Pharmacotherapy for adults with metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction–associated steatohepatitis (MASH): a systematic review and network meta-analysis
Bibliographic record
Abstract
ABSTRACT Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) have risen substantially in prevalence over recent decades, driven by a growing global burden of obesity, diabetes mellitus, and other cardiometabolic risk factors. In response, researchers have intensified efforts to evaluate novel and re-purposed therapies that may prevent or reverse disease progression. Although several pharmacological therapies are under investigation, robust comparative evidence on their relative effectiveness and safety remains limited. We will therefore conduct a systematic review and network meta-analysis (SRNMA) of randomized controlled trials (RCTs) evaluating pharmacological therapies for adults with MASLD or MASH. Methods We will search four electronic databases (Ovid MEDLINE, Embase, CINAHL and Cochrane CENTRAL) from inception to August 2025 without language and other restrictions. Eligible studies will include parallel-arm RCTs enrolling ≥10 adults per arm with MASLD or MASH; comparing any pharmacological therapy to standard care, no treatment, lifestyle modifications, placebo or alternative pharmacotherapies; and having a minimum follow-up duration of 12 weeks. Primary clinical outcomes are all-cause mortality, cardiovascular mortality, hospitalization, progression to cirrhosis, hepatic decompensation, hepatocellular carcinoma, and serious treatment-related adverse events. Surrogate outcomes include histological, imaging, biochemical, and metabolic markers of disease activity. Paired reviewers will independently screen identified hits for eligibility, extract data from eligible studies, and assess risk of bias using the Risk Of Bias instrument for Use in SysTematic reviews-for Randomised Controlled Trials (ROBUST-RCT). We will conduct separate NMAs for MASLD and MASH populations using a frequentist graph-theoretic random-effects model. Certainty of evidence will be assessed using GRADE. Subgroup and sensitivity analyses will explore effect modification by comorbidities and study quality. Ethics and Dissemination No ethics approval is required. Results will be disseminated via peer-reviewed publication and conference presentations to inform clinicians, guideline developers, and health system decision-makers. PROSPERO Registration Number CRD420251103235.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".