Bariatric intervention improves metabolic dysfunction-associated steatohepatitis in patients with obesity: A systematic review and meta-analysis

Article information

Clin Mol Hepatol. 2024;30(3):561-576
Publication date (electronic) : 2024 June 3
doi : https://doi.org/10.3350/cmh.2023.0384
1Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang, Korea
2Department of Internal Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
3Department of Gastroenterology and Hepatology, Soonchunhyang University Bucheon Hospital, Bucheon, Korea
4National Evidence-based Healthcare Collaborating Agency, Seoul, Korea
5Biostatistics Collaboration Team, Research Institute, National Cancer Center, Goyang, Korea
6Department of Internal Medicine, Hanyang University School of Medicine, Seoul, Korea
Corresponding author : Yuri Cho Center for Liver and Pancreatobiliary Cancer, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang 10408, Korea Tel: +82-31-920-1680, Fax: +82-31-920-2799, E-mail: yuricho@ncc.re.kr
Dae Won Jun Department of Internal Medicine, Hanyang University School of Medicine, 222-1, Wangsimni-ro Seongdong-gu, Seoul 04763, Korea Tel: +82-2-2290-8334, Fax: +82-2-2298-9183, E-mail: noshin@hanyang.ac.kr
Editor: Silvia Sookoian, CONICET (National Scientific and Technical Research Council), Argentina
Received 2023 September 27; Revised 2024 May 26; Accepted 2024 June 1.

Abstract

Background/Aims

Bariatric intervention has been reported to be an effective way to improve metabolic dysfunction-associated steatotic liver disease (MASLD) in obese individuals. The current systemic review aimed to assess the changes in MRI-determined hepatic proton density fat fraction (MRI-PDFF) and nonalcoholic fatty liver disease activity score (NAS) after bariatric surgery or intragastric balloon/gastric banding in MASLD patients with obesity.

Methods

We searched various databases including PubMed, OVID Medline, EMBASE, and Cochrane Library. Primary outcomes were the changes in intrahepatic fat on MRI-PDFF and histologic features of metabolic dysfunction-associated steatohepatitis (MASH).

Results

Thirty studies with a total of 3,134 patients were selected for meta-analysis. Bariatric intervention significantly reduced BMI (ratio of means, 0.79) and showed 72% reduction of intrahepatic fat on MRI-PDFF at 6 months after bariatric intervention (ratio of means, 0.28). Eight studies revealed that NAS was reduced by 60% at 3–6 months compared to baseline, 40% at 12–24 months, and 50% at 36–60 months. Nineteen studies revealed that the proportion of patients with steatosis decreased by 44% at 3–6 months, 37% at 12–24 months, and 29% at 36–60 months; lobular inflammation by 36% at 12–24 months and 51% at 36–60 months; ballooning degeneration by 38% at 12–24 months; significant fibrosis (≥F2) by 18% at 12–24 months and by 17% at 36–60 months after intervention.

Conclusions

Bariatric intervention significantly improved MRI-PDFF and histologic features of MASH in patients with obesity. Bariatric intervention might be the effective alternative treatment option for patients with MASLD who do not respond to lifestyle modification or medical treatment.

Graphical Abstract

INTRODUCTION

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease (NAFLD), includes a spectrum of liver conditions, characterized by excessive fat in the liver, without proven secondary cause of hepatic fat accumulation. Although the pathophysiology of MASLD is not completely understood due to its complex and multifactorial nature, insulin resistance is considered to be a key factor driving the development of the disease [1]. Therefore, MASLD is thought to be a component of metabolic syndrome, which is a cluster of interconnected metabolic risk factors that increase the risk of developing type 2 diabetes mellitus (DM), hypertension, and cardiovascular disease [2]. Besides, it can gradually progress through various liver stages, from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), previously known as nonalcoholic steatohepatitis (NASH), liver fibrosis, cirrhosis, and eventually liver failure or hepatocellular carcinoma over several years or even decades [3]. The prevalence of MASLD has risen alongside the increasing prevalence of obesity and metabolic syndrome worldwide, with significantly higher prevalence in specific population, such as approximately 50–90% in obese individuals and 47–63% in patients with type 2 DM [4]. Considering its high prevalence and the implications in public health, addressing MASLD is of paramount importance.

The primary goal in addressing MASLD begins with lifestyle management aimed at achieving a weight loss, the only validated approach for the condition. Weight loss of more than 7–10% has been demonstrated to effectively improve liver steatosis, inflammation, and fibrosis [5]. In addition to lifestyle modification, medication, such as GLP-1 receptor agonist or GLP-1/GIP dual receptor agonist (a novel medication yielding the most potent result in weight loss), is known to improve the histological findings in MASLD [6]. However, apart from the cases of potential treatment failure, sustaining the reduced weight can indeed pose challenges, even with the assistance of new medications, particularly among certain populations. In such populations, surgical intervention may play a pivotal role in treating MASLD. Bariatric intervention is among the most effective weight loss interventions for morbidly obese individuals, even over long-term; it improves metabolic parameters as well as liver steatosis and inflammation. As of now, its indication includes those with BMI >35 kg/m2, regardless of comorbidities, or those with BMI >30 kg/m2 with the presence of MASH, type 2 DM or failure of non-surgical intervention [7].

