Oral glucose lowering with linagliptin and metformin compared with linagliptin alone as initial treatment in Asian patients with newly diagnosed type 2 diabetes and marked hyperglycemia: Subgroup analysis of a randomized clinical trial
Bibliographic record
Abstract
AIMS/INTRODUCTION: Type 2 diabetes mellitus is an epidemic in Asia, yet clinical trials of glucose-lowering therapies often enroll predominantly Western populations. We explored the initial combination of metformin and linagliptin, a dipeptidyl peptidase-4 inhibitor, in newly diagnosed type 2 diabetes mellitus patients in Asia with marked hyperglycemia. MATERIALS AND METHODS: This was a post-hoc subgroup analysis of a multinational, parallel-group clinical trial in which 316 newly diagnosed type 2 diabetes mellitus patients with glycated hemoglobin A1c (HbA1c) 8.5-12.0% were randomized to double-blind oral treatment with linagliptin/metformin or linagliptin monotherapy. The primary end-point was the change from baseline in HbA1c at week 24. We evaluated data for the 125 participants from Asian countries. RESULTS: After 24 weeks, the mean ± standard error reduction from baseline in HbA1c (mean 10.0%) was -2.99 ± 0.18% with linagliptin/metformin and -1.84 ± 0.18% with linagliptin; a treatment difference of -1.15% (95% confidence interval -1.65 to -0.66, P < 0.0001). HbA1c <7.0% was achieved by 60% of participants receiving linagliptin/metformin. The mean bodyweight change after 24 weeks was -0.45 ± 0.41 kg and 1.33 ± 0.45 kg in the linagliptin/metformin and linagliptin groups, respectively (treatment difference -1.78 kg [95% confidence interval -2.99 to -0.57, P = 0.0043]). Drug-related adverse events occurred in 9.7% of participants receiving linagliptin/metformin and 4.8% of those receiving linagliptin. Hypoglycemia occurred in 6.5% and 4.8% of the linagliptin/metformin and linagliptin groups, respectively, with no severe episodes. Gastrointestinal disorders occurred in 12.9% and 12.7% of the linagliptin/metformin and linagliptin groups, respectively, with no associated treatment discontinuations. CONCLUSIONS: In people from Asia with newly diagnosed type 2 diabetes mellitus and marked hyperglycemia, the initial combination of linagliptin and metformin substantially improved glycemic control without weight gain and with infrequent hypoglycemia. Initial oral combination therapy might be a viable treatment for such individuals.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".