Chronic Health Conditions and Academic Achievement: A Childhood Cancer Survivor Study Report
Bibliographic record
Abstract
PURPOSE: To examine associations between special education, chronic health conditions (CHCs), and college graduation in survivors of childhood cancer and their siblings. METHODS: Childhood Cancer Survivor Study participants included 23,082 5-year survivors (53.7% male; median [IQR] age at diagnosis, 6 [3-13] years; age at evaluation, 31.0 [24-39] years; treated between 1970 and 1999) and 5,037 siblings (47.7% male; 36.0 [28-44] years at evaluation). Special education use, reasons for special education, CHCs, and college graduation were self-reported. Primary cancer diagnosis and treatment exposures were abstracted from medical records. Comparisons between survivors and siblings were made using chi-square statistics; demographic and treatment factors associated with outcomes were examined using modified Poisson regression models. RESULTS: 8.6%; relative risk [RR], 2.55 [95% CI, 2.32 to 2.80]). Of those survivors and siblings who had special education services, use was highest between kindergarten and fifth grade (64.4% of survivors and 71.9% of siblings in kindergarten-fifth grade, 14.4% of survivors and 12.5% of siblings in sixth-eighth grade, and 9.2% of survivors and 9.0% of siblings in ninth-12th grade), and primarily attributable to learning and concentration problems. Despite receiving special education, survivors were less likely to graduate college compared with siblings requiring special education (RR, 0.76 [95% CI, 0.66 to 0.88]). Risk for not graduating college included history of CNS tumor (RR, 1.47 [95% CI, 1.40 to 1.55]), cranial irradiation (20-29 Gy, RR, 1.16 [95% CI, 1.09 to 1.25]; 30-49 Gy, RR, 1.37 [95% CI, 1.26 to 1.49]; ≥50 Gy, RR, 1.35 [95% CI, 1.28 to 1.42]), or the presence of a severe, disabling or life-threatening CHC (Common Terminology Criteria for Adverse Events grade 3-4, RR, 1.15 [95% CI, 1.07 to 1.24]). CONCLUSION: Cognitive problems and CHCs increase risk for not graduating college; these problems are not alleviated by special education.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".