Several meta-analyses have showed significant metabolic and histological improvements after bariatric surgery [8-12]. However, concerns regarding the controversial results regarding the effectiveness in more advanced forms of MASLD, such as MASH, persist [13,14]. Moreover, despite liver biopsy being the gold standard for diagnosis of MASLD, it is invasive and potentially life-threatening procedure, prompting the exploration of non-invasive evaluation methods for MASLD, such as magnetic resonance imaging proton-density fat fraction (MRI-PDFF). MRI-PDFF has garnered significant recognition for its diagnostic value, demonstrating high sensitivity and specificity in the assessment of MASLD [15]. Although several studies investigating the association between bariatric intervention and MASLD, assessed by MRI-PDFF, have been published till date, no meta-analysis using this method has been conducted yet.

In this study, we conducted a systemic review to evaluate the changes in BMI, NAS, as well as intrahepatic fat composition measured by MRI-PDFF, following bariatric intervention in patients with MASLD.

MATERIALS AND METHODS

Data sources and search strategy

The protocol for this systemic review was registered with PROSPERO (International Prospective Register of Systemic Reviews, CRD42041241243). The aim of this study is to identify the effect of bariatric intervention on MASLD, determined by histologic findings and/or MRI findings. This study was conducted along with others that identified the effect of exercise intervention on MASLD [16], or validated the accuracy of noninvasive scoring system in assessing liver fibrosis [17]. Study selection followed the Preferred Reporting Items for Systemic Review and Meta-analyses extension for Diagnostic Test Accuracy (PRISMA-DTA) statements [18]. We searched the Ovid-MEDLINE, EMBASE, KMBASE, Korean Studies Information Service System (KISS), and Cochrane library, covering the period from database inception, through January 1, 1997 to October 31, 2023. We only included papers published in English. The search keywords used were: metabolic dysfunction-associated steatotic liver disease, MASLD, metabolic dysfunction-associated steatohepatitis, MASH, nonalcoholic fatty liver disease, nonalcoholic fatty liver, NAFLD, nonalcoholic steatohepatitis, NASH, obesity/obese, bariatric surgery, intragastric balloon, and gastric banding.

Study selection and data extraction

Two researchers (Y.C. and S.H.K.) reviewed the screened papers independently, by their titles and abstracts, in the first screening. In the secondary screening, full text of the papers that passed the first screening was examined, providing specific reasons for any exclusions. During the process of literature selection, any discordance between the two clinical researchers was resolved through mutual consultation. In cases where a consensus could not be reached, the final decision was made by the research committee through a formal meeting. The study design, outcome measure (histology vs. MRI-PDFF), sample size, intervention, mean age, duration of follow-up, and BMI changes in each study were extracted as basal characteristics. The entire search process was administered by a professional statistician (M.Y.C. and D.L.).

Inclusion and exclusion criteria

The following criteria were required for studies to be selected: (1) patients who underwent bariatric surgery or intragastric balloon/gastric banding for obesity; and (2) those who were diagnosed with histologically proven MASLD or MASH designs included randomized controlled trials, cross-sectional studies, and cohort studies, both prospective and retrospective. Studies were excluded based on the following criteria: (1) case reports; (2) case series, in which less than five patients in total were involved; (3) reviews; (4) cell or animal studies; (5) studies on chronic viral hepatitis, such as hepatitis B or hepatitis C; (6) studies on human immunodeficiency virus; (7) studies on population with significant alcohol consumption; (8) studies with no histology result provided; or (9) pediatric studies.

Outcome assessed

Studies that reported at least one histologic or MRI variable were included in the analyses. All included studies presented baseline and follow-up BMI. Histologic variables are as follows: (1) NALFD activity score (NAS), which assesses the severity of inflammation and hepatocellular injury in liver biopsy [19], (2) Histologic features of MASH, including steatosis, lobular inflammation, ballooning degeneration, and fibrosis, and (3) worsening MASH. MRI variable includes the change in steatosis and BMI.

Quality assessment

We performed the quality assessment of the final selection of papers, based on key questions, using RoBANS tool for non-randomized controlled studies and Cochrane risk-of-bias tool for randomized controlled study. QUADAS-2 evaluation tool was used to evaluate the diagnostic accuracy. The following factors were checked: comparability of participants, selection of participants, confounding variables, measurement of exposure, blinding of outcome assessment, outcome evaluation, incomplete outcome data, and selective reporting. Publication bias was evaluated by a funnel plot for studies investigating populations with more than ten individuals. The certainty of the evidence was evaluated by Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, which considers factors such as risk of bias, inconsistency of results, indirectness of evidence, imprecision, and publication bias.

Statistical analysis

The process of meta-analysis with paired ratio of means data and proportion data involved the estimation of Hedge’s corrected standardized mean difference, under the assumption of a random-effects model, to account for heterogeneity across the studies. The pooled effect estimates between pre- and post-operation within each study’s specific time frame were derived to measure the effect size, using Freeman-Tukey variant of the arcsine square root transformation, along with a 95% confidence interval (CI). To address the differences in follow-up periods across the selected studies, we categorized the studies according to the length of the follow-up time in further analyses. Analysis of each pooled data is shown in a forest plot. Heterogeneity of the studies was assessed by Cochrane’s Q test; I2 statistics higher than 50% was considered indicative of significant heterogeneity, and more than 75% was considered “high” heterogeneity. Next, sensitivity analyses and meta-regression were conducted to assess the influence of other factors on diagnostic accuracy across the studies with significant heterogeneity. Cochrane Review Manager version 5.4 (London, UK), R Foundation for Statistical Computing version 4.1.2 (Vienna, Austria), and GRADEpro GDT were used in the analysis, with a significance level set at a P-value less than 0.05.

