Pub Date : 2025-11-13DOI: 10.1097/hep.0000000000001612
Xin Huang, Tao Zhu, Shumin Li, Teng Liu, Shibo Lin, Hui Liang, Mingwei Zhong, Xitai Sun, Liyong Chen, Hao Bai, Zehua Zhao, Xuehui Chu, Zhiyong Dong, Guangyong Zhang, Shaozhuang Liu
Background: — At-risk metabolic dysfunction-associated steatohepatitis (MASH) elevates risks of liver-related and all-cause morbidity and mortality. We developed and validated a non-invasive score using routine clinical indicators to identity at-risk MASH in obesity. Methods: — Using data from 1,961 individuals across 5 independent bariatric cohorts with liver biopsy, we developed the predictive score in one derivation cohort (n=1095), performed internal validation (bootstrapping), and conducted external validation using the remaining four biopsy-confirmed cohorts (n=866). The score was also validated in the international overweight/obese cohorts from UK Biobank (n=15745) and NHANES database (n=1573). Predictive value for severe liver-related outcomes (SLROs, including cirrhosis, hepatocellular carcinoma, etc) was assessed in a UK Biobank subcohort (n=1955; median 13.7-year follow-up). Head-to-head comparisons with existing indices were performed. Results: — The predictive model, designated as FMO (Fibrotic/at-risk MASH in Obesity), incorporated aspartate aminotransferase, alanine aminotransferase, triglyceride, and high-density lipoprotein cholesterol. The FMO model demonstrated robust discrimination in derivation (AUROC=0.874, 95% CI 0.844-0.905) and nationwide external validation cohorts (AUROCs=0.803-0.874), and in global validation in both NHANES and UK Biobank (AUROCs=0.866 and 0.753, respectively). Longitudinal analysis confirmed SLROs prediction (Harrell’s C- index=0.703). In the derivation cohort, the FMO model demonstrated optimal rule-out [cutoff 0.05, sensitivity ≥0.90, negative predictive value (NPV) 0.976] and rule-in [cutoff 0.22, specificity ≥0.90, positive predictive value (PPV) 0.481] performance. External validation showed NPVs of 0.907-1.00 and PPVs of 0.333-0.630. Comparative analyses revealed superior diagnostic performance of the FMO model versus some existing models. Conclusion: — The FMO is an accurate and cost-effective non-invasive score for at-risk MASH identification in populations with obesity.
{"title":"Development and validation of a non-invasive score for at-risk metabolic dysfunction-associated steatohepatitis in individuals with obesity undergoing bariatric surgery","authors":"Xin Huang, Tao Zhu, Shumin Li, Teng Liu, Shibo Lin, Hui Liang, Mingwei Zhong, Xitai Sun, Liyong Chen, Hao Bai, Zehua Zhao, Xuehui Chu, Zhiyong Dong, Guangyong Zhang, Shaozhuang Liu","doi":"10.1097/hep.0000000000001612","DOIUrl":"https://doi.org/10.1097/hep.0000000000001612","url":null,"abstract":"Background: — At-risk metabolic dysfunction-associated steatohepatitis (MASH) elevates risks of liver-related and all-cause morbidity and mortality. We developed and validated a non-invasive score using routine clinical indicators to identity at-risk MASH in obesity. Methods: — Using data from 1,961 individuals across 5 independent bariatric cohorts with liver biopsy, we developed the predictive score in one derivation cohort (n=1095), performed internal validation (bootstrapping), and conducted external validation using the remaining four biopsy-confirmed cohorts (n=866). The score was also validated in the international overweight/obese cohorts from UK Biobank (n=15745) and NHANES database (n=1573). Predictive value for severe liver-related outcomes (SLROs, including cirrhosis, hepatocellular