0.826 (95%CI:0.741~0.910), and the calibration curve was close to the ideal curve (P>0.05). ROC showed that the specificity was 85.50%, the sensitivity was 86.10%, and the area under the curve (AUC) was 0.872 (95%CI:0.800~0.945) (P<0.05). Conclusion The nomogram model based on positive anti-gp210 antibody and positive anti-sp100 antibody can better predict the risk of poor prognosis of PBC patients.

Key words: Primary biliary cholangitis, Autoantibodies, Prognosis, Prediction model, Column chart

黄丽丽, 黄海静, 王德麟, 何义明, 张苗苗. 基于自身抗体指标构建原发性胆汁性胆管炎患者预后的列线图预测模型[J]. 肝脏, 2026, 31(1): 49-53.

HUANG Li-li, HUANG Hai-jing, WANG De-lin, HE Yi-ming, ZHANG Miao-miao. Based on the index of autoantibodies to build the prognosis of patients with primary biliary sex cholangitis nomogram predictive model[J]. Chinese Hepatolgy, 2026, 31(1): 49-53.

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