#800 The effect of canagliflozin dose on cardiovascular and renal outcomes in patients with type 2 diabetes and high cardiovascular risk
Bibliographic record
Abstract
Abstract Background and Aims Sodium-glucose co-transporter-2 (SGLT-2) inhibitors have revolutionized the management of chronic kidney disease (CKD). As shown in large randomized clinical trials, they reduce the incidence of atherosclerotic cardiovascular disease and heart failure and they delay CKD progression. There is evidence from pharmacokinetic studies that their effect on surrogate endpoints, such as albuminuria or blood pressure, might be dose dependent. However, the effect of SGLT-2 inhibitor dosage on hard clinical endpoints has not been adequately studied. This analysis investigates whether the effects of canagliflozin on cardiovascular and renal endpoints are dose dependent. Methods The CANVAS trial (Canagliflozin Cardiovascular Assessment Study) randomly assigned 4,330 patients with type 2 diabetes and high cardiovascular risk to receive canagliflozin 100 mg, canagliflozin 300 mg, or placebo in a 1:1:1 ratio. Results from this trial were reported together with CANVAS-R in the CANVAS program but have not been published independently [1]. Our post-hoc analysis evaluates the impact of each dose of canagliflozin on cardiovascular and renal outcomes. Our primary endpoint was a composite of non-fatal myocardial infarction, stroke, or cardiovascular death. Secondary endpoints included the individual components of the primary outcome, hospitalization for heart failure, all-cause mortality, a composite renal endpoint (including doubling of serum creatinine, end-stage kidney disease or renal death), sustained 40% reduction in estimated glomerular filtration rate, and albuminuria progression or regression. Safety outcomes included acute kidney injury and serious hyperkalemia. Hazard ratios (HR) were estimated using Cox proportional hazards models. Kaplan-Meier survival curves were compared across groups using the log-rank test. Results The study enrolled 4330 participants with type 2 diabetes and high cardiovascular risk. Median age was 61 years and 66% of patients were males. Baseline characteristics were similar across all treatment groups. Median follow-up was 74 months. In the adjusted analysis for age, sex, and history of cardiovascular disease, canagliflozin at 300 mg significantly reduced the incidence of the composite cardiovascular endpoint, compared with placebo: hazard ratio (HR) of 0.83, 95% confidence interval (CI) of 0.68–1.00 (p = 0.049). In contrast, no difference was identified between canagliflozin 100 mg, compared with placebo, for the composite cardiovascular endpoint: HR 0.96 (95% CI 0.80–1.15, p = 0.64). Both doses of canagliflozin were associated with a significant reduction in the incidence of the composite renal endpoint, compared with placebo: HR 0.50 for canagliflozin 100 mg (95% CI 0.25–0.96, p = 0.039) and HR 0.42 for canagliflozin 300 mg (95% CI 0.21–0.86, p = 0.017). Albuminuria progression to a higher stage (A1 to A2 or A2 to A3) was less common with the 300 mg dose, compared with placebo (HR 0.83, 95% CI 0.73–0.95, p = 0.006), but not with 100 mg dose (HR 0.94, 95% CI 0.83–1.07, p = 0.326). All-cause mortality was significantly lower with the 300 mg dose compared with placebo (HR 0.78, 95% CI 0.63–0.97, p = 0.027). In addition, a trend towards lower mortality rates was seen with the 100 mg dose. The incidence of acute kidney injury was comparable across the three treatment arms. A trend towards fewer severe hyperkalemia episodes was seen with the 300 mg canagliflozin dose. Results for all secondary and safety endpoints are shown in Table. Conclusion This post-hoc analysis of the CANVAS trial demonstrates a dose-dependent effect of canagliflozin on cardiovascular endpoints. However, both doses of canagliflozin seem equally effective for the prevention of hard clinical renal endpoints. In addition, both doses of the drug had a comparable safety profile. Our findings suggest that the higher canagliflozin dose may be considered in all patients with type 2 diabetes at high cardiovascular risk.
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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 | 0.002 | 0.004 |
| 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) | 0.006 | 0.001 |
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".