TY - JOUR
T1 - An Observational Data Meta-analysis on the Differences in Prevalence and Risk Factors Between MAFLD vs NAFLD
AU - Lim, Grace En Hui
AU - Tang, Ansel
AU - Ng, Cheng Han
AU - Chin, Yip Han
AU - Lim, Wen Hui
AU - Tan, Darren Jun Hao
AU - Yong, Jie Ning
AU - Xiao, Jieling
AU - Lee, Chloe Wen Min
AU - Chan, Mark
AU - Chew, Nicholas WS
AU - Xuan Tan, Eunice Xiang
AU - Siddiqui, Mohammad Shadab
AU - Huang, Daniel
AU - Noureddin, Mazen
AU - Sanyal, Arun J.
AU - Muthiah, Mark D.
N1 - Funding Information:
Grace En Hui Lim (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Writing – original draft: Lead; Writing – review & editing: Lead), Ansel Tang (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Writing – original draft: Lead; Writing – review & editing: Lead), Cheng Han Ng (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Writing – original draft: Lead; Writing – review & editing: Lead), Yip Han Chin (Conceptualization: Equal; Data curation: Equal; Formal analysis: Equal; Writing – original draft: Equal; Writing – review & editing: Equal), Wen Hui Lim (Conceptualization: Equal; Data curation: Equal; Formal analysis: Equal; Writing – original draft: Equal; Writing – review & editing: Equal), Darren Jun Hao Tan (Conceptualization: Equal; Data curation: Equal; Formal analysis: Equal; Writing – original draft: Equal), Jie Ning Yong (Conceptualization: Equal; Data curation: Equal; Writing – original draft: Equal), Jieling Xiao (Conceptualization: Equal; Data curation: Equal; Writing – original draft: Equal), Chloe Wen-Min Lee (Conceptualization: Equal; Data curation: Equal; Writing – original draft: Equal), Mark Chan (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Nicholas WS Chew (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Eunice Xiang Xuan Tan (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Mohammad Shadab Siddiqui (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Daniel Huang (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Mazen Noureddin (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Mark Dhinesh Muthiah (Conceptualization: Equal; Data curation: Equal; Formal analysis: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal), Arun J. Sanyal (Conceptualization: Equal; Supervision: Equal; Validation: Equal; Writing – review & editing: Equal)
Funding Information:
Conflicts of interest The authors disclose the following: Arun J. Sanyal is President of Sanyal Biotechnology and has stock options in Genfit, Akarna, Tiziana, Indalo, Durect; and Galmed; has served as a consultant to Astra Zeneca, Nitto Denko, Enyo, Ardelyx, Conatus, Nimbus, Amarin, Salix, Tobira, Takeda, Jannsen, Gilead, Terns, Birdrock, Merck, Valeant, Boehringer-Ingelheim, Lilly, Hemoshear, Zafgen, Novartis, Novo Nordisk, Pfizer, Exhalenz, and Genfit; has been an unpaid consultant to Intercept, Echosens, Immuron, Galectin, Fractyl, Syntlogic, Affimune, Chemomab, Zydus, Nordic Bioscience, Albireo, Prosciento, Surrozen, and Bristol Myers Squibb; and receives royalties from Elsevier and UptoDate; his institution has received grant support from Gilead, Salix, Tobira, Bristol Myers, Shire, Intercept, Merck, Astra Zeneca, Malinckrodt, Cumberland, and Norvatis. Mazen Noureddin has been on the advisory board for 89BIO, Gilead, Intercept, Pfizer, Novo Nordisk, Blade, EchoSens, Fractyl, Terns, Siemens, and Roche diagnostic; has received research support from Allergan, BMS, Gilead, Galmed, Galectin, Genfit, Conatus, Enanta, Madrigal, Novartis, Pfizer, Shire, Viking, and Zydus; and is a minor shareholder or has stocks in Anaetos, Rivus Pharma, and Viking. The remaining authors disclose no conflicts.
