Abstract 12767: Sodium-Glucose Cotransporter-2 Inhibitors Are Associated With Lower Risks of Hospitalization for Heart Failure and All-Cause Mortality in Patients With Diabetes Mellitus and Cancer
Bibliographic record
Abstract
Introduction: Patients with cancer face a heightened risk of cardiovascular (CV) events and mortality. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce CV events in at-risk patients and may possess antitumor effects. Therefore, we examined the effect of SGLT2i on CV events and mortality among patients with cancer and diabetes. Methods: This was a retrospective propensity score-matched cohort study conducted at two tertiary referral centers in Taiwan. We included all adult patients with type 2 diabetes mellitus diagnosed with cancer between January 2010 and December 2021. The primary outcomes were hospitalization for incident heart failure (HF) and all-cause mortality. The secondary outcomes were a composite of myocardial infarction, ischemic stroke, and cardiac arrhythmias, and serious adverse events associated with SGLT2i. Results: From a total of 8640 patients, 878 SGLT2i-recipients were matched to non-recipients. During a median follow-up period of 18.8 months, SGLT2i recipients had a lower rate of hospitalization for incident HF compared with non-SGLT2i recipients (2.92 vs. 8.95 per 1000 patient-years, p=0.018). In both Cox regression and competing regression models, SGLT2i were associated with a 70% reduction in the risk for hospitalization for incident HF (HR, 0.28 [95% CI: 0.11-0.77], p = 0.013; SHR, 0.32 [95% CI: 0.12-0.84], p = 0.021). The use of SGLT2i was associated with a higher overall survival (85.3% vs. 63.0% at 2 years, p<0.001). The risk of myocardial infarction, ischemic stroke, cardiac arrhythmias, and serious adverse events such as hypoglycemia, urosepsis, and sepsis was similar between the SGLT2i and non-SGLT2i cohorts. Conclusions: The use of SGLT2i was associated with a lower rate of hospitalization for incident HF and prolonged overall survival in cancer patients with diabetes mellitus.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".