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":"用于诊断纤维化 MASH 和预测肝脏相关事件的 acFibroMASH 指数：一项国际多中心研究。","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":" ","pages":""},"PeriodicalIF":11.6000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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. 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引用次数: 0
摘要
背景与目的：代谢功能障碍相关性脂肪性肝炎（MASH）和纤维化MASH是重大的健康挑战。这项跨国研究旨在验证用于MASH诊断的acMASH指数（包括血清肌酐和天冬氨酸氨基转移酶浓度），并开发一种新的指数（acFibroMASH），用于无创识别纤维化MASH，并探索其对肝脏相关事件（LREs）的预测价值：我们分析了29个中国队列和9个国际队列中3004名经活检证实患有代谢功能障碍相关性脂肪肝（MAFLD）的患者的数据，以验证acMASH指数并开发acFibroMASH指数。此外，我们还利用来自9034名MAFLD患者的多国队列的独立外部数据，研究了acFibroMASH指数与LREs风险之间的关联：在汇总的全球队列中，acMASH 指数识别 MASH 的 AUROC 为 0.802（95%CI 0.786-0.818）。acFibroMASH指数（包括acMASH指数和肝脏硬度测量）能准确识别纤维化MASH，在衍生队列中的AUROC为0.808，在验证队列中的AUROC为0.800。值得注意的是，acFibroMASH 指数的 AUROC 为 0.835（95% CI 0.786-0.882），优于 FAST 评分的 0.750（95% CI 0.693-0.800，P0.39）：这项多种族研究验证了 acMASH 指数是识别 MASH 的可靠、无创检测方法。新提出的 acFibroMASH 指数是识别纤维化 MASH 和预测 LRE 风险的可靠检测方法。
acFibroMASH Index for the Diagnosis of Fibrotic MASH and Prediction of Liver-related Events: An International Multicenter Study.
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.
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