RESULTS

Study characteristics

From January 1, 1997 to October 31, 2023, a total of 1,546 papers were identified through preliminary data searching using search keywords described in the Methods section. The numbers of papers from each database are as follows: Ovid-MEDLINE (n=593), KMBASE (n=5), EMBASE (n=845), KISS (n=11), and Cochrane library (n=92). After removal of duplicates (n=1,069), 246 papers were excluded based on the title only. In the first screening, two researchers independently reviewed the screened papers by their titles and abstracts (n=231), followed by exclusion of 156 papers after review. Furthermore, we thoroughly examined the full-text articles of the remaining studies (n=75), resulting in an additional exclusion of 46 studies. Finally, thirty studies were incorporated into this analysis (Fig. 1). Out of all these papers, twenty-four were evaluated through histological examination while the remaining six were assessed using MRI. General characteristics of the selected studies are presented in Table 1. A total of 3,134 patients from the studies were analyzed. It was noteworthy that only two were randomized controlled studies [20], whereas others employed a cross-sectional design. To address the difference in follow-up duration, we categorized the data into three time periods, as follows: 3–6 months, 12–24 months, and 36–60 months, for further analyses.

Figure 1.

Flowchart of the study selection. Flowchart showing the process of study inclusion and exclusion in the systematic review. KMBASE, Korean Medical Database; KISS, Korean Studies Information Service System.

General characteristics of 30 studies

Impact of bariatric intervention on BMI and histology in MASH

A total of thirty studies showed a significant reduction in BMI except for one randomized controlled trial with small sample size [20]. BMI was reduced by 19% at a rate of 0.81 (95% CI, 0.71–0.92) at 3–6 months, by 28% at a rate of 0.72 (95% CI, 0.68–0.76) at 12–24 months, and by 27% at a rate of 0.73 (95% CI, 0.68–0.79) at 36–60 months after intervention (Fig. 2A). The overall NAS, before and after bariatric intervention, with the ratio of their mean values, was examined in seven studies (Supplementary Table 1). NAS was reduced by 60% at a rate of 0.40 (95% CI, 0.30–0.54) at 3–6 months, by 40% at a rate of 0.60 (95% CI, 0.40–0.89) at 12–24 months, and by 50% at a rate of 0.50 (95% CI, 0.35–0.70) at 24–60 months (Fig. 2B). In the study conducted by von Schönfels et al. [21], post-NAS revealed a value of 0, rendering the calculation of confidence interval unattainable. The results of the histology were evaluated according to Brunt’s criteria and Kleiner score [19]. Nineteen studies revealed that the proportion of patients with steatosis decreased by 44% at 3–6 months, 37% at 12–24 months, and 29% at 36–60 months (Fig. 2C); lobular inflammation by 33% at 3–6 months, 36% at 12–24 months, and 51% at 36–60 months (Fig. 2D); ballooning degeneration by 20% at 3–6 months, 38% at 12–24 months, and 18% at 36–60 months (Fig. 2E). Remarkably, the proportion of patients with stage 2 fibrosis or higher (≥F2), or with more advanced form of MASLD, was found to decrease by 18% at 12–24 months, and by 17% at 36–60 months after intervention, compared to that before the operation (Fig. 2F, Supplementary Table 2). Most of these analyses revealed the I2 statistics exceeding 75%, signifying substantial heterogeneity across the studies. Subsequent sensitivity analysis and meta-regression were conducted; however, the source of heterogeneity remained unclear (data not shown).

Figure 2.

Meta-analysis forest plot of BMI and histology. (A) BMI, (B) NAS by biopsy, (C) Steatosis, (D) Lobular inflammation, (E) Ballooning degeneration, and (F) Fibrosis (≥F2). (A) and (B): risk of means was reported. (C), (D), (E), and (F): proportion difference was reported. and indicate same cohort with different follow-up time frame. BMI, body mass index; NAS, nonalcoholic fatty liver disease activity score.

Impact of bariatric intervention intrahepatic fat measured by MRI-PDFF

Six studies showed significant reduction of intrahepatic fat in MRI-PDFF at six months after bariatric intervention (Table 2). Ratio of the means of pre-operative to post-operative MRI-PDFF was 0.28 (95% CI, 0.24–0.33), which implied that 72% of intrahepatic fat was reduced after intervention with 21% of BMI reduction (Fig. 3). We observed a borderline heterogeneity in BMI, but no heterogeneity was identified in steatosis measured by MRI-PDFF.

Ratio of means of MRI-PDFF meta-analysis of the efficacy of bariatric intervention in obese patients

Figure 3.

Meta-analysis forest plot of BMI and MRI-PDFF. (A) BMI, and (B) Steatosis by MRI-PDFF. and indicate same cohort with different follow-up time frame. BMI, body mass index; MRI, magnetic resonance imaging; PDFF, proton density fat fraction.

Mortality after bariatric surgery and MASH aggravation

Two studies reported mortality rate after the bariatric surgery, with pooled mortality rate of 13% (95% CI, 0.07–0.21). The other three studies reported cases in which MASLD worsened based on liver histologic examination after the surgery, with a pooled proportion of 6% (95% CI, 0.04–0.09) (Supplementary Table 3).

