Identifying Predictors of Longitudinal Decline in the Level of Medical Care Received by Adult Survivors of Childhood Cancer: A Report from the Childhood Cancer Survivor Study
Bibliographic record
Abstract
Objectives Characterize longitudinal changes in the use of medical care in adult survivors of childhood cancer. Data Sources The Childhood Cancer Survivor Study, a retrospective cohort study of 5+ year survivors of childhood cancer. Study Design Medical care was assessed at entry into the cohort (baseline) and at most recent questionnaire completion. Care at each time point was classified as no care, general care, or survivor‐focused care. Data Collection There were 6,176 eligible survivors. Multivariable models evaluated risk factors for reporting survivor‐focused care or general medical care at baseline and no care at follow‐up; and survivor‐focused care at baseline and general care at follow‐up. Principal Findings Males (RR, 2.3; 95 percent CI 1.8–2.9), earning <$20,000/year (RR, 1.6; 95 percent CI 1.2–2.3) or ≤high school education (RR, 2.5; 95 percent CI 1.6–3.8 and RR 2.0; 95 percent CI 1.5–2.7 for RR 0.5; 95 percent CI 0.3–0.6) were less likely to report no care at follow‐up. Conclusions While the incidence of late effects increases over time for survivors, the likelihood of receiving survivor‐focused care decreases for vulnerable populations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".