Meta-Analysis

. 2023 Sep;79(3):592-604.

doi: 10.1016/j.jhep.2023.04.025. Epub 2023 Apr 29.

An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography

Jia-Xu Liang¹, Javier Ampuero², Hao Niu³, Kento Imajo⁴, Mazen Noureddin⁵, Jaideep Behari⁶, Dae Ho Lee⁷, Richard L Ehman⁸, Fredrik Rorsman⁹, Johan Vessby⁹, Juan R Lacalle¹⁰, Ferenc E Mózes¹¹, Michael Pavlides¹², Quentin M Anstee¹³, Stephen A Harrison¹¹, Javier Castell¹⁴, Rohit Loomba¹⁵, Manuel Romero-Gómez¹⁶; LITMUS Consortium Investigators

Affiliations

¹ Digestive Diseases Unit and CIBERehd, Virgen del Rocío University Hospital, Seville, Spain; Institute of Biomedicine of Seville (HUVR/CSIC/US), University of Seville, Seville, Spain; Department of Diagnostic Radiology, The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
² Digestive Diseases Unit and CIBERehd, Virgen del Rocío University Hospital, Seville, Spain; Institute of Biomedicine of Seville (HUVR/CSIC/US), University of Seville, Seville, Spain.
³ Digestive System and Clinical Pharmacology Unit, Virgen de la Victoria University Hospital, Biomedical Research Institute of Malaga and Nanomedicine Platform-IBIMA (Plataforma BIONAND), University of Malaga, Málaga, Spain; Biomedical Research Network Center for Hepatic and Digestive Diseases (CIBERehd), Carlos III Health Institute, Madrid, Spain.
⁴ Department of Gastroenterology, Yokohama City University Graduate School of Medicine; Yokohama, Japan.
⁵ Fatty Liver Program, Division of Digestive and Liver Diseases, Comprehensive Transplant Program, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
⁶ Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, Center for Liver Diseases, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
⁷ Department of Internal Medicine, Gachon University College of Medicine (Gachon University Gil Medical Center), Incheon, South Korea.
⁸ Department of Diagnostic Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA.
⁹ Department of Medical Sciences, Section of Gastroenterology and Hepatology, Uppsala University, Uppsala, Sweden.
¹⁰ Biostatistics Unit, Department of Preventive Medicine and Public Health, University of Seville, Seville, Spain.
¹¹ Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
¹² Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Translational Gastroenterology Unit, University of Oxford, Oxford, UK.
¹³ Translational and Clinical Research Institute; Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK; Newcastle NIHR Biomedical Research Centre, Newcastle Upon Tyne Hospitals, NHS Trust, Newcastle Upon Tyne, UK.
¹⁴ Department of Radiology, Virgen del Rocío University Hospital, Seville, Spain.
¹⁵ Division of Epidemiology, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA; NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
¹⁶ Digestive Diseases Unit and CIBERehd, Virgen del Rocío University Hospital, Seville, Spain; Institute of Biomedicine of Seville (HUVR/CSIC/US), University of Seville, Seville, Spain. Electronic address: mromerogomez@us.es.

PMID: 37121437
PMCID: PMC10623141
DOI: 10.1016/j.jhep.2023.04.025

Meta-Analysis

An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography

Jia-Xu Liang et al. J Hepatol. 2023 Sep.

. 2023 Sep;79(3):592-604.

doi: 10.1016/j.jhep.2023.04.025. Epub 2023 Apr 29.

Authors

Affiliations

¹ Digestive Diseases Unit and CIBERehd, Virgen del Rocío University Hospital, Seville, Spain; Institute of Biomedicine of Seville (HUVR/CSIC/US), University of Seville, Seville, Spain; Department of Diagnostic Radiology, The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
² Digestive Diseases Unit and CIBERehd, Virgen del Rocío University Hospital, Seville, Spain; Institute of Biomedicine of Seville (HUVR/CSIC/US), University of Seville, Seville, Spain.
³ Digestive System and Clinical Pharmacology Unit, Virgen de la Victoria University Hospital, Biomedical Research Institute of Malaga and Nanomedicine Platform-IBIMA (Plataforma BIONAND), University of Malaga, Málaga, Spain; Biomedical Research Network Center for Hepatic and Digestive Diseases (CIBERehd), Carlos III Health Institute, Madrid, Spain.
⁴ Department of Gastroenterology, Yokohama City University Graduate School of Medicine; Yokohama, Japan.
⁵ Fatty Liver Program, Division of Digestive and Liver Diseases, Comprehensive Transplant Program, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
⁶ Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, Center for Liver Diseases, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
⁷ Department of Internal Medicine, Gachon University College of Medicine (Gachon University Gil Medical Center), Incheon, South Korea.
⁸ Department of Diagnostic Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA.
⁹ Department of Medical Sciences, Section of Gastroenterology and Hepatology, Uppsala University, Uppsala, Sweden.
¹⁰ Biostatistics Unit, Department of Preventive Medicine and Public Health, University of Seville, Seville, Spain.
¹¹ Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
¹² Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Translational Gastroenterology Unit, University of Oxford, Oxford, UK.
¹³ Translational and Clinical Research Institute; Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK; Newcastle NIHR Biomedical Research Centre, Newcastle Upon Tyne Hospitals, NHS Trust, Newcastle Upon Tyne, UK.
¹⁴ Department of Radiology, Virgen del Rocío University Hospital, Seville, Spain.
¹⁵ Division of Epidemiology, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA; NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
¹⁶ Digestive Diseases Unit and CIBERehd, Virgen del Rocío University Hospital, Seville, Spain; Institute of Biomedicine of Seville (HUVR/CSIC/US), University of Seville, Seville, Spain. Electronic address: mromerogomez@us.es.

