Sodium-Glucose Cotransporter 2 Inhibitors During Cancer Therapy: Benefits, Risks, and Ongoing Clinical Trials
Bibliographic record
Abstract
PURPOSE OF REVIEW: The goal of this paper is to summarize the data pertaining to the use of sodium-glucose cotransporter-2 inhibitors (SGLT-2i) for the prevention of cardiotoxicity in patients receiving anthracyclines for cancer treatment. We discuss the potential efficacy of this class of medications, incorporating insights from existing literature and ongoing studies. RECENT FINDINGS: SGLT2i are a class of medications which were initially developed for treatment of Type 2 diabetes and later extended to treat heart failure with reduced and preserved ejection fraction regardless of diabetes status. There remains a need for effective and safe treatments to preventing cardiotoxicity in anthracycline-treated patients. It has been proposed that SGLT2i may provide protection against the cardiotoxic effects of anthracyclines. Some of the proposed mechanisms include beneficial metabolic, neurohormonal, and hemodynamic effects, renal protection, as well as a decrease in inflammation, oxidative stress, apoptosis, mitochondrial dysfunction and ion homeostasis. There is emerging evidence from basic science and observational studies that SGLT2i may play a role in the prevention of chemotherapy-induced cardiotoxicity. Randomized controlled trials are needed to conclusively determine the role of SGLT2 inhibitors as a cardioprotective therapy in patients receiving anthracyclines for the treatment of cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".