Weight Reduction Heterogenicity and Mediators of GLP-1RAs and Dual Agonists for Individuals With Obesity: A Meta-Analysis

Original title: Weight Reduction Heterogenicity and Mediators of GLP-1RAs and Dual Agonists for Individuals With Obesity: A Meta-Analysis.

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and dual agonists have become pivotal options for obesity, but marked weight loss heterogeneity remains poorly understood.

By Lu, Li, Yuan +1Clinical obesityOct 1, 2026

Score█████░░░░░5.2

Key numbers

95% CI 7.92%

VerdictA leading story on any desk.

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Abstract

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and dual agonists have become pivotal options for obesity, but marked weight loss heterogeneity remains poorly understood. This meta-regression analysis aimed to identify factors influencing this heterogeneity. We searched Medline, Embase, The Cochrane Library, and Web of Science up to February 1, 2026, enrolling 32 eligible trials (40 408 participants) following PRISMA guidelines. Meta-regression and subgroup analyses were performed using R software. Pooled analysis showed that GLP-1RAs and dual agonists achieved a weighted mean weight reduction of 9.36% (95% CI 7.92%-10.80%), with high interstudy heterogeneity (I2 = 99.6%, p < 0.001). Subgroup analyses revealed that GLP-1/GIP dual agonists (tirzepatide) and longer treatment duration (≥ 72 weeks) yielded superior weight-lowering effects. Meta-regression demonstrated that baseline anxiety/depression was positively associated with weight loss efficacy (β = 2.44, p < 0.001, R2 = 81.34%). Comorbid Type 2 diabetes mellitus (T2DM), obstructive sleep apnea (OSA) and metabolic dysfunction-associated fatty liver disease (MAFLD) were negatively correlated with treatment response (all p < 0.05). Emotional state and metabolic comorbidities including T2DM, OSA and MAFLD are important influencing factors of the interindividual differences of weight loss efficacy of GLP-1RAs and dual agonists, providing evidence for personalized obesity management.

Difei Lu, Na Li, Zhenfang Yuan, Ying Gao

The editor's rubric

Heuristic review

Dimension	Level	Weight	What that level means
Leverage	██░░░ 2	10%	Reusable within one subfield (a technique, dataset, or protocol a few groups will adopt).
Magnitude	███░░ 3	20%	Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
Evidence	█████ 5	32%	Definitive: phase 3 randomized evidence on hard endpoints, multi-lab replication, or community verification at scale.
Novelty	██░░░ 2	8%	A new combination of known ideas.
Trajectory	██░░░ 2	5%	Some room to improve with obvious engineering.
Stakes	███░░ 3	25%	Meaningful benefit to many people within a few years.

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: gains (relative gain, outperforms); design (phase 3, meta-analysis); verification (confidence interval, p-value); stakes (major disease, prevention or cure).

How the score was computed

rank-2026-09-29

Score█████░░░░░5.2

Score = 10 × (80% × adjusted merit / 10 + 10% × attention + 10% × freshness)

Merit: 6.8 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 5.3 / 10; Shrunk toward the desk prior by editor confidence (46%).
Attention: 0%; Citations, upvotes, points, mentions.
Freshness: 98%; Half-life decay since publication.

Citations0 (reference 20, via openalex, Oct 1, 2026, 06:17 UTC)
Field-weighted citation impact0 (reference 3, via openalex, Oct 1, 2026, 06:17 UTC)

The record

Reviewed by heuristic-v2 on Oct 1, 2026, 06:17 UTC. Paper type: clinical.
Categories: Meta-Analysis, review-article, Review, Journal Article, Humans, Diabetes Mellitus, Type 2, Obesity, Weight Loss, Anti-Obesity Agents, Glucagon-Like Peptide-1 Receptor Agonists
BRIEF, No.1 in the Medicine edition of October 1, 2026.