Efficacy, Safety, and Tolerability of Oral Semaglutide Versus Placebo Added to Insulin With or Without Metformin in Patients With Type 2 Diabetes: The PIONEER 8 Trial
Bibliographic record
Abstract
OBJECTIVE To investigate the efficacy, safety, and tolerability of oral semaglutide added to insulin with or without metformin. RESEARCH DESIGN AND METHODS Patients with type 2 diabetes uncontrolled on insulin with or without metformin were randomized to oral semaglutide 3 mg (N = 184), 7 mg (N = 182), or 14 mg (N = 181) or to placebo (N = 184) in a 52-week, double-blind trial. End points were change from baseline to week 26 in HbA1c (primary) and body weight (confirmatory secondary). Two estimands were defined: treatment policy (effect regardless of trial product discontinuation or rescue medication) and trial product (effect assuming trial product continuation without rescue medication) in randomized patients. RESULTS Oral semaglutide was superior to placebo in reducing HbA1c (estimated treatment difference [ETD] –0.5% [95% CI –0.7, –0.3], –0.9% [–1.1, –0.7], and –1.2% [–1.4, –1.0] for 3, 7, and 14 mg, respectively; P < 0.001) and body weight (ETD −0.9 kg [95% CI −1.8, −0.0], −2.0 kg [−3.0, −1.0], and −3.3 kg [−4.2, −2.3]; P = 0.0392 for 3 mg, P ≤ 0.0001 for 7 and 14 mg) at week 26 (treatment policy estimand). Significantly greater dose-dependent HbA1c and body weight reductions versus placebo were achieved with oral semaglutide at weeks 26 and 52 (both estimands). The most frequent adverse event with oral semaglutide was nausea (11.4–23.2% of patients vs. 7.1% with placebo; mostly mild to moderate). CONCLUSIONS Oral semaglutide was superior to placebo in reducing HbA1c and body weight when added to insulin with or without metformin in patients with type 2 diabetes. The safety profile was consistent with other glucagon-like peptide 1 receptor agonists.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".