Abstract
Background and Aims:
Metabolic dysfunction-associated steatohepatitis (MASH) is a leading cause of liver disease. Dynamic changes in magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF) are associated with MASH resolution. We aimed to determine the relative efficacy of therapeutic agents for reducing hepatic fat, assessed by magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF).
Approach and results:
In this systematic review and network meta-analysis, we searched MEDLINE and Embase from inception until Dec 26, 2023, for published randomized-controlled trials (RCTs) comparing pharmacological interventions in patients with MASH that assessed changes in MRI-PDFF. The primary outcome was the absolute change in MRI-PDFF. The secondary outcome was a ≥30% decline in MRI-PDFF. A surface under-the-curve cumulative ranking probabilities (SUCRA) analysis was performed. Of 1550 records, a total of 39 RCTs (3311 participants) met the inclusion criteria. For MRI-PDFF decline at 24 weeks, aldafermin (SUCRA: 83.65), pegozafermin (SUCRA: 83.46), and pioglitazone (SUCRA: 71.67) were ranked the most effective interventions. At 24-weeks, efinopegdutide (SUCRA: 67.02), semaglutide + firsocostat (SUCRA: 62.43), and pegbelfermin (SUCRA: 61.68) were ranked the most effective interventions for achieving a ≥30% decline in MRI-PDFF.
Conclusions:
This study provides an updated, relative rank-order efficacy of therapies for MASH in reducing hepatic fat. These data may help inform the design and sample size calculation of future clinical trials and assist selection of combination therapy.
Keywords: Metabolic dysfunction-associated steatohepatitis, Pharmacologic therapies, Network meta-analysis
Graphical Abstract
INTRODUCTION
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of liver-related morbidity and mortality 1–3. MASLD is the fastest-growing cause of mortality from cirrhosis and liver cancer. Metabolic dysfunction-associated steatohepatitis (MASH) is the inflammatory form of MASLD that progresses to advanced fibrosis, hepatic decompensation, and hepatocellular carcinoma 4–7. Liver biopsy is the gold standard for determining treatment response in MASH but is limited by invasiveness, potential complications, and sampling variability 8. Recent studies have determined that magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF) provides an accurate, noninvasive, quantitative, and precise estimation of liver fat content 9–13.
A reduction, and a 30% relative decline in MRI-PDFF, are associated with the resolution of MASH 14–17. Multiple early-phase randomized trials in patients with MASH have utilized MRI-PDFF as the primary endpoint, and emerging data suggest that combination therapy may be associated with even greater reductions in MRI-PDFF compared to monotherapy 18. However, the relative efficacy of these pharmacological agents for reducing hepatic steatosis has not been systematically assessed. Therefore, we performed a systematic review and network meta-analysis to estimate the comparative impact and the relative rank order of MASH therapeutic agents in reducing hepatic steatosis, assessed by MRI-PDFF.
METHODS
Search strategy
This network meta-analysis was conducted with reference to the Preferred Reporting Items for Systematic Review and Meta-Analyses extended statement for network analysis19,20. A comprehensive search was conducted on Medline (Ovid) and Embase with assistance from a medical librarian for MASH randomized controlled trials (RCTs) from inception to 26th December 2023. The full search strategy is enclosed in supplementary material 1. All references were imported into Endnote 20 for duplicate removal. The references of the included articles were also annually screened to maintain a comprehensive search.
Eligibility and selection criteria
Two authors (BK, JX) independently conducted the screening of abstracts and evaluation of full text for inclusion based on the eligibility criteria. Any discrepancies were resolved through consensus and consultation with a senior author. The inclusion criteria for this study included (i) randomized control trials (RCTs) (Phase II, III or IV); (ii) enrolled patients with biopsy-proven or MRI confirmed MASH; (iii) compared one or more of established or potentially beneficial therapies for MASH based on American Association for the Study of Liver Diseases (AASLD) guidelines to each other or to placebo; (iv) had a follow-up duration of at least 6 months; and (v) reported the primary outcome including absolute change in MRI-PDFF and/or the secondary outcome of ≥30% decline in MRI-PDFF at week 12, 24 and 48 weeks. Trials examining a combination of drugs within the same treatment arm were included. Observational studies, systematic reviews, meta-analyses, case series, correspondence, and editorials are excluded. Trials enrolling less than 40 patients, evaluating lifestyle interventions, or futile therapy based on the AASLD guidelines (e.g. metformin, omega-3 fatty acids, statins, etc.) were excluded. Pediatric studies were excluded as the focus of the current study is primarily on the adult population. Transformation of values was carried out using pre-existing formulae, in which mean and standard deviation was estimated from median and range using the widely adopted formula by Wan et al21.