Quality of the selected studies

Out of a total of thirty studies, most studies showed low risk of bias, whereas a few showed moderate/high (Supplementary Figs. 1 and 2). To visually inspect the potential publication bias, we also created funnel plots for studies investigating populations with more than ten individuals where BMI was measured within 12–24 months. We found significant publication bias (Supplementary Fig. 3). To address this bias, we applied trim and fill method, confirming the correction of publication bias in the modified result. Notably, the adjusted effect size values remained consistent with the trend observed in the analysis using raw values. For populations with a follow-up period of 12–24 months, the GRADE assessment was used to rate the quality of evidence (Supplementary Table 4).

DISCUSSION

The current study aimed to comprehensively assess the impact of bariatric intervention on hepatic steatosis and MASH, with particular focus on presenting the association using a novel measure, MRI-PDFF, which, to the best of our knowledge, has not been reported till date. MASLD is one of the most common causes of chronic liver disease worldwide. While the complete pathophysiology remains unclear, insulin resistance is considered a pivotal factor of the disease development. This condition leads to an increase in free fatty acids released from adipose tissue, which subsequently move to the liver and are taken up by hepatocytes. Moreover, insulin resistance upregulates fatty acid transport proteins, impairs mitochondrial fatty acid oxidation, and alters the adipokine profile, all of which can accelerate hepatic fat accumulation and inflammation [22]. Hence, the primary treatment goal has been focused on improving insulin resistance by managing obesity, particularly central obesity, in MASLD. Lifestyle modification and, if indicated, medications targeting weight loss are valid options for initial management of the disease. Among the medical options, GLP-1 receptor agonist has shown superiority over other drugs in managing MASH. In case these approaches fail to achieve substantial weight loss, the consideration of bariatric intervention for obese patients would be justified.

However, whether the impact of weight loss extends to more advanced liver conditions, such as MASH or liver fibrosis, when inflammation in the liver progresses, has remained a long-standing controversy. This is probably due not only to the disease progressing to an irreversible stage but also to the liver’s inability to tolerate the lipotoxicity arising from the massive release of free fatty acids, mainly originating from visceral fat, following rapid weight loss, which is particularly evident in the early stage of bariatric surgery [23]. Nevertheless, several previous meta-analyses have found a favorable effect of the surgery on improving MASH [9-11]. Notably, Lee et al. [10] reported their meta-analysis, wherein histological worsening of MASLD after bariatric surgery was 12%. Our study showed, in line with the above studies, a pooled mortality rate of 13% within a pooled follow-up time of 30.8 months, and a pooled worsening MASH rate of 6%. It would be worth noting that the number of studies reporting post-surgery deaths was considerably limited. Thus, we emphasized that the potential risks associated with bariatric surgery should not be disregarded, especially in advanced liver disease.

We have presented robust evidence of the significant impact of bariatric intervention on MASH, which aligns with the findings from prior meta-analyses. Moreover, we assessed the risk of bariatric intervention, which was not routinely evaluated in prior studies, emphasizing that the potential risk should not be overlooked when considering intervention. Our approach involved not only considering the type of liver histology but also incorporating NAS, a comprehensive tool for assessing MASLD. This enabled us to evaluate the effect of bariatric intervention from multiple perspectives. Finally, we showed, for the first time, that MRI-PDFF is a reliable indicator for assessing MASLD for bariatric intervention, particularly in its early stages. While several imaging modalities have been proposed as alternatives to liver biopsy, due to its invasive nature, MRI-PDFF demonstrated excellent sensitivity and specificity in diagnosing relatively early-stage MASLD [15].

Our study has several limitations. First, we encountered considerable heterogeneity in most analyses, despite categorizing by follow-up period and other interventions. This result was consistent with the GRADE assessment in our post hoc analyses. This methodological limitation has been identified in previous studies as well, suggesting that differences in study design and/or population may have significantly impacted this high heterogeneity. Nonetheless, the consistent and substantial impact of bariatric intervention has been evident across various study methodologies, reducing doubts about the reliability of this study result. Second, despite our meta-analysis showing the reliability of MRI as an alternative to liver biopsy in bariatric intervention, it would be important to note that the applicability of MRI-PDFF in more advanced liver diseases, such as MASH or liver cirrhosis, still remains a subject of scrutiny. Its limitations in establishing consistent correlations of the severity of steatohepatitis with advanced liver diseases underscore the necessity for further research in this area. Third, our analysis did not include the individual biochemical measures. However, the assessment of liver function through laboratory findings was thoroughly analyzed in prior meta-analyses, prompting us to avoid redundancy. Finally, the absence of individual patient data restricted the extent of more comprehensive analyses.

In conclusion, this meta-analysis reaffirmed the efficacy of bariatric intervention in the improvement of MASH for patients with obesity and MASLD while also highlighting the robust reliability of MRI-PDFF in assessing hepatic steatosis after bariatric intervention. Our study further reported that the favorable impact of bariatric intervention on MASH patients with obesity, like significant liver fibrosis or cirrhosis, remains uncertain due to potential risks of exacerbating liver conditions.

Notes

Authors’ contribution

All authors substantially participated in the analysis, data interpretation and preparation of manuscript. JH and HH should be considered joint first author.

Conflicts of Interest

The authors have no conflicts to disclose.

Acknowledgements

This research was supported by the grants of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (HI22C1948), the National Research Foundation of Korea grant funded by the Korea government (2021R1A2C4001401), and the National Cancer Center, Korea (2210420).

Abbreviations

MRI

magnetic resonance imaging

PDFF

proton density fat fraction

MASLD

metabolic dysfunction-associated steatotic liver disease

MASH

metabolic dysfunction-associated steatohepatitis

NAS

nonalcoholic fatty liver disease activity score

SUPPLEMENTAL MATERIAL

Supplementary material is available at Clinical and Molecular Hepatology website (http://www.e-cmh.org).