carcinoma, etc) was assessed in a UK Biobank subcohort (n=1955; median 13.7-year follow-up). Head-to-head comparisons with existing indices were performed. Results: — The predictive model, designated as FMO (Fibrotic/at-risk MASH in Obesity), incorporated aspartate aminotransferase, alanine aminotransferase, triglyceride, and high-density lipoprotein cholesterol. The FMO model demonstrated robust discrimination in derivation (AUROC=0.874, 95% CI 0.844-0.905) and nationwide external validation cohorts (AUROCs=0.803-0.874), and in global validation in both NHANES and UK Biobank (AUROCs=0.866 and 0.753, respectively). Longitudinal analysis confirmed SLROs prediction (Harrell’s C- index=0.703). In the derivation cohort, the FMO model demonstrated optimal rule-out [cutoff 0.05, sensitivity ≥0.90, negative predictive value (NPV) 0.976] and rule-in [cutoff 0.22, specificity ≥0.90, positive predictive value (PPV) 0.481] performance. External validation showed NPVs of 0.907-1.00 and PPVs of 0.333-0.630. Comparative analyses revealed superior diagnostic performance of the FMO model versus some existing models. Conclusion: — The FMO is an accurate and cost-effective non-invasive score for at-risk MASH identification in populations with obesity.","PeriodicalId":177,"journal":{"name":"Hepatology","volume":"25 1","pages":""},"PeriodicalIF":13.5,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145509397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-13DOI: 10.1097/HEP.0000000000001617
Zobair M Younossi, Leyla de Avila, Salvatore Petta, Hannes Hagström, Seung Up Kim, Atsushi Nakajima, Javier Crespo, Laurent Castera, Naim Alkhouri, Ming-Hua Zheng, Sombat Treeprasertsuk, Prooksa Ananchuensook, Shalimar, Emmanuel Tsochatzis, Shenoy Kotacherry Trivikrama, Leena Kondarappassery Balakumaran, Jian-Gao Fan, Stuart K Roberts, Khalid Alswat, Vincent Wai-Sun Wong, Yusuf Yilmaz, Winston Dunn, Sven Francque, Ahmed Cordie, Ming-Lung Yu, Mattias Ekstedt, George Boon-Bee Goh, Claudia P Oliveira, Mario Guimaraes Pessoa, Wah Kheong Chan, Marlen Ivon Castellanos Fernandez, Ajay Duseja, Juan Pablo Arab, George Papatheodoridis, Giada Sebastiani, Cristiane Villela-Nogueira, Roberta D'Ambrosio, Pietro Lampertico, Khalid Alnaamani, A G Holleboom, Arun Valsan, Arathi Venu, Mohamed El-Kassas, Grazia Pennisi, Ying Shang, Wen-Yue Liu, Hye Won Lee, Takashi Kobayashi, Satoru Kakizaki, Cyrielle Caussy, Brian Pearlman, Paula Iruzubieta, Rida Nadeem, Felice Cinque, Antonia Neonaki, Mirko Zoncapé, Rui-Xu Yang, Sherlot Juan Song, Nicholas Dunn, Zouhir Gadi, Ming-Lun Yeh, Kevin Kim-Jun The, Sanjiv Mahadeva, Licet Gonzalez Fabian, Ahmed Almohsen, Nathalie Leite, Nicola Pugliese, Johan Vessby, Chencheng Xie, Narendra Singh Choudhary, Ethan Friend, Maria Poca, Takumi Kawaguchi, Francesco Paolo Russo, Adrian Gadano, Luis Antonio Diaz, Ashwani K Singal, Berenice Segrestin, Nadege Gunn, Didac Mauricio, Marco Arrese, Anna Fracanzani, Brian Lam, Andrei Racila, Saleh A Alqahtani, Maria Stepanova
Background: Advanced histologic fibrosis is a major predictor of mortality in metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to identify advanced fibrosis clinical determinants across diverse MASLD populations and to assess the prognostic value of non-invasive markers (NITs) of fibrosis for adverse outcomes.
Methods: The Global MASLD (G-MASLD) enrolled biopsy-confirmed MASLD patients with clinical, histologic, and non-invasive test (NIT) data. Factors associated with the presence of advanced histologic fibrosis (F3-F4) in MASLD and clinical outcomes were assessed.