Outcomes
The primary outcome was the absolute change in MRI-PDFF. The secondary outcome was a ≥30% decline in MRI-PDFF.
Statistical analysis
Statistical analysis was conducted in RStudio (Version 4.3). The analysis was conducted in a Bayesian network model from a generalized linear model using BUGSnet and JAGS software. Bayes iterations parameters were set to 1000 burn-ins, 1000 adaptations, and 10000 iterations for Markov Chain Monte Carlo (MCMC) algorithm22. Model fit was examined from a visual inspection of the trace and density plot. Both models of fixed and random effects were conducted, and the evaluation of model fitting was based on the Deviance Information Criterion (DIC). DIC and unrelated mean effects (UME) model was used to examine consistency which assesses statistical agreement between indirect and direct evidence required for validation of the transitivity assumption22. A surface under-the-curve cumulative ranking probabilities (SUCRA) analysis was performed for the endpoint of treatment outcomes. The SUCRA analysis ranks each treatment included from 0 to 100% with a higher number closer to 100% indicating a greater probability of successful event. The unit of measure was risk ratio (RR) for dichotomous outcomes and mean difference (MD) for continuous events with a log-link and identity-link respectively. Outputs of the meta-analysis were presented in RR/MD with the corresponding credible intervals (Crl).
Risk of bias assessment
The risk of bias assessment was done using the Cochrane Risk of Bias 2.023. In brief, the included articles were assessed on the randomization process, deviation from intended interventions, incomplete outcome data, measurement of the outcome, selective outcome reporting, and other potential sources of bias. Any discrepancies that arise were resolved by consensus or in discussion with a third author. Potential publication bias was assessed through visual inspection for asymmetry of the funnel plot.
RESULTS
A total of 1550 references were identified through electronic searches of the databases, and 39 RCTs met inclusion criteria (Supplementary material 2). Supplementary material 3 summarizes the papers included in the analysis. In total, 3311 participants and 41 interventions were evaluated. The mean age of patients was 53.4 years old in the control group and 53.7 years old in the intervention group. A total of 44.6% (n = 532) and 43.6% (n = 924) of patients in the control and intervention groups were male, respectively. The majority of the included studies have low concerns of bias (Supplementary Table 4). Publication bias was not evaluable as only a single study was included for each drug comparison.
Primary outcome: absolute change in MRI-PDFF at 24 weeks
A total of 784, 1154, and 609 participants were included in the 12-week, 24-week, and 48-week analyses, respectively. Supplementary Table 5 summarizes the baseline characteristics of studies included in these analyses. The treatment effect of each pharmacologic therapy in absolute change of MRI-PDFF is presented in Figure 1.
Figure 1:
Treatment effect for absolute change in magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF)at 12 weeks, 24 weeks, and 48 weeks
At 24 weeks, the absolute change in MRI-PDFF included 14 treatments (aldafermin, colesevelam, ezetimibe, pegozafermin, pioglitazone, semaglutide, exenatide, dulaglutide, insulin glargine, pemafibrate, dapagliflozin, efinopegdutide, tofogliflozin and sitagliptin). There was the greatest significant decrease in MRI-PDFF for patients receiving aldafermin (log mean difference: −6.64, Crl: −8.64 to −4.64), pegozafermin (log mean difference: −6.60, Crl:−8.53 to −4.65), pioglitazone (log mean difference: −4.3, Crl: −5.88 to −2.71), compared to placebo. However, patients on colesevelam (log mean difference: 5.50, Crl: 3.60 to 7.40), and sitagliptin (log mean difference: 5.51, CrI 1.26 to 9.72) had a statistically higher MRI-PDFF compared to placebo. The results of the network meta-analysis are summarised in Figure 2. Based on the SUCRA score, aldafermin (SUCRA: 83.65) and pegozafermin had the highest likelihood of being the best treatments (SUCRA: 83.46), while colesevelam had the lowest score (SUCRA: 17.89) (Table 1).
