Cardiotoxicity in Pediatric Cancer Survivorship: Retrospective Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
Background: Improved survival rates in pediatric cancer have shifted focus to long-term effects of treatment, with cardiovascular complications emerging as a leading cause of morbidity and mortality. Understanding the patterns and predictors of cardiotoxicity is crucial for risk stratification, treatment optimization, and long-term care planning. Objective: This study investigated the prevalence, incidence, and risk factors of cardiotoxicity in pediatric cancer survivors using data from the Childhood Cancer Survivor Study. Methods: We conducted a retrospective cohort study of 24,938 five-year survivors of childhood cancer diagnosed between 1970 and 1999. Cardiovascular complications, including cardiomyopathy, coronary artery disease, valvular heart disease, and arrhythmias, were assessed through self-reported questionnaires and medical record review. Cox proportional hazards models were used to evaluate risk factors, and a prediction model was developed using multivariable logistic regression. Results: The cumulative incidence of any cardiovascular complication by 30 years postdiagnosis was 18.7% (95% CI 17.9%-19.5%). Significant risk factors included anthracycline exposure (hazard ratio 2.31, 95% CI 2.09-2.55 for doses ≥250 mg/m²), chest radiation (hazard ratio 1.84, 95% CI 1.66-2.05 for doses ≥20 Gy), older age at diagnosis, male sex, and obesity. A risk prediction model demonstrated good discrimination (C statistic 0.78, 95% CI 0.76-0.80). Survivors had a significantly higher risk of cardiovascular complications compared with sibling controls (odds ratio 3.7, 95% CI 3.2-4.2). Conclusions: Childhood cancer survivors face a substantial and persistent risk of cardiovascular complications. The identified risk factors and prediction model can guide personalized follow-up strategies and interventions. These findings underscore the need for lifelong cardiovascular monitoring and care in this population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it