PMID: 37121437
PMCID: PMC10623141
DOI: 10.1016/j.jhep.2023.04.025

Abstract

Background & aims: We conducted an individual patient data meta-analysis to establish stiffness cut-off values for magnetic resonance elastography (MRE) in staging liver fibrosis and to assess potential confounding factors.

Methods: A systematic review of the literature identified studies reporting MRE data in patients with NAFLD. Data were obtained from the corresponding authors. The pooled diagnostic cut-off value for the various fibrosis stages was determined in a two-stage meta-analysis. Multilevel modelling methods were used to analyse potential confounding factors influencing the diagnostic accuracy of MRE in staging liver fibrosis.

Results: Eight independent cohorts comprising 798 patients were included in the meta-analysis. The area under the receiver operating characteristic curve (AUROC) for MRE in detecting significant fibrosis was 0.92 (sensitivity, 79%; specificity, 89%). For advanced fibrosis, the AUROC was 0.92 (sensitivity, 87%; specificity, 88%). For cirrhosis, the AUROC was 0.94 (sensitivity, 88%, specificity, 89%). Cut-offs were defined to explore concordance between MRE and histopathology: ≥F2, 3.14 kPa (pretest probability, 39.4%); ≥F3, 3.53 kPa (pretest probability, 24.1%); and F4, 4.45 kPa (pretest probability, 8.7%). In generalized linear mixed model analysis, histological steatohepatitis with higher inflammatory activity (odds ratio 2.448, 95% CI 1.180-5.079, p <0.05) and high gamma-glutamyl transferase (GGT) concentration (>120U/L) (odds ratio 3.388, 95% CI 1.577-7.278, p <0.01] were significantly associated with elevated liver stiffness, and thus affecting accuracy in staging early fibrosis (F0-F1). Steatosis, as measured by magnetic resonance imaging proton density fat fraction, and body mass index(BMI) were not confounders.

Conclusions: MRE has excellent diagnostic performance for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Elevated inflammatory activity and GGT level may lead to overestimation of early liver fibrosis, but anthropometric measures such as BMI or the degree of steatosis do not.

Impact and implications: This individual patient data meta-analysis of eight international cohorts, including 798 patients, demonstrated that MRE achieves excellent diagnostic accuracy for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Cut-off values (significant fibrosis, 3.14 kPa; advanced fibrosis, 3.53 kPa; and cirrhosis, 4.45 kPa) were established. Elevated inflammatory activity and gamma-glutamyltransferase level may affect the diagnostic accuracy of MRE, leading to overestimation of liver fibrosis in early stages. We observed no impact of diabetes, obesity, or any other metabolic disorder on the diagnostic accuracy of MRE.

Keywords: Elastography; Fibrosis; GGT; Magnetic Resonance; NAFLD; NASH.

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Conflict of interest statement