Supplementary Table 1.

Ratio of means of NAS meta-analysis of bariatric intervention in obese patients

cmh-2023-0384-Supplementary-Table-1.pdf
Supplementary Table 2.

The result of histology between pre- and post-bariatric intervention

cmh-2023-0384-Supplementary-Table-2.pdf
Supplementary Table 3.

Mortality and worsening MASH after bariatric surgery

cmh-2023-0384-Supplementary-Table-3.pdf
Supplementary Table 4.

GRADE certainty assessment summary of findings table

cmh-2023-0384-Supplementary-Table-4.pdf
Supplementary Figure 1.

Risk of bias summary.

cmh-2023-0384-Supplementary-Fig-1.pdf
Supplementary Figure 2.

Risk of bias summary for review author’s judgment.

cmh-2023-0384-Supplementary-Fig-2.pdf
Supplementary Figure 3.

Funnel plots. BMI, body mass index.

cmh-2023-0384-Supplementary-Fig-3.pdf

References

1. Khan RS, Bril F, Cusi K, Newsome PN. Modulation of insulin resistance in nonalcoholic fatty liver disease. Hepatology 2019;70:711–724.
2. Lee KC, Wu PS, Lin HC. Pathogenesis and treatment of nonalcoholic steatohepatitis and its fibrosis. Clin Mol Hepatol 2023;29:77–98.
3. Song SJ, Wong VW. Implications of comorbidities in nonalcoholic fatty liver disease. Clin Mol Hepatol 2023;29:384–389.
4. Younossi ZM, Golabi P, de Avila L, Paik JM, Srishord M, Fukui N, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. J Hepatol 2019;71:793–801.
5. European Association for the Study of the Liver (EASL), ; European Association for the Study of Diabetes (EASD), ; European Association for the Study of Obesity (EASO). EASL-EASDEASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J Hepatol 2016;64:1388–1402.
6. Park MJ, Kim H, Kim MG, Kim K. Comparison of glucagon-like peptide-1 receptor agonists and thiazolidinediones on treating nonalcoholic fatty liver disease: A network meta-analysis. Clin Mol Hepatol 2023;29:693–704.
7. Eisenberg D, Shikora SA, Aarts E, Aminian A, Angrisani L, Cohen RV, et al. 2022 American Society for Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO): Indications for Metabolic and Bariatric Surgery. Surg Obes Relat Dis 2022;18:1345–1356.
8. Zhou H, Luo P, Li P, Wang G, Yi X, Fu Z, et al. Bariatric surgery improves nonalcoholic fatty liver disease: Systematic review and meta-analysis. Obes Surg 2022;32:1872–1883.
9. Fakhry TK, Mhaskar R, Schwitalla T, Muradova E, Gonzalvo JP, Murr MM. Bariatric surgery improves nonalcoholic fatty liver disease: a contemporary systematic review and meta-analysis. Surg Obes Relat Dis 2019;15:502–511.
10. Lee Y, Doumouras AG, Yu J, Brar K, Banfield L, Gmora S, et al. Complete resolution of nonalcoholic fatty liver disease after bariatric surgery: A systematic review and meta-analysis. Clin Gastroenterol Hepatol 2019;17:1040–1060.e11.
11. Mummadi RR, Kasturi KS, Chennareddygari S, Sood GK. Effect of bariatric surgery on nonalcoholic fatty liver disease: systematic review and meta-analysis. Clin Gastroenterol Hepatol 2008;6:1396–1402.
12. Bower G, Toma T, Harling L, Jiao LR, Efthimiou E, Darzi A, et al. Bariatric surgery and non-alcoholic fatty liver disease: A systematic review of liver biochemistry and histology. Obes Surg 2015;25:2280–2289.
13. Kral JG, Thung SN, Biron S, Hould FS, Lebel S, Marceau S, et al. Effects of surgical treatment of the metabolic syndrome on liver fibrosis and cirrhosis. Surgery 2004;135:48–58.
14. Taitano AA, Markow M, Finan JE, Wheeler DE, Gonzalvo JP, Murr MM. Bariatric surgery improves histological features of nonalcoholic fatty liver disease and liver fibrosis. J Gastrointest Surg 2015;19:429–436. discussion 436-437.
15. Gu J, Liu S, Du S, Zhang Q, Xiao J, Dong Q, et al. Diagnostic value of MRI-PDFF for hepatic steatosis in patients with non-alcoholic fatty liver disease: a meta-analysis. Eur Radiol 2019;29:3564–3573.
16. Nam H, Yoo JJ, Cho Y, Kang SH, Ahn SB, Lee HW, et al. Effect of exercise-based interventions in nonalcoholic fatty liver disease: A systematic review with meta-analysis. Dig Liver Dis 2023;55:1178–1186.
17. Han S, Choi M, Lee B, Lee HW, Kang SH, Cho Y, et al. Accuracy of noninvasive scoring systems in assessing liver fibrosis in patients with nonalcoholic fatty liver disease: A systematic review and meta-analysis. Gut Liver 2022;16:952–963.
18. McInnes MDF, Moher D, Thombs BD, McGrath TA, Bossuyt PM, Clifford T, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: The PRISMA-DTA Statement. JAMA 2018;319:388–396.
19. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005;41:1313–1321.
20. Lee YM, Low HC, Lim LG, Dan YY, Aung MO, Cheng CL, et al. Intragastric balloon significantly improves nonalcoholic fatty liver disease activity score in obese patients with nonalcoholic steatohepatitis: a pilot study. Gastrointest Endosc 2012;76:756–760.
21. von Schönfels W, Beckmann JH, Ahrens M, Hendricks A, Röcken C, Szymczak S, et al. Histologic improvement of NAFLD in patients with obesity after bariatric surgery based on standardized NAS (NAFLD activity score). Surg Obes Relat Dis 2018;14:1607–1616.
22. Watt MJ, Miotto PM, De Nardo W, Montgomery MK. The liver as an endocrine organ-linking NAFLD and insulin resistance. Endocr Rev 2019;40:1367–1393.
23. Verna EC, Berk PD. Role of fatty acids in the pathogenesis of obesity and fatty liver: impact of bariatric surgery. Semin Liver Dis 2008;28:407–426.
24. Aldoheyan T, Hassanain M, Al-Mulhim A, Al-Sabhan A, AlAmro S, Bamehriz F, et al. The effects of bariatric surgeries on nonalcoholic fatty liver disease. Surg Endosc 2017;31:1142–1147.
