Weight change with liraglutide and comparator therapies: an analysis of seven phase 3 trials from the liraglutide diabetes development programme
Bibliographic record
Abstract
AIM: We investigated the relationship between weight change and related factors in subjects with type 2 diabetes mellitus (T2DM) treated with liraglutide versus comparator diabetes therapies. METHODS: Twenty-six-week data from seven phase 3, randomized trials in the liraglutide T2DM development programme were analysed by trial and treatment group: liraglutide (1.2 and 1.8 mg), active comparator and placebo. Outcome measures included proportions of subjects in various weight change categories and their percentage weight change from baseline; impact of body mass index (BMI) and gastrointestinal (GI) adverse events (AEs) on weight change and correlation of weight change with change in glycosylated haemoglobin (HbA1c). RESULTS: A number of subjects experienced >5% weight loss during the trials (24.4% liraglutide 1.8 mg and 17.7% liraglutide 1.2 mg; 17.7% exenatide, 10.0% sitagliptin, 3.6-7.0% sulphonylurea, 2.6% thiazolidinedione and 2.6% glargine; 9.9% placebo). More weight loss was seen with liraglutide 1.2 and 1.8 mg than with active comparators except exenatide. Across trials, higher initial BMI was associated with slightly greater weight loss with liraglutide. Mean weight loss increased slightly the longer GI AEs persisted. Although HbA1c reduction was slightly larger in higher weight loss categories across treatments (including placebo), sample sizes were small and no clear correlation could be determined. Liraglutide-treated subjects experienced additional HbA1c reduction beyond that which appeared weight induced; thus, not all HbA1c-lowering effect appears weight mediated. CONCLUSIONS: The majority of liraglutide-treated T2DM subjects experienced weight loss in this analysis. Weight loss was greater and occurred more in glucagon-like peptide-1 receptor agonist-treated subjects than in active comparator-treated subjects.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".