The effects of sodium-glucose cotransporter-2 inhibitors in chemotherapy-induced cardiotoxicity and mortality in patients with cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The effects of sodium-glucose cotransporter-2 (SGLT2) inhibitors on reducing cardiovascular events in different subgroups of diabetic patients are under investigation. The current systematic review and meta-analysis investigated the effects of SGLT2 inhibitors on preventing cardiovascular events and mortality and their adverse events in patients with active cancer and diabetes undergoing cardiotoxic cancer treatment. METHODS: We searched PubMed, Embase, Web of Science, and Scopus to find studies investigating the effects of SGLT2 inhibitors on patients with diabetes and confirmed cancer until 19 August 2024. Meta-analyses were conducted using the random-effects model to compare all-cause mortality, cancer-associated mortality, heart failure (HF) hospitalization, arrhythmia, and adverse event rates such as ketoacidosis, hypoglycemia, urinary tract infection, and sepsis between patients with or without SGLT2 inhibitors use. Risk ratios (RRs) with 95% confidence intervals (CI) were used to compare outcomes between SGLT2 inhibitors and non-SGLT2 inhibitors groups. RESULTS: Eleven studies were included with 88,096 patients with confirmed cancer (49% male). Among the total population, 20,538 received SGLT2 inhibitors (age 61.68 ± 10.71), while 67,558 did not receive SGLT2 inhibitors (age 68.24 ± 9.48). The meta-analysis found that the patients who received SGLT2 inhibitors had a significantly lower mortality rate than those who did not receive SGLT2 inhibitors (RR 0.46, 95% CI 0.34 to 0.63, p-value < 0.0001). Similarly, the cancer-associated mortality rate was also lower (RR 0.29, 95% CI 0.27 to 0.30, p-value < 0.0001). Further analysis found that the SGLT2 inhibitor group had a lower rate of HF hospitalization, compared to controls (RR 0.44, 95% CI 0.27 to 0.70, p-value = 0.0007). Moreover, patients receiving SGLT2 inhibitors had a statistically lower rate of arrhythmia (RR 0.38, 95% CI 0.26 to 0.56, p-value < 0.0001). Finally, patients in the SGLT2 inhibitors group had a lower rate of adverse events (RR 0.51, 95% CI 0.42 to 0.62, p-value < 0.0001). CONCLUSIONS: SGLT2 inhibitors are effective in reducing mortality (all-cause and cancer-associated), HF hospitalization, arrhythmia, and drug adverse events in patients with cancer. If confirmed in future studies, these agents could be a potentially ideal candidate to prevent cardiotoxicity of cancer therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".