Publisher Copyright:
© 2023 AGA Institute
PY - 2023/3
Y1 - 2023/3
N2 - BACKGROUND & AIMS: The shift to redefine nonalcoholic fatty liver disease (NAFLD) as metabolic associated fatty liver disease (MAFLD) can profoundly affect patient care, health care professionals, and progress within the field. To date, there remains no consensus on the characterization of NAFLD vs MAFLD. Thus, this study sought to compare the differences between the natural history of NAFLD and MAFLD.METHODS: Medline and Embase databases were searched to include articles on prevalence, risk factors, or outcomes of patients with MAFLD or NAFLD. Meta-analysis of proportions was conducted using the generalized linear mix model. Risk factors and outcomes were evaluated in conventional pairwise meta-analysis.RESULTS: Twenty-two articles involving 379,801 patients were included. Pooled prevalence of MAFLD was 39.22% (95% confidence interval [CI], 30.96%-48.15%) with the highest prevalence in Europe and Asia, followed by North America. The current MAFLD Definition only accounted for 81.59% (95% CI, 66.51%-90.82%) of NAFLD diagnoses. Patients had increased odds of being diagnosed with MAFLD compared with NAFLD (odds ratio, 1.37; 95% CI, 1.16-1.63; P < .001). Imaging modality resulted in a significantly higher odds of being diagnosed with MAFLD compared with NAFLD, but not biopsy. MAFLD was significantly associated with males, higher body mass index, hypertension, diabetes, lipids, transaminitis, and greater fibrosis scores compared with NAFLD.CONCLUSIONS: There were stark differences in the prevalence and risk factors between MAFLD and NAFLD. However, in the use of the MAFLD Definition, a greater emphasis on the management of concomitant metabolic diseases and a collaborative effort is required to explore the complex pathophysiologic mechanisms underlying the disease.
AB - BACKGROUND & AIMS: The shift to redefine nonalcoholic fatty liver disease (NAFLD) as metabolic associated fatty liver disease (MAFLD) can profoundly affect patient care, health care professionals, and progress within the field. To date, there remains no consensus on the characterization of NAFLD vs MAFLD. Thus, this study sought to compare the differences between the natural history of NAFLD and MAFLD.METHODS: Medline and Embase databases were searched to include articles on prevalence, risk factors, or outcomes of patients with MAFLD or NAFLD. Meta-analysis of proportions was conducted using the generalized linear mix model. Risk factors and outcomes were evaluated in conventional pairwise meta-analysis.RESULTS: Twenty-two articles involving 379,801 patients were included. Pooled prevalence of MAFLD was 39.22% (95% confidence interval [CI], 30.96%-48.15%) with the highest prevalence in Europe and Asia, followed by North America. The current MAFLD Definition only accounted for 81.59% (95% CI, 66.51%-90.82%) of NAFLD diagnoses. Patients had increased odds of being diagnosed with MAFLD compared with NAFLD (odds ratio, 1.37; 95% CI, 1.16-1.63; P < .001). Imaging modality resulted in a significantly higher odds of being diagnosed with MAFLD compared with NAFLD, but not biopsy. MAFLD was significantly associated with males, higher body mass index, hypertension, diabetes, lipids, transaminitis, and greater fibrosis scores compared with NAFLD.CONCLUSIONS: There were stark differences in the prevalence and risk factors between MAFLD and NAFLD. However, in the use of the MAFLD Definition, a greater emphasis on the management of concomitant metabolic diseases and a collaborative effort is required to explore the complex pathophysiologic mechanisms underlying the disease.
KW - Liver Diseases
KW - Metabolic Associated Fatty Liver Disease
KW - Nonalcoholic Fatty Liver Disease
KW - Prevalence
KW - Risk Factors
KW - Asia
KW - Biopsy
KW - Humans
KW - Non-alcoholic Fatty Liver Disease
KW - Male
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U2 - 10.1016/j.cgh.2021.11.038
DO - 10.1016/j.cgh.2021.11.038
M3 - Review article
C2 - 34871813
AN - SCOPUS:85123740722
VL - 21
SP - 619-629.e7
JO - Clinical Gastroenterology and Hepatology
JF - Clinical Gastroenterology and Hepatology
SN - 1542-3565
IS - 3
ER -