Baseline Characteristics of Parents Enrolled in Children's Oncology Group Study ACCL20N1CD: Financial Toxicity During Treatment for Pediatric Acute Lymphoblastic Leukemia in the United States
Bibliographic record
Abstract
BACKGROUND: Costs to parents and associated financial distress may contribute to observed health disparities in pediatric oncology. We describe financial distress in a cohort of parents with children newly diagnosed with acute lymphoblastic leukemia (ALL) and identify factors contributing to high financial distress. PROCEDURES: Settings were 28 Children's Oncology Group practices in the National Cancer Institute Community Oncology Research Program. We included English- or Spanish-speaking parents of children with newly diagnosed ALL. Analyses focused on baseline surveys completed by parents during their child's ALL induction therapy. Survey items asked about socio-demographics, household material hardships, financial burden, financial distress, and financial coping behaviors. RESULTS: The cohort included 104 parents. Most were female (87; 83.7%), White (68; 65.4%), non-Hispanic (50; 48.1%), and paid for their child's care with Medicaid or CHIP (60; 57.7%). Financial burden totaled greater than 15% of monthly gross household income for half (54, 51.5%), and 45 (43%) indicated high financial distress (score 1-4). Prevalent coping behaviors with health implications included cutting back on groceries (62, 59.6%) or other necessities (61, 58.7%). Parents who had poverty-level income (p = 0.0009), paid with Medicaid or CHIP (OR 3.0 [CI: 1.26, 7.13], p = 0.01), were unemployed (OR 2.5 [CI: 1.1, 5.7], p = 0.04), or lived where more than 50% of residents had socioeconomic disadvantages (OR 3.0 [CI: 1.13, 8.05], p = .03) were more likely to indicate high financial distress than others. CONCLUSIONS: During their child's ALL induction therapy, sizeable proportions of parents exhibited high financial burdens, high levels of financial distress, and multiple financial coping behaviors with health implications.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".