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
{"title":"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","authors":"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","doi":"10.1016/j.jtauto.2023.100215","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>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 <span>https://ndth-zzy.shinyapps.io/APOSF-nomogram/</span><svg><path></path></svg>). 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.</p></div><div><h3>Conclusion</h3><p>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.</p></div>","PeriodicalId":36425,"journal":{"name":"Journal of Translational Autoimmunity","volume":"7 ","pages":"Article 100215"},"PeriodicalIF":4.7000,"publicationDate":"2023-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel web-based online nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome\",\"authors\":\"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\",\"doi\":\"10.1016/j.jtauto.2023.100215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>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 <span>https://ndth-zzy.shinyapps.io/APOSF-nomogram/</span><svg><path></path></svg>). 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.</p></div><div><h3>Conclusion</h3><p>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.</p></div>\",\"PeriodicalId\":36425,\"journal\":{\"name\":\"Journal of Translational Autoimmunity\",\"volume\":\"7 \",\"pages\":\"Article 100215\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2023-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Translational Autoimmunity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S258990902300028X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Translational Autoimmunity","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S258990902300028X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
A novel web-based online nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome
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.