Efficacy and Safety of Alogliptin in Patients With Type 2 Diabetes: Analysis of the ATTAK-J Study
Bibliographic record
Abstract
BACKGROUND: Dipeptidyl peptidase-4 (DPP-4) inhibitors have been shown to reduce hemoglobin A1c (HbA1c) in patients with type 2 diabetes, but the reduction varies between patients and adequate glycemic control may not be achieved. We evaluated the efficacy and safety of the DPP-4 inhibitor alogliptin in the real clinical setting, and analyzed factors associated with the improvement of HbA1c by alogliptin treatment. METHODS: A retrospective observational study was performed in patients with type 2 diabetes attending hospitals or clinics belonging to the Kanagawa Physicians Association who received treatment with alogliptin for 1 year or longer. Patients using insulin were excluded from the study. The efficacy endpoints were HbA1c (National Glycohemoglobin Standardization Program value), blood glucose (fasting/postprandial), body weight, blood pressure (systolic/diastolic), liver function (glutamate oxaloacetate transaminase, glutamate pyruvate transaminase, and γ-glutamyl transpeptidase), kidney function (serum creatinine and estimated glomerular filtration rate), serum lipids (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides), and serum amylase. Adverse events were compiled to assess safety. RESULTS: Of 330 patients whose case records were collected, 27 patients were excluded for protocol violations, leaving 303 patients to form the full analysis set. Compared with baseline, HbA1c showed a decrease by 0.54±1.22% (mean ± standard deviation) after 12 months of alogliptin treatment. Factor analysis demonstrated that the change of HbA1c after 12 months was significantly influenced by the baseline HbA1c level, duration of diabetes, concomitant use of sulfonylureas, and compliance with diet therapy. In addition, there was a significant reduction of total cholesterol, low-density lipoprotein cholesterol, and the estimated glomerular filtration rate after 12 months of alogliptin treatment, as well as a significant increase in serum creatinine. No significant changes of body weight, blood pressure, or liver function were observed. Symptoms of hypoglycemia occurred in two patients (0.6%). CONCLUSIONS: Alogliptin displayed a significant hypoglycemic effect and excellent safety in routine clinical use. Factors influencing the change of HbA1c with alogliptin therapy may include the HbA1c at the start of treatment, the duration of diabetes, use of sulfonylureas, and compliance with diet therapy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".