25. Barker KB, Palekar NA, Bowers SP, Goldberg JE, Pulcini JP, Harrison SA. Non-alcoholic steatohepatitis: effect of Roux-enY gastric bypass surgery. Am J Gastroenterol 2006;101:368–373.
26. Caiazzo R, Lassailly G, Leteurtre E, Baud G, Verkindt H, Raverdy V, et al. Roux-en-Y gastric bypass versus adjustable gastric banding to reduce nonalcoholic fatty liver disease: a 5-year controlled longitudinal study. Ann Surg 2014;260:893–898. discussion 898-899.
27. Chaim FDM, Pascoal LB, Chaim FHM, Palma BB, Damázio TA, da Costa LBE, et al. Histological grading evaluation of non-alcoholic fatty liver disease after bariatric surgery: a retrospective and longitudinal observational cohort study. Sci Rep 2020;10:8496.
28. Esquivel CM, Garcia M, Armando L, Ortiz G, Lascano FM, Foscarini JM. Laparoscopic sleeve gastrectomy resolves NAFLD: Another formal indication for bariatric surgery? Obes Surg 2018;28:4022–4033.
29. Fazel I, Pourshams A, Merat S, Hemayati R, Sotoudeh M, Malekzadeh R. Modified jejunoileal bypass surgery with biliary diversion for morbid obesity and changes in liver histology during follow-up. J Gastrointest Surg 2007;11:1033–1038.
30. Furuya CK Jr, de Oliveira CP, de Mello ES, Faintuch J, Raskovski A, Matsuda M, et al. Effects of bariatric surgery on nonalcoholic fatty liver disease: preliminary findings after 2 years. J Gastroenterol Hepatol 2007;22:510–514.
31. Jaskiewicz K, Raczynska S, Rzepko R, Sledziński Z. Nonalcoholic fatty liver disease treated by gastroplasty. Dig Dis Sci 2006;51:21–26.
32. Lassailly G, Caiazzo R, Ntandja-Wandji LC, Gnemmi V, Baud G, Verkindt H, et al. Bariatric surgery provides long-term resolution of nonalcoholic steatohepatitis and regression of fibrosis. Gastroenterology 2020;159:1290–1301.e5.
33. Liu X, Lazenby AJ, Clements RH, Jhala N, Abrams GA. Resolution of nonalcoholic steatohepatits after gastric bypass surgery. Obes Surg 2007;17:486–492.
34. Mathurin P, Hollebecque A, Arnalsteen L, Buob D, Leteurtre E, Caiazzo R, et al. Prospective study of the long-term effects of bariatric surgery on liver injury in patients without advanced disease. Gastroenterology 2009;137:532–540.
35. Mattar SG, Velcu LM, Rabinovitz M, Demetris AJ, Krasinskas AM, Barinas-Mitchell E, et al. Surgically-induced weight loss significantly improves nonalcoholic fatty liver disease and the metabolic syndrome. Ann Surg 2005;242:610–617. discussion 618-620.
36. Meinhardt NG, Souto KE, Ulbrich-Kulczynski JM, Stein AT. Hepatic outcomes after jejunoileal bypass: is there a publication bias? Obes Surg 2006;16:1171–1178.
37. Moretto M, Kupski C, da Silva VD, Padoin AV, Mottin CC. Effect of bariatric surgery on liver fibrosis. Obes Surg 2012;22:1044–1049.
38. Mottin CC, Moretto M, Padoin AV, Kupski C, Swarowsky AM, Glock L, et al. Histological behavior of hepatic steatosis in morbidly obese patients after weight loss induced by bariatric surgery. Obes Surg 2005;15:788–793.
39. Parker BM, Wu J, You J, Barnes DS, Yerian L, Kirwan JP, et al. Reversal of fibrosis in patients with nonalcoholic steatohepatosis after gastric bypass surgery. BMC Obes 2017;4:32.
40. Russo MF, Lembo E, Mari A, Angelini G, Verrastro O, Nanni G, et al. Insulin resistance is central to long-term reversal of histologic nonalcoholic steatohepatitis after metabolic surgery. J Clin Endocrinol Metab 2021;106:750–761.
41. Salman MA, Salman AA, Abdelsalam A, Atallah M, Shaaban HE, El-Mikkawy A, et al. Laparoscopic sleeve gastrectomy on the horizon as a promising treatment modality for NAFLD. Obes Surg 2020;30:87–95.
42. Salman MA, Salman AA, Omar HSE, Abdelsalam A, Mostafa MS, Tourky M, et al. Long-term effects of one-anastomosis gastric bypass on liver histopathology in NAFLD cases: a prospective study. Surg Endosc 2021;35:1889–1894.
43. Verrastro O, Panunzi S, Castagneto-Gissey L, De Gaetano A, Lembo E, Capristo E, et al. Bariatric-metabolic surgery versus lifestyle intervention plus best medical care in non-alcoholic steatohepatitis (BRAVES): a multicentre, open-label, randomised trial. Lancet 2023;401:1786–1797.
44. Folini L, Veronelli A, Benetti A, Pozzato C, Cappelletti M, Masci E, et al. Liver steatosis (LS) evaluated through chemical-shift magnetic resonance imaging liver enzymes in morbid obesity; effect of weight loss obtained with intragastric balloon gastric banding. Acta Diabetol 2014;51:361–368.
45. Hedderich DM, Hasenberg T, Haneder S, Schoenberg SO, Kücükoglu Ö, Canbay A, et al. Effects of bariatric surgery on non-alcoholic fatty liver disease: Magnetic resonance imaging is an effective, non-invasive method to evaluate changes in the liver fat fraction. Obes Surg 2017;27:1755–1762.
46. Luo RB, Suzuki T, Hooker JC, Covarrubias Y, Schlein A, Liu S, et al. How bariatric surgery affects liver volume and fat density in NAFLD patients. Surg Endosc 2018;32:1675–1682.
47. Mamidipalli A, Fowler KJ, Hamilton G, Wolfson T, Covarrubias Y, Tran C, et al. Prospective comparison of longitudinal change in hepatic proton density fat fraction (PDFF) estimated by magnitude-based MRI (MRI-M) and complex-based MRI (MRI-C). Eur Radiol 2020;30:5120–5129.
48. Pooler BD, Wiens CN, McMillan A, Artz NS, Schlein A, Covarrubias Y, et al. Monitoring fatty liver disease with MRI following bariatric surgery: A prospective, dual-center study. Radiology 2019;290:682–690.
49. Tan HC, Shumbayawonda E, Beyer C, Cheng LT, Low A, Lim CH, et al. Multiparametric magnetic resonance imaging and magnetic resonance elastography to evaluate the early effects of bariatric surgery on nonalcoholic fatty liver disease. Int J Biomed Imaging 2023;2023:4228321.