Results: There were 17,792 MASLD patients. Advanced fibrosis (≥F3) was present in 35%. The prevalence of type 2 diabetes (T2D) increased stepwise with fibrosis stage, from 28% in F0 to 70% in F4 (trend p<0.0001). Independent predictors of advanced fibrosis included older age, T2D, and obesity, although the association with obesity varied by region. Among patients with follow-up (mean 6.6 y), 6.5% died and 10.1% experienced a clinical event. Older age, male sex, T2D, and obesity were independent predictors of both mortality and clinical events (p<0.05). Fibrosis severity, whether defined histologically or by NITs, was strongly associated with higher risks of death and liver-related outcomes (all aHR>1.0, p<0.001). Five-year mortality was 2.1% overall, rising to 8.3% in patients with cirrhosis, and exceeded 10% among those with high-risk NIT score values.
Conclusions: In this large global biopsy-based MASLD cohort, advanced fibrosis was highly prevalent and strongly linked to T2D. Both histologic fibrosis and NITs were independent predictors of mortality and clinical outcomes, underscoring the prognostic value of fibrosis assessment with non-invasive tests.
{"title":"Predictors of fibrosis, clinical events and mortality in MASLD: Data from the Global-MASLD study.","authors":"Zobair M Younossi, Leyla de Avila, Salvatore Petta, Hannes Hagström, Seung Up Kim, Atsushi Nakajima, Javier Crespo, Laurent Castera, Naim Alkhouri, Ming-Hua Zheng, Sombat Treeprasertsuk, Prooksa Ananchuensook, Shalimar, Emmanuel Tsochatzis, Shenoy Kotacherry Trivikrama, Leena Kondarappassery Balakumaran, Jian-Gao Fan, Stuart K Roberts, Khalid Alswat, Vincent Wai-Sun Wong, Yusuf Yilmaz, Winston Dunn, Sven Francque, Ahmed Cordie, Ming-Lung Yu, Mattias Ekstedt, George Boon-Bee Goh, Claudia P Oliveira, Mario Guimaraes Pessoa, Wah Kheong Chan, Marlen Ivon Castellanos Fernandez, Ajay Duseja, Juan Pablo Arab, George Papatheodoridis, Giada Sebastiani, Cristiane Villela-Nogueira, Roberta D'Ambrosio, Pietro Lampertico, Khalid Alnaamani, A G Holleboom, Arun Valsan, Arathi Venu, Mohamed El-Kassas, Grazia Pennisi, Ying Shang, Wen-Yue Liu, Hye Won Lee, Takashi Kobayashi, Satoru Kakizaki, Cyrielle Caussy, Brian Pearlman, Paula Iruzubieta, Rida Nadeem, Felice Cinque, Antonia Neonaki, Mirko Zoncapé, Rui-Xu Yang, Sherlot Juan Song, Nicholas Dunn, Zouhir Gadi, Ming-Lun Yeh, Kevin Kim-Jun The, Sanjiv Mahadeva, Licet Gonzalez Fabian, Ahmed Almohsen, Nathalie Leite, Nicola Pugliese, Johan Vessby, Chencheng Xie, Narendra Singh Choudhary, Ethan Friend, Maria Poca, Takumi Kawaguchi, Francesco Paolo Russo, Adrian Gadano, Luis Antonio Diaz, Ashwani K Singal, Berenice Segrestin, Nadege Gunn, Didac Mauricio, Marco Arrese, Anna Fracanzani, Brian Lam, Andrei Racila, Saleh A Alqahtani, Maria Stepanova","doi":"10.1097/HEP.0000000000001617","DOIUrl":"https://doi.org/10.1097/HEP.0000000000001617","url":null,"abstract":"<p><strong>Background: </strong>Advanced histologic fibrosis is a major predictor of mortality in metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to identify advanced fibrosis clinical determinants across diverse MASLD populations and to assess the prognostic value of non-invasive markers (NITs) of fibrosis for adverse outcomes.</p><p><strong>Methods: </strong>The Global MASLD (G-MASLD) enrolled biopsy-confirmed MASLD patients with clinical, histologic, and non-invasive test (NIT) data. Factors associated with the presence of advanced histologic fibrosis (F3-F4) in MASLD and clinical outcomes were assessed.