Mediators of the effect of ertugliflozin on a composite kidney outcome in patients with type 2 diabetes and atherosclerotic cardiovascular disease: analyses from VERTIS CV
Bibliographic record
Abstract
Abstract Introduction Sodium–glucose cotransporter 2 (SGLT2) inhibitors have been shown to slow the decline of kidney function in outcome trials, but the biological mediator(s) underlying the therapeutic benefit are not well established. Purpose We performed a post-hoc analysis exploring potential mediators of the effects of the SGLT2 inhibitor ertugliflozin on the VERTIS CV exploratory kidney composite outcome (sustained 40% decrease from baseline in estimated glomerular filtration rate [eGFR], chronic kidney replacement therapy or kidney death). Methods In VERTIS CV, 8246 participants with type 2 diabetes mellitus and established atherosclerotic cardiovascular disease were randomised to placebo, ertugliflozin 5 mg or 15 mg (pooled for analyses, as prospectively planned), and were followed for a mean of 3.5 years. The hazard ratio (HR; 95% confidence interval) for the pre-specified exploratory kidney composite outcome was 0.66 (0.50, 0.88). Cox regression models were used to evaluate covariates that were significantly differentially changed from baseline with ertugliflozin treatment as candidate mediators, with a mediator identified as a covariate when added to an unadjusted model of randomised treatment assignment a) yielded a larger hazard ratio; and b) the mediator retained P<0.05 in the model (eGFR was excluded as a covariate). The percentage of mediation was determined by the proportional increase in the HR between the unadjusted and adjusted models for each post-randomisation period: early (first change from baseline measurement) and average (weighted average of change from baseline from all post-baseline measurements). Each potential mediator was tested individually, so across analyses, mediation % sums to >100%. Results Of 22 covariates significantly changed by ertugliflozin, nine were identified as potential mediators (Table). The covariates with a high percentage of mediation were those related to changes in blood erythrocytes (haemoglobin, haematocrit and red blood cell mass), with average changes in haemoglobin having the highest percentage of mediation (61.8%). Serum uric acid was associated with a mediation of 29.4% and 50.0% for the early and average post-randomisation effect periods, respectively. Early changes in glycated haemoglobin had a large mediation (50%), but the average change during the trial was not significant. Average change in serum albumin had a large mediation (29.4%). Average changes in body weight and systolic blood pressure had percentages of mediation of 41.2% and 14.7%, respectively. Conclusion Multiple factors may be involved in the reduction of the kidney composite outcome observed with ertugliflozin. In the short-term, changes in glycaemia had a high mediation effect. Over the long-term, changes suggestive of haemoconcentration and/or haematopoiesis (natriuresis-related effects), showed the highest percentage of mediation, followed by changes in serum uric acid and body weight (glucosuria-related effects). Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Sponsored by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA in collaboration with Pfizer Inc., New York, NY, USA
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".