Figure 2:
Comparison of treatments for absolute change in magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF)at 24 weeks
Table 1:
SUCRA analysis results of MASH treatment for absolute change in MRI-PDFF
| Treatment | SUCRA |
|---|---|
| 12 weeks | |
| Efruxifermin | 97.89 |
| Aldafermin | 90.93 |
| Pegozafermin | 87.68 |
| EDP-305 | 63.84 |
| Resmetirom | 62.03 |
| IONIS-DGAT2Rx | 60.32 |
| Licogliflozin | 59.86 |
| Vonafexor | 45.58 |
| Lubiprostone | 38.00 |
| PXL770 | 37.58 |
| Dapagliflozin | 30.47 |
| Namodenoson | 14.42 |
| Placebo | 10.48 |
| Fenofibrate | 0.92 |
| 24 weeks | |
| Aldafermin | 83.65 |
| Pegozafermin | 83.46 |
| Pioglitazone | 71.67 |
| Dulaglutide | 65.88 |
| Exenatide | 58.19 |
| Insulin Glargine | 48.35 |
| Ezetimibe | 48.19 |
| Pemafibrate | 47.10 |
| Dapagliflozin | 47.09 |
| Efinopegdutide | 46.95 |
| Tofogliflozin | 44.42 |
| Semaglutide | 35.94 |
| Placebo | 33.18 |
| Sitagliptin | 18.04 |
| Colesevelam | 17.89 |
| 48 weeks | |
| Cilofexor + Firsocostat | 82.65 |
| Firsocostat + Selonsertib | 77.57 |
| Cilofexor | 64.85 |
| Firsocostat | 63.79 |
| Semaglutide | 48.84 |
| Cilofexor + Selonsertib | 46.53 |
| Placebo | 14.85 |
| Pemafibrate | 0.93 |
Legend: MRI-PDFF- Magnetic Resonance Imaging Proton Density Fat Fraction; MASH – Metabolic Associated Steatohepatitis; SUCRA – Surface Under the Cumulative Ranking Curve
At 12-weeks, 14 interventions (aldafermin, EDP-305, licogfilozin, PXL770, dapagliflozin, fenofibrate, namodenoson, vonafexor, IONIS-DGAT2Rx, pegozafermin, efruxifermin, lubiprostone,and resmetirom) were compared to placebo. The network analysis showed the most substantial decrease in MRI-PDFF for patients receiving efruxifermin (mean difference: −14.40, Crl: −16.64 to −12.15), aldafermin (mean difference: −12.39, Crl: −15.54 to −9.22), pegozafermin (mean difference: −11.09, Crl: −16.09 to −6.12), and EDP-305 (mean difference: −4.70, Crl: −7.42 to −1.99) (Supplementary Figure 1). Based on the SUCRA score, efruxifermin had the highest likelihood of being the best treatment (SUCRA: 97.89), while fenofibrate had the lowest SUCRA score (SUCRA: 0.92) (Table 1).
Analysis at 48 weeks included 7 interventions (cilofexor, firsocostat, cilofexor + firsocostat, cilofexor + selonsertib, firsocostat + selonsertib, semaglutide, and pemafibrates). Analysis showed statistically significant difference in an intervention of cilofexor + firsocostat (mean difference: −4.95, CrI: −8.10 to −1.79), firsocostat + selonsertib (mean difference: −4.65, CrI: −7.81 to −1.50), firsocostat monotherapy (mean difference: −3.91, CrI: −7.54 to −0.26), and semaglutide (mean difference: - 2.93, CrI: −4.50 to −1.38) compared to placebo (Supplementary Figure 2). Based on SUCRA score, cilofexor + firsocostat had the highest probability of being the best treatment (SUCRA: 82.65), while pemafibrates had the lowest score (SUCRA: 0.93) (Table 1).
Secondary outcome: ≥30% decline in MRI-PDFF at 24 weeks
20 RCTs were included in this analysis. 17 RCTs were compared to placebo, one study compared Selonsertib with or without Simtuzumab to Simtuzumab monotherapy, one study compared efinopegdutide to semaglutide, one study compared semaglutide to a combination therapy with cilofexor and/or firsocostat24, and one study compared a monotherapy of tropifexor or cenicriviroc to a combination therapy of both drugs25. In total, 649 patients were included in the analysis at 12 weeks, 767 patients were analyzed at 24 weeks, and 452 patients at the 48-week analysis. The baseline characteristics are summarised in Supplementary Table 6. The treatment effect of each pharmacologic therapy in absolute change of MRI-PDFF is presented in Figure 3.