</p><p><strong>Results: </strong>There were 17,792 MASLD patients. Advanced fibrosis (≥F3) was present in 35%. The prevalence of type 2 diabetes (T2D) increased stepwise with fibrosis stage, from 28% in F0 to 70% in F4 (trend p<0.0001). Independent predictors of advanced fibrosis included older age, T2D, and obesity, although the association with obesity varied by region. Among patients with follow-up (mean 6.6 y), 6.5% died and 10.1% experienced a clinical event. Older age, male sex, T2D, and obesity were independent predictors of both mortality and clinical events (p<0.05). Fibrosis severity, whether defined histologically or by NITs, was strongly associated with higher risks of death and liver-related outcomes (all aHR>1.0, p<0.001). Five-year mortality was 2.1% overall, rising to 8.3% in patients with cirrhosis, and exceeded 10% among those with high-risk NIT score values.</p><p><strong>Conclusions: </strong>In this large global biopsy-based MASLD cohort, advanced fibrosis was highly prevalent and strongly linked to T2D. Both histologic fibrosis and NITs were independent predictors of mortality and clinical outcomes, underscoring the prognostic value of fibrosis assessment with non-invasive tests.</p>","PeriodicalId":177,"journal":{"name":"Hepatology","volume":" ","pages":""},"PeriodicalIF":15.8,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-12DOI: 10.1097/hep.0000000000001620
Richard K. Sterling
{"title":"FIB-4 turns 20: A lesson of serendipity","authors":"Richard K. Sterling","doi":"10.1097/hep.0000000000001620","DOIUrl":"https://doi.org/10.1097/hep.0000000000001620","url":null,"abstract":"","PeriodicalId":177,"journal":{"name":"Hepatology","volume":"43 1","pages":""},"PeriodicalIF":13.5,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145498414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1097/HEP.0000000000001615
Jian Huang
{"title":"Letter to the Editor: Survival analysis pitfalls in MASLD: Proportional hazards, immortal time, and follow-up discrepancies.","authors":"Jian Huang","doi":"10.1097/HEP.0000000000001615","DOIUrl":"https://doi.org/10.1097/HEP.0000000000001615","url":null,"abstract":"","PeriodicalId":177,"journal":{"name":"Hepatology","volume":" ","pages":""},"PeriodicalIF":15.8,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145706706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1097/HEP.0000000000001610
Mingchen Xie, Haitao Wu, Jian Xu
{"title":"Letter to the Editor: From risk alert to decision support: Enhancing the clinical value of the AI model for cholangiocarcinoma.","authors":"Mingchen Xie, Haitao Wu, Jian Xu","doi":"10.1097/HEP.0000000000001610","DOIUrl":"10.1097/HEP.0000000000001610","url":null,"abstract":"","PeriodicalId":177,"journal":{"name":"Hepatology","volume":" ","pages":""},"PeriodicalIF":15.8,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145487322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1097/HEP.0000000000001611
Yashbir Singh, John E Eaton, Bradley J Erickson, Gregory J Gores
{"title":"Reply: From risk alert to decision support: Enhancing the clinical value of the AI model for cholangiocarcinoma.","authors":"Yashbir Singh, John E Eaton, Bradley J Erickson, Gregory J Gores","doi":"10.1097/HEP.0000000000001611","DOIUrl":"10.1097/HEP.0000000000001611","url":null,"abstract":"","PeriodicalId":177,"journal":{"name":"Hepatology","volume":" ","pages":""},"PeriodicalIF":15.8,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145487239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1097/HEP.0000000000001609
Jie Zhao, Lidan Hou, Kenneth J Dery, Xiaoyi Yuan, Kang Ho Kim, Jerzy W Kupiec-Weglinski, David R Hall, Caitlin J Thornley, Mark J Hobeika, Holger K Eltzschig, Cynthia Ju
