Glycaemic target attainment in people with Type 2 diabetes treated with insulin glargine/lixisenatide fixed‐ratio combination: a <i>post hoc</i> analysis of the LixiLan‐O and LixiLan‐L trials
Bibliographic record
Abstract
Abstract Aims Both fasting (FPG) and postprandial plasma glucose (PPG) contribute to HbA1c levels. We investigated the relationship between achievement of American Diabetes Association (ADA) and American Association of Clinical Endocrinologists (AACE) recommended FPG and/or PPG targets and glycaemic efficacy outcomes in two trials. Methods In this post hoc analysis, data from participants with Type 2 diabetes in the phase 3 LixiLan‐O (NCT 02058147) and LixiLan‐L (NCT 02058160) trials were evaluated to compare the relationship between achievement of society‐recommended FPG and/or PPG targets and efficacy (HbA1c change, HbA1c goal attainment, weight change) and safety outcomes in the treatment groups. Results Across treatment arms, iGlarLixi achieved the highest proportion of participants meeting both ADA‐ and AACE‐recommended FPG and PPG targets at study end in both trials. A higher proportion of participants in the iGlarLixi (fixed‐ratio combination of insulin glargine and lixisenatide) vs. insulin glargine alone or lixisenatide alone treatment arms achieved HbA1c goals (P < 0.001 for overall comparisons), irrespective of ADA‐ or AACE‐defined targets. Hypoglycaemia rates [any, documented symptomatic (plasma glucose ≤ 3.9 mmol/l), and clinically important (plasma glucose < 3.0 mmol/l)] were low across all groups. Participants treated with iGlarLixi tended to show weight loss or less weight gain compared with participants receiving insulin glargine alone. No differences were observed in average daily basal insulin dose at week 30 between the two treatment arms or across the different FPG and PPG target groups. Conclusion Insulin glargine and lixisenatide as a fixed‐ratio combination resulted in more participants reaching both FPG and PPG targets, leading to better HbA1c target attainment.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".