Efficacy and safety of the glucagon-like peptide-1 receptor agonist lixisenatide versus the dipeptidyl peptidase-4 inhibitor sitagliptin in young (<50 years) obese patients with type 2 diabetes mellitus
Bibliographic record
Abstract
Objective To compare the efficacy and safety of the once-daily prandial glucagon-like peptide-1 receptor agonist lixisenatide with the dipeptidyl peptidase-4 inhibitor sitagliptin in patients aged <50 years affected by obesity and type 2 diabetes mellitus (T2DM). Materials and methods This was a 24-week, double-blind, randomized, parallel-group study. Obese patients with T2DM inadequately controlled on metformin were randomized to lixisenatide 20 μg once-daily injection ( n = 158) or once-daily oral sitagliptin 100 mg ( n = 161). The primary endpoint was the proportion of patients with a glycated hemoglobin (HbA 1c ) <7% and ≥5% weight loss at 24 weeks. Results The proportion of patients that achieved the primary endpoint was 12.0% for lixisenatide versus 7.5% for sitagliptin; weighted average of proportion difference: 4.6%, p = 0.1696). A total of 40.7% of patients achieved HbA 1c <7% with lixisenatide versus 40.0% with sitagliptin. Lixisenatide produced greater reductions in body weight (LS mean difference: −1.3 kg, p = 0.0006) and postprandial plasma glucose after a standardized meal test (LS mean difference: −34.4 mg/dL [−1.9 mmol/L], p = 0.0001) versus sitagliptin. There was a similar incidence of treatment-emergent adverse events (63.9% vs. 60.9%) and serious treatment-emergent adverse events (1.9% vs. 1.9%), with low rates of symptomatic hypoglycemia (0.6% vs. 1.9%) for lixisenatide and sitagliptin, respectively, and no cases of severe hypoglycemia. Conclusion In obese patients aged <50 years with T2DM, the proportion of patients with an HbA 1c <7% with weight loss ≥5% was similar between groups. Lixisenatide, however, resulted in significantly greater reductions in body weight and postprandial plasma glucose excursions than sitagliptin. Tolerability was similar between groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".