Prevalence of carotid ultrasound screening in survivors of childhood cancer: A report from the Childhood Cancer Survivor Study
Bibliographic record
Abstract
INTRODUCTION: Many childhood cancer survivors are at risk for cardiovascular disease and stroke. The North American Children's Oncology Group long-term follow-up guidelines recommend carotid ultrasound in cancer survivors 10 years after neck radiation therapy (RT) ≥40 Gy. The use of carotid ultrasound in this population has not been described. METHODS: Survivors of childhood cancer diagnosed 1970-1999 (N = 8693) and siblings (N = 1989) enrolled in the Childhood Cancer Survivor Study were asked if they had ever had a carotid ultrasound. Prevalence of carotid ultrasound was evaluated. Prevalence ratios (PR) and 95% confidence intervals (CIs) were evaluated in multivariate Poisson regression models. RESULTS: Among participants with no reported cardiovascular condition, prevalence of carotid ultrasound among survivors with RT ≥40 Gy to the neck (N = 172) was 29.7% (95% CI, 22.5-36.8), significantly higher than those with <40 Gy (prevalence 10.7%; 95% CI, 9.9%-11.4%). Siblings without a cardiovascular condition (N = 1621) had the lowest prevalence of carotid ultrasound (4.7%; 95% CI, 3.6%-5.7%). In a multivariable models among survivors with no reported cardiovascular condition and RT ≥40 Gy to the neck, those who were over age 50 (vs. 18-49) at follow-up (PR = 1.82; 95% CI, 1.09-3.05), with a history of seeing a cancer specialist in the last 2 years (PR = 2.58; 95% CI, 1.53-4.33), or having a colonoscopy (PR = 2.02; 95% CI, 1.17-3.48) or echocardiogram (PR = 6.42; 95% CI, 1.54-26.85) were more likely to have had a carotid ultrasound. CONCLUSION: Many survivors do not undergo carotid ultrasound despite meeting existing guidelines. Health care delivery features such as having seen a cancer specialist or having other testing are relevant.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".