Achievement of HbA1c ≤6.5% (47.5mmol/mol), with ≥10% weight loss, without hypoglycemia in patients treated with tirzepatide vs. comparators in SURPASS program
Bibliographic record
Abstract
Question What are the proportion of participants treated with tirzepatide (TZP) achieving a triple composite endpoint of HbA1c ≤ 6.5 with ≥ 10% weight loss without hypoglycemia? Methodology The purpose of this post-hoc analysis was to compare the percentage of participants achieving a composite endpoint of HbA1c ≤ 6.5% (47.5mmol/mol) with ≥ 10% weight loss without hypoglycemia in the SURPASS studies. End of treatment HbA1c and weight were evaluated at week 40 (SURPASS-1, 2, 5) and week 52 (SURPASS-3, 4). Results More participants treated with TZP (any dose) achieved the triple endpoint vs placebo or active comparators in SURPASS 1-5. TZP monotherapy (5, 10, 15mg) led to 25%, 36%, 44% participants achieving the triple endpoint vs 0% with placebo (SURPASS-1). As add-on to metformin, TZP (5, 10, 15mg) led to 33%, 50%, 59% achieving the same vs 22% with semaglutide (SEMA) 1mg (SURPASS-2). When compared to basal insulin, TZP (5, 10, 15mg) led to 33%, 50%, 64% achieving the triple endpoint vs 3% with degludec (SURPASS-3; add-on to metformin) and when added to 1-3 oral antihyperglycemics, TZP (5, 10, 15mg) led to 28%, 44%, 53% achieving the triple endpoint vs 1% with glargine U100 (SURPASS-4). As add-on to basal insulin, TZP (5, 10, 15mg) led to 16%, 35%, 40% achieving the triple endpoint vs 1% with placebo (SURPASS-5). Conclusion Significantly more participants treated with TZP achieved a HbA1c ≤ 6.5% (47.5mmol/mol) with ≥ 10% weight loss without hypoglycemia vs placebo, SEMA, or basal insulin in SURPASS-1 to -5 studies. Publication History Article published online: 02 May 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".