Cardiovascular Toxicity of Multi-Tyrosine Kinase Inhibitors in Advanced Solid Tumors: A Population-Based Observational Study
Bibliographic record
Abstract
BACKGROUND: Treatment with small molecule tyrosine kinase inhibitors (TKIs) has improved survival in many cancers, yet has been associated with an increased risk of adverse events. Warnings of cardiovascular events are common in drug labels of many TKIs. Despite these warnings, cardiovascular toxicity of patients treated with TKIs remains unclear. Here, we evaluate the cardiovascular outcomes of advanced cancer patients treated with small molecule tyrosine kinase inhibitors. METHODS: A population based cohort study was undertaken involving adults aged >18 years in Ontario, Canada, diagnosed with any advanced malignancy between 2006 and 2012. Data were extracted from linked administrative governmental databases. Adults with advanced cancer receiving TKIs were identified and followed throughout the time period. The main outcomes of interest were rates of hospitalization for ischemic heart disease (acute myocardial infarction and angina) or cerebrovascular accidents and death. RESULTS: 1642 patients with a mean age of 62.5 years were studied; 1046 were treated with erlotinib, 166 with sorafenib and 430 with sunitinib. Over the 380 day median follow-up period (range 6-1970 days), 1.1% of all patients had ischemic heart events, 0.7% had cerebrovascular accidents and 72.1% died. Rates of cardiovascular events were similar to age and gender-matched individuals without cancer. In a subgroup analysis of treatment patients with a prior history of ischemic heart disease, 3.3% had ischemic heart events while 1.2% had cerebrovascular accidents. CONCLUSIONS: TKIs do not appear to increase the cause-specific hazard of ischemic heart disease and cerebrovascular accidents compared to age and gender-matched individuals without advanced cancer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".