Article information Continued

Notes

Study Highlights

• This study assessed the changes in MRI-determined hepatic proton density fat fraction (MRI-PDFF) and NAS after bariatric intervention in patients with obesity and MASLD. We found that bariatric intervention significantly reduces BMI, intrahepatic fat, as well as NAS. Overall, our study reported that bariatric intervention could significantly improve MRI-PDFF and the histologic features of MASH in patients with obesity, and hence, could be a possible alternative treatment option for patients with MASLD who otherwise are resistant to lifestyle modification and/or medical treatment.

Figure 1.

Flowchart of the study selection. Flowchart showing the process of study inclusion and exclusion in the systematic review. KMBASE, Korean Medical Database; KISS, Korean Studies Information Service System.

Figure 2.

Meta-analysis forest plot of BMI and histology. (A) BMI, (B) NAS by biopsy, (C) Steatosis, (D) Lobular inflammation, (E) Ballooning degeneration, and (F) Fibrosis (≥F2). (A) and (B): risk of means was reported. (C), (D), (E), and (F): proportion difference was reported. and indicate same cohort with different follow-up time frame. BMI, body mass index; NAS, nonalcoholic fatty liver disease activity score.

Figure 3.

Meta-analysis forest plot of BMI and MRI-PDFF. (A) BMI, and (B) Steatosis by MRI-PDFF. and indicate same cohort with different follow-up time frame. BMI, body mass index; MRI, magnetic resonance imaging; PDFF, proton density fat fraction.

Table 1.

