Gong Feng, Ferenc E Mózes, Dong Ji, Sombat Treeprasertsuk, Takeshi Okanoue, Toshihide Shima, Huiqing Liang, Emmanuel Tsochatzis, Jinjun Chen, Jörn M Schattenberg, Christian Labenz, Sanjiv Mahadeva, Wah Kheong Chan, Xiaoling Chi, Adèle Delamarre, Victor de Lédinghen, Salvatore Petta, Elisabetta Bugianesi, Hannes Hagström, Jérôme Boursier, José Luis Calleja, George Boon-Bee Goh, Rocio Gallego-Durán, Arun J Sanyal, Jian-Gao Fan, Laurent Castéra, Michelle Lai, Stephen A Harrison, Manuel Romero-Gomez, Seung Up Kim, Yongfen Zhu, Geraldine Ooi, Junping Shi, Masato Yoneda, Atsushi Nakajima, Jing Zhang, Monica Lupsor-Platon, Bihui Zhong, Jeremy F L Cobbold, Chun-Yan Ye, Peter J Eddowes, Philip Newsome, Jie Li, Jacob George, Fangping He, Myeong Jun Song, Hong Tang, Yuchen Fan, Jidong Jia, Liang Xu, Su Lin, Yiling Li, Zhonghua Lu, Yuemin Nan, Junqi Niu, Xuebing Yan, Yongjian Zhou, Chenghai Liu, Hong Deng, Qing Ye, Qing-Lei Zeng, Lei Li, Jing Wang, Song Yang, Huapeng Lin, Hye Won Lee, Terry Cheuk-Fung Yip, Céline Fournier-Poizat, Grace Lai-Hung Wong, Grazia Pennisi, Angelo Armandi, Wen-Yue Liu, Ying Shang, Marc de Saint-Loup, Elba Llop, Kevin Kim Jun Teh, Carmen Lara-Romero, Amon Asgharpour, Sara Mahgoub, Mandy Sau-Wai Chan, Clemence M Canivet, Fanpu Ji, Yongning Xin, Jin Chai, Zhiyong Dong, Giovanni Targher, Christopher D Byrne, Na He, Man Mi, Feng Ye, Vincent Wai-Sun Wong, Michael Pavlides, Ming-Hua Zheng
{"title":"acFibroMASH Index for the Diagnosis of Fibrotic MASH and Prediction of Liver-related Events: An International Multicenter Study.","authors":"Gong Feng, Ferenc E Mózes, Dong Ji, Sombat Treeprasertsuk, Takeshi Okanoue, Toshihide Shima, Huiqing Liang, Emmanuel Tsochatzis, Jinjun Chen, Jörn M Schattenberg, Christian Labenz, Sanjiv Mahadeva, Wah Kheong Chan, Xiaoling Chi, Adèle Delamarre, Victor de Lédinghen, Salvatore Petta, Elisabetta Bugianesi, Hannes Hagström, Jérôme Boursier, José Luis Calleja, George Boon-Bee Goh, Rocio Gallego-Durán, Arun J Sanyal, Jian-Gao Fan, Laurent Castéra, Michelle Lai, Stephen A Harrison, Manuel Romero-Gomez, Seung Up Kim, Yongfen Zhu, Geraldine Ooi, Junping Shi, Masato Yoneda, Atsushi Nakajima, Jing Zhang, Monica Lupsor-Platon, Bihui Zhong, Jeremy F L Cobbold, Chun-Yan Ye, Peter J Eddowes, Philip Newsome, Jie Li, Jacob George, Fangping He, Myeong Jun Song, Hong Tang, Yuchen Fan, Jidong Jia, Liang Xu, Su Lin, Yiling Li, Zhonghua Lu, Yuemin Nan, Junqi Niu, Xuebing Yan, Yongjian Zhou, Chenghai Liu, Hong Deng, Qing Ye, Qing-Lei Zeng, Lei Li, Jing Wang, Song Yang, Huapeng Lin, Hye Won Lee, Terry Cheuk-Fung Yip, Céline Fournier-Poizat, Grace Lai-Hung Wong, Grazia Pennisi, Angelo Armandi, Wen-Yue Liu, Ying Shang, Marc de Saint-Loup, Elba Llop, Kevin Kim Jun Teh, Carmen Lara-Romero, Amon Asgharpour, Sara Mahgoub, Mandy Sau-Wai Chan, Clemence M Canivet, Fanpu Ji, Yongning Xin, Jin Chai, Zhiyong Dong, Giovanni Targher, Christopher D Byrne, Na He, Man Mi, Feng Ye, Vincent Wai-Sun Wong, Michael Pavlides, Ming-Hua Zheng","doi":"10.1016/j.cgh.2024.07.045","DOIUrl":null,"url":null,"abstract":"<p><strong>Background & aims: </strong>Metabolic dysfunction-associated steatohepatitis (MASH) and fibrotic MASH are significant health challenges. This multi-national study aimed to validate the acMASH index (including serum creatinine and aspartate aminotransferase concentrations) for MASH diagnosis and develop a new index (acFibroMASH) for non-invasively identifying fibrotic MASH and exploring its predictive value for liver-related events (LREs).</p><p><strong>Methods: </strong>We analyzed data from 3004 individuals with biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD) across 29 Chinese and 9 international cohorts to validate the acMASH index and develop the acFibroMASH index. Additionally, we utilized the independent external data from a multi-national cohort of 9034 patients with MAFLD to examine associations between the acFibroMASH index and the risk of LREs.