Figure 3:
Treatment effect for ≥30% decline in magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF)at 12 weeks, 24 weeks, and 48 weeks
24-week analysis compared 5 treatments (pegbelfermin, JKB-121, pemafibrate, efruxifermin, and aldafermin) to placebo, selonsertib with or without simtuzumab was compared to simtuzumab monotherapy, semaglutide with or without cenicriviroc and firsocostat, while cenicriviroc, tropifexor and tropifexor + cenicriviroc, efinopegdutide and semaglutide were compared to each other. Network analysis compared to placebo showed a statistically significantly lower incidence of a ≥30% decline in MRI-PDFF in aldafermin (log RR: 0.92, Crl: 0.57 to 1.35), efruxifermin (log RR: 1.35, CrI: 0.85 to 2.00) and pegbelfermin (log RR: 1.57, Crl: 0.52 to 3.08) (Figure 4). Compared to simtuzumab monotherapy selonsertib +/− simtuzumab did not have a significantly higher incidence (log RR: 1.37, Crl −0.30 to 4.66). Amongst the 3 treatments (tropifexor, cenicriviroc, and tropifexor + cenicriviroc), the dual therapy of tropifexor + cenicriviroc had a significantly higher incidence of a ≥30% decline in MRI-PDFF when compared to both tropifexor (RR: 1.16, Crl: 0.17 to 2.61) and cenicriviroc (RR: 1.42, Crl: 0.40 to 2.88). Semaglutide monotherapy did not show any significant difference in ≥30% decline in MRI-PDFF when compared to combination therapy with cilofexor and/or firsocostat. SUCRA score analysis identified efinopegdutide as the most likely treatment (SUCRA: 67.02), followed by semaglutide + firsocostat (SUCRA: 62.43), and pegbelfermin (SUCRA: 61.68) in causing a ≥30% decline in MRI-PDFF (Table 2).
Figure 4:
Comparison of treatments for ≥30% decline in magnetic resonance imaging (MRI) proton-density-fat fraction (PDFF) at 24 weeks
Table 2:
SUCRA analysis results of MASH treatment for ≥30% decline in MRI-PDFF
| Treatment | SUCRA |
|---|---|
| 12 weeks | |
| Pegozafermin | 95.23 |
| Aldafermin | 86.34 |
| Efruxifermin | 76.79 |
| Denifanstat | 60.85 |
| PXL770 | 54.13 |
| Resmetirom | 53.58 |
| Vonafexor | 47.34 |
| IONIS-DGAT2Rx | 42.07 |
| Licogliflozin | 41.71 |
| EDP-305 | 27.80 |
| Placebo | 8.15 |
| TERN-101 | 6.00 |
| 24 weeks | |
| Efinopegdutide | 67.02 |
| Semaglutide + Firsocostat | 62.43 |
| Pegbelfermin | 61.68 |
| Semaglutide + Cilofexor | 60.86 |
| Efruxifermin | 59.87 |
| Selonsertib +/− Simtuzumab | 55.31 |
| Semaglutide | 52.35 |
| Aldafermin | 52.07 |
| Semaglutide + Cilofexor + Firsocostat | 51.37 |
| Tropifexor + Cenicriviroc | 49.57 |
| Simtuzumab | 46.44 |
| Pemafibrate | 38.81 |
| Tropifexor | 38.09 |
| Placebo | 37.99 |
| Cenicriviroc | 35.84 |
| JKB-121 | 30.34 |
| 48 weeks | |
| Semaglutide | 83.18 |
| Tropifexor | 82.87 |
| Tropifexor + Cenicriviroc | 58.00 |
| Pegbelfermin | 52.68 |
| Cenicriviroc | 28.30 |
| Placebo | 26.28 |
| Pemafibrate | 18.70 |
Legend: MRI-PDFF- Magnetic Resonance Imaging Proton Density Fat Fraction; MASH – Metabolic Associated Steatohepatitis; SUCRA – Surface Under the Cumulative Ranking Curve
At 12-week analysis comparing 11 interventions (PXL770, denifanstat, TERN-101, vonafexor, aldafermin, efruxifermin, resmetirom, licogliflozin, pegozafermin, IONIS-DGAT2Rx, and EDP-305) to placebo, network analysis identified significantly higher incidence of a ≥30% decline in MRI-PDFF in pegozafermin (log RR: 3.04, Crl: 1.39 to 6.09), aldafermin (log RR: 2.16, CrI: 1.23 to 3.66), efruxifermin (log RR: 1.77, Crl: 0.83 to 3.21), denifanstat (log RR: 1.28, Crl: 0.59 to 2.22), resmetirom (log RR: 1.11, Crl: 0.53 to 1.88), vonafexor (log RR: 0.98, CrI: 0.09 to 2.06) and licogliflozin (log RR: 0.84, CrI: 0.21 to 1.72) (Supplementary Figure 3). SUCRA score analysis identified pegozafermin as having the highest likelihood of being the best treatment option (SUCRA score: 95.23), followed by aldafermin (SUCRA: 86.34), and efruxifermin (SUCRA: 76.79) (Table 2).