General characteristics of 30 studies

Author (year) Study design Method No. of samples Intervention Mean age (years) Follow-up duration Pre-BMI Post-BMI
Aldoheyan et al. (2017) [24] Prospective cohort Histology 27 Bariatric surgery 35±8 3 months 44.6±7.8 34.2±6.3
Barker et al. (2006) [25] Prospective cohort Histology 19 Roux-en-Y gastric bypass (RYGBP) 48.6 (35–58) 21.4 months (13.3–31.7) 46.8±4.4 28.8±5.2
Caiazzo et al. (2014a) [26], Prospective cohort Histology 681 RYGBP 41.1±11.1 1 year 49.8±8.2 36.0±6.9
Caiazzo et al. (2014b) [26], Prospective cohort Histology 555 Adjustable gastric banding (AGB) 40.3±11.4 1 year 46.8±6.5 39.9±6.7
Chaim et al. (2020) [27] Prospective cohort Histology 895 Bariatric surgery 39.4±10.2 21±22 months 35.9±2.8 25.7±3.8
Esquivel et al. (2018) [28] Prospective cohort Histology 63 Sleeve gastrectomy (SG) 40±10 1 year 44.9±5.6 30.5±4.2
Fazel et al. (2007) [29] Prospective cohort Histology 43 Modified Jejunoileal bypass surgery 35±10 60 months 46±7 32±6
Furuya et al. (2007) [30] Prospective cohort Histology 18 RYGBP 46.6±7.3 2 years 51.7±7.4 31±2
Jaskiewicz et al. (2006) [31] Prospective cohort Histology 87 Bariatric surgery 40.7±10.0 41 months 46.7±8.8 N/A
Kral et al. (2004) [13] Prospective cohort Histology 689 Biliopancreatic diversion 36.9±9 41±25 months 47±8.4 31±7.9
Lassailly et al. (2020) [32] Prospective cohort Histology 180 Bariatric surgery 46.7±10.6 5 year 48.1±7.9 36.1±7.8
Lee et al. (2012) [20] Randomized controlled trial Histology 8 Intragastric balloon 43±19.8 6 months 30.3±4.2 28.8±3.01
Liu et al. (2007) [33] Retrospective cohort Histology 39 Laparoscopic RYGBP 41.4±9 18 (6-41) months 47.7±6.2 29.5±5.6
Mathurin et al. (2009) [34] Prospective cohort Histology 381 Band, bypass, RYGBP 41.5±9.6 1 year, 5 years 50±7.8 39±8.2 (1 year), 37.7±8.4 (5 years)
Mattar et al. (2005) [35] Retrospective cohort Histology 70 Laparoscopic RYGBP, Laparoscopic AGB, LSG 49±9 15±9 months 56±11 39±10
Meinhardt et al. (2006) [36] Prospective cohort Histology 50 End-to-side JIB 37.9±7.6 67.0±42.8 months 52.8±7.5 35.7±7.5
Moretto et al. (2012) [37] Retrospective cohort Histology 78 Gastric bypass 39.5±11.4 1 year 45.4±8.1 29.7±3.9 & 29±6.5 (two groups)
Mottin et al. (2005) [38] Prospective cohort Histology 186 RYGBP 35.6±1.1 1 year 46.7±0.88 N/A
Parker et al. (2017) [39] Prospective cohort Histology 106 RYGBP 46±11 N/A 48±8 N/A
Russo et al. (2021) [40] Prospective cohort Histology 37 Biliopancreatic diversion 42±9 5 years 49.3±5.9 32.8±6.4
Salman et al. (2020) [41] Prospective cohort Histology 94 LSG 41.4±7.6 1 year 44.54±5.45 34.23±2.66
Salman et al. (2021) [42] Prospective cohort Histology 67 Gastric bypass 44.4±5.7 15 months 44.2±4.3 34.4±2.7
Taitano et al. (2015) [14] Prospective cohort Histology 160 Laparoscopic AGB or RYGBP 47±12 31±26 months 52±10 33±8
Verrasto et al. (2023a) [43], Randomized controlled trial Histology 77 RYGBP 46.4±8.5 1 year 43.39±4.14 29.70±4.26
Verrasto et al. (2023b) [43], Randomized controlled trial Histology 79 SG 46.8±8.8 1 year 40.76±3.74 30.82±4.08
von Schönfels et al. (2018) [21] Retrospective cohort Histology 257 SG or RYGBP 42±15 6 months 49.9±11.3 37±9
Folini et al. (2014) [44] Prospective cohort MR PDFF 18 Intragastric balloon or gastric banding 43.6±12.2 6 months 42.8±7.1 38.2±6.19
Hedderich et al. (2017) [45] Prospective cohort MR PDFF 19 RYGBP + LSG 41.4±12.5 6 months 44.1±5.2 33.8±5.6
Luo et al. (2018) [46] Prospective cohort MR PDFF 124 LSG, LRYGBP 50.9±10.8 6 months 45.3±5.9 34.4±5.1
Mamidipalli et al. (2020) [47] Prospective cohort MR PDFF 54 RYGBP or LSG 52±12 6 months 42.3±5.0 34.3±4.7
Pooler et al. (2019) [48] Retrospective cohort MR PDFF 50 Gastric bypass, sleeve, band, or plication 51±11.2 6 months 44.9±6.5 34.5±5.4
Tan et al. (2023) [49] Prospective cohort MR PDFF 9 LSG 45.1±9.0 6 months 39.7±5.3 32.4±4.8

BMI, body mass index; RYGB, Roux-en-Y gastric bypass; LSG, laparoscopic sleeve gastrectomy; SG, sleeve gastrectomy; AGB, adjustable gastric banding.

indicates different patient cohort according to surgery type.

Table 2.

Ratio of means of MRI-PDFF meta-analysis of the efficacy of bariatric intervention in obese patients

Author (year) No. of samples Ratio of mean (95% CI)
BMI Steatosis by MRI
After 3–6 months
Folini et al. (2014) [44] 18 0.87 (0.79–0.97) 0.46 (0.23–0.89)
Hedderich et al. (2017) [45] 19 0.77 (0.70–0.84) 0.31 (0.19–0.53)
Luo et al. (2018) [46] 124 0.76 (0.73–0.79) 0.26 (0.23–0.31)
Mamidipalli et al. (2020) [47] 54 0.81 (0.77–0.85) 0.32 (0.25–0.40)
Pooler et al. (2019) [48] 50 0.77 (0.72–0.82) 0.27 (0.21–0.34)
Tan et al. (2023) [49] 9 0.82 (0.72–0.93) 0.33
Overall 0.79 (0.75–0.83) 0.28 (0.24–0.33)
Heterogeneity - I2 50.9% (0.0–80.5%) 0% (0–79.2%)
P-value 0.070 0.417

MRI, magnetic resonance imaging; PDFF, proton density fat fraction; BMI, body mass index; CI, confidence interval.