Development of the European Association for the Study of Obesity (EASO) Grade-Based Framework on the Pharmacological Treatment of Obesity: Design and Methodological Aspects
Bibliographic record
Abstract
Introduction: The aim of this study was to describe the design and methodological aspects of the upcoming European Association for the Study of Obesity (EASO) Framework for the Pharmacological Treatment of Obesity utilizing currently available evidence, which is grounded in a rigorous and transparent approach to evidence synthesis and guideline development. Methods: An expert panel of 13 members, selected by EASO, has developed the framework using the GRADE methodology to ensure transparent, evidence-based guideline development. Clinical questions were formulated using the population, intervention, comparator, outcomes (PICO) framework, focusing on the effectiveness and safety of European Medicines Agency-approved obesity management medications, including orlistat, naltrexone/bupropion, liraglutide, semaglutide, and tirzepatide. A comprehensive literature search is being conducted using Medline and Embase, including randomized controlled trials with a minimum duration of 48 weeks. Meta-analyses and network meta-analyses are planned to compare treatment effectiveness and safety profiles across various patient subgroups. The guidelines will target adults with a body mass index (BMI) ≥27 kg/m2 and at least one weight-related comorbidity or a BMI ≥30 kg/m2. The primary endpoint will be total body weight loss. Secondary outcomes include changes in body composition (i.e., fat mass, fat-free mass), metabolic improvements (i.e., glucose levels, HbA1c, lipid profile), remission of obesity-related comorbidities (i.e., type 2 diabetes, obstructive sleep apnea syndrome, metabolic dysfunction-associated steatotic liver disease, cardiovascular disease, and knee osteoarthritis), and improvements in mental health and quality of life. The methodological framework ensures that recommendations are tailored, evidence-based, and applicable across clinical settings. Conclusions: The EASO framework provides a structured and individualized approach to optimize pharmacological treatment for obesity. Its methodological rigor, based on GRADE and PICO, enhances the reliability, reproducibility, and clinical relevance of the guidelines. By integrating clinical efficacy, safety outcomes, and patient-specific factors, this framework offers solid, actionable guidance to support healthcare professionals in delivering high-quality, personalized obesity care. .
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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 | 0.456 | 0.481 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.012 | 0.013 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".