Assessment of Pancreas Safety in the Development Program of Once-Weekly GLP-1 Receptor Agonist Dulaglutide
Bibliographic record
Abstract
OBJECTIVE To assess the risk of acute pancreatitis during treatment with glucagon-like peptide 1 receptor agonist dulaglutide, placebo, and active comparators across phase 2/3 dulaglutide trials. RESEARCH DESIGN AND METHODS A total of 6,005 patients with type 2 diabetes participated (dulaglutide group N = 4,006 [dose range 0.1–3.0 mg]; active comparator group [metformin, sitagliptin, exenatide twice daily, insulin glargine] N = 1,541; placebo group N = 703; 245 placebo-treated patients subsequently received dulaglutide or sitagliptin and were also included in these groups) for up to 104 weeks. The following events were adjudicated: investigator-reported pancreatitis, adverse events (AEs) of severe or serious abdominal pain of unknown etiology, and confirmed asymptomatic increases in pancreatic enzymes ≥3× the upper limit of normal range. RESULTS Overall, 203 events from 151 patients underwent adjudication (dulaglutide group n = 108; comparator group including placebo n = 43). Acute pancreatitis was confirmed by adjudication in seven patients (dulaglutide n = 3, placebo n = 1, sitagliptin n = 3). Exposure-adjusted incidence rates were as follows: dulaglutide group 0.85 patients/1,000 patient-years, placebo group 3.52 patients/1,000 patient-years, sitagliptin group 4.71 patients/1,000 patient-years. No events of pancreatitis were confirmed by adjudication in patients treated with exenatide twice daily, metformin, or glargine. Increases in median values of lipase and pancreatic amylase within the normal range were observed with all treatments except glargine. These changes were not associated with AEs. CONCLUSIONS The exposure-adjusted incidence rate of acute pancreatitis in dulaglutide-treated patients was similar to the rates with placebo, with few reported cases during the entire program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".