A novel web-based online nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome

IF 4.7 Q2 IMMUNOLOGY Journal of Translational Autoimmunity Pub Date : 2023-10-14 DOI:10.1016/j.jtauto.2023.100215
Zhiyi Zhang , Jian Wang , Yun Chen , Yiguang Li , Li Zhu , Huali Wang , Yilin Liu , Jiacheng Liu , Shengxia Yin , Xin Tong , Xiaomin Yan , Yuxin Chen , Chuanwu Zhu , Jie Li , Yuanwang Qiu , Chao Wu , Rui Huang
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Abstract

Background

Patients with autoimmune hepatitis-primary biliary cholangitis (AIH-PBC) overlap syndrome have a worse prognosis compared to AIH or PBC alone and accurately predicting the severity and dynamically monitoring the progression of disease are therefore essential. We aimed to develop a nomogram-based model to predict advanced liver fibrosis in patients with AIH-PBC overlap syndrome.

Methods

A total of 121 patients with AIH-PBC overlap syndrome were retrospectively included and randomly assigned to a development set and a validation set. Backward stepwise regression's best model with the lowest AIC was employed to create a nomogram. Diagnose accuracy was evaluated using the area under the receiver operator characteristic curve (AUROC), calibration analysis, and decision curve analysis (DCA) and was compared with aspartate aminotransferase-to-platelet ratio (APRI) and fibrosis index based on four factors-4 (FIB-4) score.

Results

The median age of patients was 53.0 years (IQR: 46.0–63.0), and female patients accounted for 95.0 %. Platelets, globulin, total bilirubin, and prothrombin time were associated with advanced fibrosis (≥S3) and used to construct an AIH-PBC overlap syndrome fibrosis (APOSF)-nomogram (available online at https://ndth-zzy.shinyapps.io/APOSF-nomogram/). The AUROCs of APOSF-nomogram were 0.845 (95 % CI: 0.754–0.936) and 0.843 (95 % CI: 0.705–0.982) in development set and validation set respectively, which was significantly better than APRI and FIB-4. Calibration revealed that the estimated risk fits well with biopsy-proven observation. DCA outperformed APRI and FIB4 in terms of net benefit, demonstrating clinical utility.

Conclusion

This novel non-invasive web-based online APOSF-nomogram provided a convenient tool for identifying advanced fibrosis in patients with AIH-PBC overlap syndrome. Further prospective, multicenter studies with large sample size are necessary to validate the applicability of APOSF-nomogram.

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一种新的基于网络的在线图预测自身免疫性肝炎-原发性胆管炎重叠综合征患者的晚期肝纤维化
背景:自身免疫性肝炎-原发性胆管炎(AIH-PBC)重叠综合征患者的预后比单独的AIH或PBC更差,因此准确预测严重程度和动态监测疾病进展至关重要。我们旨在开发一种基于nomogram模型来预测AIH-PBC重叠综合征患者的晚期肝纤维化。方法回顾性分析121例AIH-PBC重叠综合征患者,随机分为发展组和验证组。采用逆向逐步回归中AIC最小的最佳模型生成nomogram。采用受试者操作者特征曲线下面积(AUROC)、校准分析和决策曲线分析(DCA)评估诊断准确性,并与天门冬氨酸转肽酶血小板比(APRI)和基于四因素-4 (FIB-4)评分的纤维化指数进行比较。结果患者中位年龄为53.0岁(IQR: 46.0 ~ 63.0),女性患者占95.0%。血小板、球蛋白、总胆红素和凝血酶原时间与晚期纤维化(≥S3)相关,并用于构建AIH-PBC重叠综合征纤维化(APOSF)-图(可在https://ndth-zzy.shinyapps.io/APOSF-nomogram/在线获取)。APOSF-nomogram在开发集和验证集的auroc分别为0.845 (95% CI: 0.754 ~ 0.936)和0.843 (95% CI: 0.705 ~ 0.982),显著优于APRI和FIB-4。校正显示,估计的风险与活检证实的观察结果吻合得很好。就净收益而言,DCA优于APRI和FIB4,证明了临床实用性。结论:这种基于网络的新型无创在线aposf图为AIH-PBC重叠综合征患者的晚期纤维化提供了一种方便的识别工具。需要进一步的前瞻性、多中心、大样本量的研究来验证APOSF-nomogram的适用性。
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来源期刊
Journal of Translational Autoimmunity
Journal of Translational Autoimmunity Medicine-Immunology and Allergy
CiteScore
7.80
自引率
2.60%
发文量
33
审稿时长
55 days
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