Efficacy and safety of switching to insulin icodec, a once-weekly basal insulin, vs insulin glargine U100 in patients with type 2 diabetes inadequately controlled on OADs and basal insulin
Bibliographic record
Abstract
Background Insulin icodec (icodec) is a novel basal insulin analogue in development as the first once-weekly insulin. Methods This 16-week phase 2 trial compared the efficacy and safety of once-weekly icodec with and without a loading dose (LD) vs once-daily IGlar U100 in patients with T2D insufficiently controlled (HbA1c 7.0-10.0%) with oral antidiabetic drugs and once/twice-daily insulin. Insulin doses were titrated weekly to a target of 4.4-7.2 mmol/L The primary endpoint was time in range (TIR) 3.9-10.0 mmol/L (based on continuous glucose monitoring (Dexcom G6®) during weeks 15 and 16. Secondary endpoints included HbA1c and hypoglycaemic episodes. Results Patients (N=154) were randomized 1:1:1 to icodec + LD (n=54), icodec (n=50) or IGlar U100 (n=50). TIR (weeks 15 and 16) was statistically significantly greater for icodec + LD than for IGlar U100 (72.9 vs 65.0%, estimated treatment difference [ETD]: 7.88%; p=0.01) and similar between icodec and IGlar U100. For icodec + LD, icodec and IGlar U100, respectively, the estimated mean changes from baseline in HbA1c were: -0.77, -0.47 and -0.54%-points. Observed rates of combined level 2 (<3 mmol/L or < 54 mg/dL) and 3 (severe) hypoglycaemia were similar between icodec + LD and IGlar, and numerically lower for icodec. Conclusion Switching to once-weekly insulin icodec was well tolerated and efficacious. Switching to icodec with a loading dose resulted in significantly more “time in range” without an increased risk of clinically significant hypoglycaemia vs IGlar U100. Publication History Article published online: 26 May 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 |
| 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".