Analysis at 48-week compared 5 interventions to placebo (pegbelfermin, semaglutide, pemafibrate, peglbelfermin, and tropifexor), while cenicriviroc, tropifexor, and tropifexor + cenicriviroc were compared to each other. In total, 452 patients were included in the analysis. Network analysis showed a significant difference between semaglutide (RR: 2.39, CrI: 1.48 to 4.39) and tropifexor (RR: 2.32, CrI: 1.44 to 4.07) compared to placebo, while cenicriviroc and tropifexor showed no significant difference in causing a ≥30% decline in MRI-PDFF compared to tropifexor + cenicriviroc (Supplementary Figure 4). SUCRA analysis revealed semaglutide as being the most likely beneficial treatment (SUCRA: 83.18), followed by tropifexor (SUCRA: 82.87), and tropifexor + cenicriviroc (SUCRA: 58.0) (Table 2).
DISCUSSION
Main findings
In this network meta-analysis of 39 RCTs, we determined the comparative efficacy of various pharmacologic therapies in reducing hepatic steatosis among participants with biopsy-proven MASH. Aldafermin, pegozafermin, and pioglitazone were ranked the most effective therapies for reducing hepatic steatosis when assessed by a decline in MRI-PDFF over 24 weeks. At 24-weeks, efinopegdutide, semaglutide + firsocostat , and pegbelfermin were ranked the most effective interventions for achieving a ≥30% decline in MRI-PDFF. Among studies with available data for change in MRI-PDFF at week 12, efruxifermin, aldafermin, and pegozafermin were ranked the most efficacious therapies. In an analysis for the likelihood of achieving ≥30% decline in MRI-PDFF at 12 weeks, pharmacologic therapies involving pegozafermin appeared to be the most efficacious, followed by aldafermin, and efruxifermin.
In context with current literature
A previous meta-analysis provided data on the comparative efficacy of therapies for biopsy-confirmed MASH resolution26. A decline in MRI-PDFF has been shown in multiple studies to be associated with MASH resolution and histologic response 15–17. MRI-PDFF provides reliable non-invasive quantification of hepatic fat throughout the liver and allows for the identification of geographic steatosis, which may be more accurate than liver biopsy which takes a small sample of tissue; this has also been validated across different histological steatosis grades27. The current study builds on these data by providing the relative rank-order efficacy of therapies for reducing hepatic fat. Several landmark studies which did not meet our inclusion criteria also highlighted the therapeutic potential of these drugs for MASH resolution and improving liver fibrosis. The MAESTRO-NASH trial was a landmark study that led to the Food and Drug Agency (FDA) approval of resmetirom in treating MASH28. Resmetirom significantly reduced hepatic fat compared to placebo at both 16 and 52 weeks, leading to FDA approval and a possible turning point in the field. Emerging therapies have also shown promising preliminary results. The SURPASS-3 MRI trial concluded with tirzepatide showing significantly reduced in hepatic fat content amongst patients with NASH and type 2 diabetes compared to insulin degludec (−8.09% versus −3.38%, p < 0.0001)29. These studies highlight the still available potential of pharmacological treatments in MASH for the future.