Hepatic ischemia-reperfusion injury (H-IRI) is a critical complication in liver surgery and liver transplantation, contributing to graft dysfunction and poor clinical outcomes. When hepatocyte protective mechanisms are insufficient to counteract energy depletion and oxidative stress during ischemia, cell death occurs. Tissue damage during H-IRI leads to the release of damage-associated molecular patterns (DAMPs), which recruit and activate immune cells such as neutrophils and monocytes, orchestrating the initiation, progression, and eventual resolution of sterile inflammation. Extended criteria donor (ECD) livers, particularly steatotic ones, are more vulnerable to H-IRI, leading to poorer outcomes and limiting expansion of the donor pool. However, the mechanisms underlying this increased vulnerability are not yet fully understood. Emerging therapeutic strategies, including machine perfusion technologies, ischemic preconditioning, pharmacological interventions and others, offer promise for mitigating H-IRI by either attenuating early injury triggers, enhancing intrinsic survival pathways, or restraining excessive inflammatory responses. Despite considerable progress in understanding H-IRI, further research is needed to identify additional therapeutic targets, particularly in the context of ECD livers, to develop effective, targeted interventions that can improve clinical outcomes.
{"title":"Hepatic ischemia reperfusion injury: Underlying mechanisms and concepts in liver surgery and liver transplantation.","authors":"Jie Zhao, Lidan Hou, Kenneth J Dery, Xiaoyi Yuan, Kang Ho Kim, Jerzy W Kupiec-Weglinski, David R Hall, Caitlin J Thornley, Mark J Hobeika, Holger K Eltzschig, Cynthia Ju","doi":"10.1097/HEP.0000000000001609","DOIUrl":"https://doi.org/10.1097/HEP.0000000000001609","url":null,"abstract":"<p><p>Hepatic ischemia-reperfusion injury (H-IRI) is a critical complication in liver surgery and liver transplantation, contributing to graft dysfunction and poor clinical outcomes. When hepatocyte protective mechanisms are insufficient to counteract energy depletion and oxidative stress during ischemia, cell death occurs. Tissue damage during H-IRI leads to the release of damage-associated molecular patterns (DAMPs), which recruit and activate immune cells such as neutrophils and monocytes, orchestrating the initiation, progression, and eventual resolution of sterile inflammation. Extended criteria donor (ECD) livers, particularly steatotic ones, are more vulnerable to H-IRI, leading to poorer outcomes and limiting expansion of the donor pool. However, the mechanisms underlying this increased vulnerability are not yet fully understood. Emerging therapeutic strategies, including machine perfusion technologies, ischemic preconditioning, pharmacological interventions and others, offer promise for mitigating H-IRI by either attenuating early injury triggers, enhancing intrinsic survival pathways, or restraining excessive inflammatory responses. Despite considerable progress in understanding H-IRI, further research is needed to identify additional therapeutic targets, particularly in the context of ECD livers, to develop effective, targeted interventions that can improve clinical outcomes.</p>","PeriodicalId":177,"journal":{"name":"Hepatology","volume":" ","pages":""},"PeriodicalIF":15.8,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145487264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1097/HEP.0000000000001616
Jiahang He, Qing Xie, Zhujun Cao
{"title":"Letter to the Editor: Comments on the Study-Body size disparities limit women's access to liver transplantation under the MELD 3.0 scoring system.","authors":"Jiahang He, Qing Xie, Zhujun Cao","doi":"10.1097/HEP.0000000000001616","DOIUrl":"10.1097/HEP.0000000000001616","url":null,"abstract":"","PeriodicalId":177,"journal":{"name":"Hepatology","volume":" ","pages":""},"PeriodicalIF":15.8,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145487285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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