</p><p><strong>Results: </strong>In the pooled global cohort, the acMASH index identified MASH with an area under the receiver operating characteristic curve (AUROC) of 0.802 (95% confidence interval [CI], 0.786-0.818). The acFibroMASH index (including the acMASH index plus liver stiffness measurement) accurately identified fibrotic MASH with an AUROC of 0.808 in the derivation cohort and 0.800 in the validation cohort. Notably, the AUROC for the acFibroMASH index was 0.835 (95% CI, 0.786-0.882), superior to that of the FAST score at 0.750 (95% CI, 0.693-0.800; P < .01) in predicting the 5-year risk of LREs. Patients with acFibroMASH >0.39 had a higher risk of LREs than those with acFibroMASH <0.15 (adjusted hazard ratio, 11.23; 95% CI, 3.98-31.66).</p><p><strong>Conclusions: </strong>This multi-ethnic study validates the acMASH index as a reliable, noninvasive test for identifying MASH. The newly proposed acFibroMASH index is a reliable test for identifying fibrotic MASH and predicting the risk of LREs.</p>","PeriodicalId":10347,"journal":{"name":"Clinical Gastroenterology and Hepatology","volume":null,"pages":null},"PeriodicalIF":11.6000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Gastroenterology and Hepatology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.cgh.2024.07.045","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background & aims: Metabolic dysfunction-associated steatohepatitis (MASH) and fibrotic MASH are significant health challenges. This multi-national study aimed to validate the acMASH index (including serum creatinine and aspartate aminotransferase concentrations) for MASH diagnosis and develop a new index (acFibroMASH) for non-invasively identifying fibrotic MASH and exploring its predictive value for liver-related events (LREs).
Methods: We analyzed data from 3004 individuals with biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD) across 29 Chinese and 9 international cohorts to validate the acMASH index and develop the acFibroMASH index. Additionally, we utilized the independent external data from a multi-national cohort of 9034 patients with MAFLD to examine associations between the acFibroMASH index and the risk of LREs.
Results: In the pooled global cohort, the acMASH index identified MASH with an area under the receiver operating characteristic curve (AUROC) of 0.802 (95% confidence interval [CI], 0.786-0.818). The acFibroMASH index (including the acMASH index plus liver stiffness measurement) accurately identified fibrotic MASH with an AUROC of 0.808 in the derivation cohort and 0.800 in the validation cohort. Notably, the AUROC for the acFibroMASH index was 0.835 (95% CI, 0.786-0.882), superior to that of the FAST score at 0.750 (95% CI, 0.693-0.800; P < .01) in predicting the 5-year risk of LREs. Patients with acFibroMASH >0.39 had a higher risk of LREs than those with acFibroMASH <0.15 (adjusted hazard ratio, 11.23; 95% CI, 3.98-31.66).
Conclusions: This multi-ethnic study validates the acMASH index as a reliable, noninvasive test for identifying MASH. The newly proposed acFibroMASH index is a reliable test for identifying fibrotic MASH and predicting the risk of LREs.
期刊介绍:
Clinical Gastroenterology and Hepatology (CGH) is dedicated to offering readers a comprehensive exploration of themes in clinical gastroenterology and hepatology. Encompassing diagnostic, endoscopic, interventional, and therapeutic advances, the journal covers areas such as cancer, inflammatory diseases, functional gastrointestinal disorders, nutrition, absorption, and secretion.
As a peer-reviewed publication, CGH features original articles and scholarly reviews, ensuring immediate relevance to the practice of gastroenterology and hepatology. Beyond peer-reviewed content, the journal includes invited key reviews and articles on endoscopy/practice-based technology, health-care policy, and practice management. Multimedia elements, including images, video abstracts, and podcasts, enhance the reader's experience. CGH remains actively engaged with its audience through updates and commentary shared via platforms such as Facebook and Twitter.