Total and cancer-attributable phase-based costs for childhood cancer care: A population-based study in British Columbia, Canada.
Bibliographic record
Abstract
11 Background: Childhood cancer presents unique issues regarding treatment, late effects, and long-term survival, but few studies have reported costs. Childhood cancer-specific costs are useful for economic evaluation and planning care. This study estimates total and cancer-attributable (net) medical costs for a population-based childhood cancer cohort in British Columbia, Canada, by phase of care. Methods: Patients diagnosed with cancer at ages 91 days to 14 years between 1995-2009 were identified from the British Columbia Cancer Registry, and followed to December 31, 2010. Data were linked with clinical and provincial administrative healthcare databases covering all medically-necessary costs. Total resource-specific costs (Canadian $ 2012) were estimated overall and for patients with leukemia, lymphoma, central nervous system (CNS), and “other” cancers. Net costs were calculated by subtracting healthcare costs for propensity-score-matched provincial samples of children without cancer from cancer patient costs. Results: Of the 1,440 cases, 33% had leukemia, with 23% CNS tumours, 10% lymphoma, 34% other cancers; 93% survived >=1 year. Overall pre-diagnosis mean costs per patient were $4,633, of which $4,555 was attributable to the cancer. Overall initial (first-year) mean costs were $97,780 ($97,254). Overall continuing phase mean costs were $12,441 ($12,006). Overall final year of life mean costs were $284,201 ($283,652). Cancer types with highest costs were CNS (pre-diagnosis), leukemia (first-year), “other” cancers (continuing), and lymphoma (end-of-life). Virtually all inpatient hospitalizations were cancer-related, representing ~41% of pre-diagnosis, ~71% of first-year, ~57% of continuing, and ~73% of end-of-life costs. Conclusions: Management of childhood cancer is costly, and is higher than for adolescent cancer in all phases of care, reflecting greater morbidity and treatment complexity. Hospitalizations were the largest driver of costs in all post-diagnosis phases of care. Costs in the continuing phase, including surveillance and care for late effects, were 13% of first-year phase costs.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".