Conflicts of interest

The Mayo Clinic and RLE have intellectual property rights and a financial interest in MRE technology. RL serves as a consultant to Aardvark Therapeutics, Altimmune, Anylam/Regeneron, Amgen, Arrowhead, AstraZeneca, Bristol Myer Squibb, CohBar, Eli Lilly, Galmed, Gilead, Glympse Bio, HighTide, Inipharma, Intercept, Inventiva, Ionis, Janssen, Madrigal, Metacrine, NGM Bio, Novartis, Novo Nordisk, Merck, Pfizer, Sagimet, Theratechnologies, 89bio, Terns, and Viking. In addition, his institutions have received research grants from Arrowhead, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galectin, Galmed, Gilead, Intercept, Hanmi, Intercept, Inventiva, Ionis, Janssen, Madrigal, Merck, NGM Bio, Novo Nordisk, Merck, Pfizer, Sonic Incytes, and Terns. He is also a co-founder of LipoNexus Inc. QMA is a coordinator of the EU IMI-2 LITMUS consortium, which is funded by the EU Horizon 2020 programme and EFPIA. His institutions have received research grants from Abbvie, AstraZeneca, Boehringer Ingelheim, Glympse Bio, Intercept, Novartis, Pfizer, Allergan/Tobira, GlaxoSmithKline, Glympse Bio, Intercept, and Novartis. He also serves as a consultant on behalf of Newcastle University for Alimentiv, Akero, AstraZeneca, Axcella, 89bio, Boehringer Ingelheim, Bristol Myers Squibb, Galmed, Genfit, Genentech, Gilead, GlaxoSmithKline, Hanmi, HistoIndex, Intercept, Inventiva, Ionis, IQVIA, Janssen, Madrigal, Medpace, Merck, NGM Bio, Novartis, Novo Nordisk, PathAI, Pfizer, Poxel, Resolution Therapeutics, Roche, Ridgeline Therapeutics, RTI, Shionogi, and Terns. In addition, he is a speaker for Fishawack, Integritas Communications, Kenes, Novo Nordisk, Madrigal, Medscape, and Springer Healthcare, and receives royalties from Elsevier Ltd. MP is a shareholder in Perspectum Ltd. MN has been on the advisory board and served as a consultant for 89bio, Altimmune, Gilead, CohBar, Cytodyn, ChronWell, Intercept, Pfizer, Novo Nordisk, Blade, EchoSens, Fractyl, Madrgial, NorthSea, Prespecturm, Terns, Siemens, and Roche Diagnostics. Moreover, he has received research support from Allergan, BMS, Gilead, Galmed, Galectin, Genfit, Conatus, Enanta, Madrigal, Novartis, Pfizer, Shire, Viking, and Zydus. He is also a shareholder or has stocks in Anaetos, Ciema, Rivus Pharma, and Viking. SAH serves as a scientific advisor or consultant for Akero, Alentis, Altimmune, Arrowhead, Axcella, BMS, ChronWell, Echosens, Galectin, Gilead, Hepion, Hepagene, HistoIndex, Intercept, Madrigal, Medpace, Metacrine, NGM Bio, NorthSea, Novartis, Novo Nordisk, PathAI, Poxel, Sagimet, Terns, and Viking. He has stock options in Akero, Cirius, Galectin, Genfit, Hepion, HistoIndex, PathAI, Metacrine, NGM Bio, and NorthSea. In addition, he has received grants and/or research support from Akero, Axcella, BMS, Cirius, CiVi Biopharma, Conatus, Corcept, Cymabay, Enyo, Galectin, Genentech, Genfit, Gilead, Hepion, HighTide, Intercept, Madrigal, Metacrine, NGM Bio, Novartis, Novo Nordisk, NorthSea, Pfizer, Sagimet, Viking, and 89bio. FR is a member of the advisory board for Norgine and Intercept; has received a speaker fee from Norgine and Gore; and has received research support from Norgine, Antaros Medical, and Boehringer Ingelheim. JV has received research support from Antaros Medical and Boehringer Ingelheim. JB has received research grant funding from Gilead, Pfizer, and ENDRA Life Sciences. In addition, he has signed institutional research contracts with Intercept, Pfizer, Galectin, Exact Sciences, Inventiva, Enanta, Shire, Gilead, Allergan, Celgene, Galmed, and Genentech. MR-G is a scientific advisor, consultant, and/or speaker for Abbvie, Alpha Sigma, Allergan, AstraZeneca, Axcella, BMS, Boehringer Ingelheim, Gilead, Intercept, Inventia, Kaleido, MSD, Novo Nordisk, Pfizer, Prosciento, Rubió, Siemens, Shionogi, Sobi, and Zydus. He has received research grants from Gilead, Intercept, and Siemens, and is a co-inventor of Hepamet Fibrosis Score, DeMILI, and DeMILI 3.0. The other authors declare no conflict of interest that pertain to this work.

Please refer to the accompanying ICMJE disclosure forms for further details.

Figures

**Fig. 1.. Study identification and selection flow chart.**
MRE, magnetic resonance elastography.

**Fig. 2.. Liver stiffness values by MRE corresponding to each liver fibrosis stage.**
The bars represent the minimum and maximum; the top and bottom lines in the box represent the 25% and 75% levels, respectively; and the middle line indicates the median level. MRE, magnetic resonance elastography.

**Fig. 3.. Pooled cut-offs for staging liver fibrosis stage in patients with NAFLD.**
(A) Pooled cut-off for mild fibrosis (≥F1). (B) Pooled cut-off for significant fibrosis (≥F2). (C) Pooled cut-off for advanced fibrosis (≥F3). (D) Pooled cut-off for cirrhosis (F4). Pooled cut-offs were estimated by study-level cut-offs in fixed or random-effects model meta-analyses and were displayed graphically as forest plots. The diamond symbol represents the pooled cut-off value, and its width represents the 95% CI. REML, restricted maximum likelihood.

See this image and copyright information in PMC

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An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography

Affiliations

An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Miscellaneous