Looking beyond cancer for cabozantinib-induced cardiotoxicity: evidence of absence or absence of evidence?
Bibliographic record
Abstract
The advent of molecular targeted therapy has transformed the scape of medical oncology in the past decades—patients previously deemed terminal now have more treatment options proven to extend survival. An example is renal cell carcinoma (RCC); given its myriad clinical presentation, a significant proportion of patients have locally advanced or metastatic disease at the time of diagnosis. Historically, treatment options for such patients were limited and their prognosis grim. In the past years, however, vascular endothelial growth factor (VEGF) inhibitors and tyrosine kinase inhibitors (TKIs), such as bevacizumab, sunitinib and pazopanib, have been shown to improve progression-free survival, although there have been increasing reports of drug cardiotoxicity including hypertension and heart failure (1-5). As a result, there is a growing need for better patient selection, prevention and monitoring of cardiotoxicity during treatment, as well as exploration of alternative safer agents.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".