Effect of Population Socioeconomic and Health System Factors on Medical Care of Childhood Cancer Survivors: A Report from the Childhood Cancer Survivor Study
Bibliographic record
Abstract
PURPOSE: To determine the independent contribution of population socioeconomic and health system factors on childhood cancer survivors' medical care and screening. METHODS: 7899 childhood cancer survivors in the United States and Canada enrolled in the Childhood Cancer Survivor Study (CCSS). Population-level factors were derived from U.S. Area Health Resource File or 201 Canadian Census. Health service utilization and individual-level factors were self-reported. Multivariable logistic regression was used to calculate the effect of population factors on medical care (any care vs. no care; risk-based care vs. general care) and indicated echocardiogram or mammogram, adjusting for individual sociodemographic and health status. RESULTS: After adjusting for individual factors, population factors had a nominal impact on childhood cancer survivors' medical care and screening. Higher population median income was associated with risk-based survivor-focused care versus general care (odds ratio [OR] 1.05, 95% confidence interval [CI], 1.01-1.09) among all participants, but not among U.S. residents only (OR 1.03, 95% CI, 0.99-1.07). For U.S. residents, the number of CCSS centers within the geographic area was associated with greater odds of receiving risk-based survivor-focused medical care (OR 1.12, 95% CI, 1.04-1.20). Areas with higher median income had higher rates of echocardiogram screening among survivors at risk of cardiomyopathy (for every $10,000 increase in median income, there is a 12% increase in odds of echocardiogram screening; 95% CI 1.05-1.20). A positive relationship was identified between greater number of physicians and surgeons in the county of residence and recommended echocardiogram (for every additional 1000 physicians and surgeons: OR 1.12, 95% CI, 1.01-1.23). We found no association between population-level factors and mammography screening. CONCLUSIONS: Population socioeconomic disparities moderately affect childhood cancer survivors' risk-based medical care and screening after accounting for individual sociodemographic and health factors.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".