Limitations
This study is not without limitations. There were limited studies that directly compared one therapy to another. The nature of our study design would also only generate indirect retrospective assumptions about the therapeutic effect of the evaluated drugs. However, patients with MASH are often a diverse population with varying comorbidities and inter-patient variability30–32. As such, a prospective head-to-head study directly comparing pharmacological therapies would be an ideal follow-up to support the findings in this paper. Some of the included RCTs had limited sample sizes, hence more data may be needed to validate the relative efficacy of the therapeutic agents. Many of the RCTs were performed in the United States and may require validation in other regions. Several therapies, such as tirzepatide and saroglitazar did not provide data for MRI-PDFF changes at week 12, 24, and 48 and hence were not included based on our pre-specified inclusion criteria33,34. Data for absolute change in MRI-PDFF for finopegdutide, semaglutide + firsocostat were provided in less mean squares, which could not be transformed into absolute values, hence only data for achieving 30% PDFF decline were provided for these therapies. Additionally, although MRI-PDFF is a reliable predictor of treatment response13,35–37, changes in hepatic fat based on MRI-PDFF do not always correlate with the success of the drug in gaining FDA approval or in clinical practice14,38. The use of retrospective data to make prospective assumptions may be challenging for a multi-dimensional disease such as MASH.
Implications for future research and clinical practice
These data may help inform the design of future clinical trials, especially when selecting potential agents for combination therapy with antifibrotic agents, as well as for sample size calculation. These data provide further evidence for the use of MRI-PDFF to non-invasively quantify the efficacy of therapeutic agents for reducing hepatic fat in people with MASH. In conclusion, this updated network meta-analysis provides an updated, relative rank-order efficacy of therapies for MASH in reducing hepatic fat. These data may help inform the design and sample size calculation of future clinical trials and assist selection of combination therapy.
Supplementary Material
Acknowledgements
All authors have made substantial contributions to all of the following: (1) the conception and design of the study, or acquisition of data, or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted. No writing assistance was obtained in the preparation of the manuscript. The manuscript, including related data, figures and tables has not been previously published and that the manuscript is not under consideration elsewhere.
Funding
Daniel Q. Huang received funding support from the Singapore Ministry of Health’s National Medical Research Council (MOH-001370). Rohit Loomba received funding support from NCATS (5UL1TR001442), NIDDK (U01DK061734, U01DK130190, R01DK106419, R01DK121378, R01DK124318, P30DK120515), NHLBI (P01HL147835), and John C Martin Foundation (RP124).
Footnotes
Conflicts of Interests
Cheng Han Ng consults for Boxer Capital. Mazen Noureddin advises and received grants from Boehringer Ingelheim, Gilead, GlaxoSmithKline, Madrigal, Novo Nordisk, Pfizer, Takeda, and Terns. He advises 89bio, Altimmune, Blade, CohBar, CytoDyn, Echosens, Fractyl, Intercept, Merck, NorthSea, Roche, and Siemens. He received grants from Allergan, Akero, Boehringer Ingelheim, Bristol Myers Squibb, Conatus, Corcept, Enanta, Galectin, Galmed, GENFIT, Novartis, Shire, Viking, and Zydus. He owns stock in Anaetos, ChronWell, CytoDyn, Rivus, and Viking. Daniel Q. Huang consults for Gilead and Roche. Rohit Loomba consults and received grants from Arrowhead, AstraZeneca, Bristol Myers Squibb, Eli Lilly, Galmed, Gilead, Intercept, Inventiva, Ionis, Janssen, Madrigal, Merck, NGM Bio, Novo Nordisk, Pfizer, and Terns. He consults and owns stock in Sagimet. He consults for 89bio, Aardvark, Altimmune, Alnylam/Regeneron, Amgen, Cascade, CohBar, Glympse Bio, HighTide, Inipharm, Lipidio, Metacrine, NeuroBo, Novartis, Takeda, Theratechnologies, and Viking. He received grants from Boehringer Ingelheim, Galectin, Hanmi, and Sonic Incytes. He has other interests with LipoNexus. The remaining authors have no conflicts to report.
Ethical Statement
The study was conducted in accordance with the Declaration of Helsinki. The study was exempt from IRB review was no confidential patient information was involved.
Data Availability
No dataset was used in this study. All articles in this manuscript are publicly available from Medline and Embase.
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Data Availability Statement
No dataset was used in this study. All articles in this manuscript are publicly available from Medline and Embase.