The Association of Sodium-Glucose Cotransporter 2 Inhibitors With Cardiovascular Outcomes in Anthracycline-Treated Patients With Cancer
Bibliographic record
Abstract
Sodium glucose cotransporter-2 inhibitors (SGLT2is) are hypothesized to reduce the risk of anthracycline-associated cardiotoxicity. This study sought to determine the association between SGLT2is and cardiovascular disease (CVD) after anthracycline-containing chemotherapy. Using administrative data sets, we conducted a population-based cohort study of people >65 years of age with treated diabetes and no prior heart failure (HF) who received anthracyclines between January 1, 2016, and December 31, 2019. After estimating propensity scores for SGLT2i use, the average treatment effects for the treated weights were used to reduce baseline differences between SGLT2i-exposed and -unexposed controls. The outcomes were hospitalization for HF, incident HF diagnoses (in- or out-of-hospital), and documentation of any CVD in future hospitalizations. Death was treated as a competing risk. Cause-specific HRs for each outcome were determined for SGLT2i-treated people relative to unexposed controls. We studied 933 patients (median age 71.0 years, 62.2% female), 99 of whom were SGLT2i treated. During a median follow-up of 1.6 years, there were 31 hospitalizations for HF (0 in the SGLT2i group), 93 new HF diagnoses, and 74 hospitalizations with documented CVD. Relative to controls, SGLT2i exposure was associated with HR of 0 for HF hospitalization (P < 0.001) but no significant difference in incident HF diagnosis (HR: 0.55; 95% CI: 0.23-1.31; P = 0.18) or CVD diagnosis (HR: 0.39; 95% CI: 0.12-1.28; P = 0.12). There was no significant difference in mortality (HR: 0.63; 95% CI: 0.36-1.11; P = 0.11). SGLT2is may reduce the rate of HF hospitalization after anthracycline-containing chemotherapy. This hypothesis warrants further testing in randomized controlled trials.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".