Achievement of glycaemic targets with weight loss and without hypoglycaemia in type 2 diabetes with the once‐weekly glucose‐dependent insulinotropic polypeptide and glucagon‐like peptide‐1 receptor agonist tirzepatide: A <i>post hoc</i> analysis of the <scp>SURPASS</scp> ‐1 to ‐5 studies
Bibliographic record
Abstract
AIM: To assess composite endpoints combining glycaemic control (HbA1c < 7.0%, ≤ 6.5% or < 5.7%) with weight loss (≥ 5%, ≥ 10% or ≥ 15%) and without hypoglycaemia with tirzepatide in type 2 diabetes (T2D). MATERIALS AND METHODS: Data from the phase 3 SURPASS programme were evaluated post hoc by trial. Participants with T2D were randomized to tirzepatide (5, 10 and 15 mg), placebo (SURPASS-1,5), semaglutide 1 mg (SURPASS-2) or titrated basal insulin (SURPASS-3,4). The proportions of participants achieving the composite endpoints were compared between tirzepatide and the respective comparator groups at week 40/52. RESULTS: The proportions of participants achieving an HbA1c value of less than 7.0% with 5% or more weight loss and without hypoglycaemia ranged from 43% to 82% with tirzepatide across the SURPASS-1 to -5 trials versus 4%-5% with placebo, 51% with semaglutide 1 mg and 5% with basal insulin (P < .001 vs. all comparators). The proportions of participants achieving an HbA1c value of less than 7.0% with 10% or more, or 15% or more weight loss and without hypoglycaemia were significantly higher with all tirzepatide doses versus comparators across trials (P < .001 or P < .05). Similar results were observed for all other combinations of endpoints with an HbA1c value of 6.5% or less, or less than 5.7%, with more tirzepatide-treated participants achieving these endpoints versus those in the comparator groups, including semaglutide. CONCLUSIONS: Across the SURPASS-1 to -5 clinical trials, more tirzepatide-treated participants with T2D achieved clinically meaningful composite endpoints, which included reaching glycaemic targets with various degrees of weight loss and without hypoglycaemia, than those in the comparator 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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| 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) | 0.002 | 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".