Evaluation of the Pharmacokinetics and Exposure–Response Relationship of Dapagliflozin in Patients without Diabetes and with Chronic Kidney Disease
Bibliographic record
Abstract
Dapagliflozin, a sodium-glucose co-transporter inhibitor, was originally developed as an oral glucose-lowering drug for the treatment of type 2 diabetes mellitus. Emerging data suggest that cardiovascular and kidney benefits extend to patients without diabetes. Limited pharmacological data are, however, available in patients without diabetes. We aimed to characterise the pharmacokinetic profile of dapagliflozin in patients with chronic kidney disease without type 2 diabetes. Plasma samples were collected in a randomised, placebo-controlled, double-blind, cross-over trial (DIAMOND, NCT03190694, n = 53) that assessed the effects of 10 mg of dapagliflozin in patients with a glomerular filtration rate ≥ 25 mL/min/1.73 m 2 and proteinuria > 500 mg/day. Mixed-effects models were used to develop a pharmacokinetic model and to evaluate the association between plasma exposure and response. Plasma concentrations ( n = 430 observations) from 48 patients (mean age 50.8 years, mean glomerular filtration rate 57.9 mL/min/1.73 m 2 , median proteinuria 1115 mg/24 h) were best described using a two-compartment model with first-order elimination. Apparent clearance and volume of distribution were 11.7 (95% confidence interval 10.7–12.7) L/h and 44.9 (95% confidence interval 39.0–50.9) L, respectively. Median dapagliflozin plasma exposure was 740.9 ng h/mL (2.5th–97.5th percentiles: 434.0–1615.3). Plasma exposure increased with decreasing kidney function. Every 100-ng h/mL increment in dapagliflozin plasma exposure was associated with a decrease in the urinary albumin:creatinine ratio ( β = − 2.8%, p = 0.01), glomerular filtration rate ( β = − 0.5 mL/min/1.73 m 2 , p < 0.01) and systolic blood pressure ( β = − 0.4 mmHg, p = 0.03). The dapagliflozin plasma concentration–time profile in patients with non-diabetic kidney disease appears similar to the profile of patients with diabetic kidney disease described in the literature. Furthermore, the plasma exposure was associated with changes in risk markers for kidney disease.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".