Cost disparities with age in the treatment of advanced non-small cell lung cancer (NSCLC) in Ontario, Canada.
Bibliographic record
Abstract
6629 Background: Previous studies noted an association between age and cost of care in NSCLC. The drivers of these cost disparities have not yet been fully examined. We conducted a cost analysis study examining the differences in, and drivers of, costs of NSCLC care across age groups in Ontario, Canada. Methods: We conducted a retrospective cohort study of patients diagnosed in Ontario from Apr 1, 2007 to Mar 30, 2014, who received palliative chemotherapy for stage IV NSCLC. Variables of interest were extracted from registry data linked by the Institute for Clinical Evaluative Sciences (ICES). The mean total cost of care including systemic therapy and supportive care, was calculated in 2015 CAD dollars by fiscal year of diagnosis. Results: Of all NSCLC cases diagnosed in Ontario (n = 37,786), 17,203 (45.5%) were de novo stage IV, of which 29.7% of patients received any chemotherapy for their disease (n = 5,113), and 281 patients are presumed alive. In this population, median age was 65 to 69 years, 51.9% were male, 43.5% were adenocarcinomas, and 25.1% received second line chemotherapy. After adjusting for comorbidities, income, gender, year of diagnosis, and rural versus urban living, the average lifetime costs per patient remains significantly inversely related to age (p < 0.001). Belonging to the highest income quintile (p = 0.006) and being diagnosed in more recent years (p < 0.001) contributes significantly to increasing overall healthcare costs. Elderly patients (80+) cost less (71%) and have shorter survival time (HR of death 1.28, 95% C.I. 1.10 to 1.50) compared to younger patients (≤45 years old). Accounting for longer survival in younger patients, the youngest group still incur a higher cost per day alive than other age groups ($471/day in ≤45 group, $301/day in > 85 group). Hospitalization accounts for ~30% of total cost in both age groups. Chemotherapy accounts for 1% of total health care costs amongst the elderly (80+) age group and 10% of costs in ≤45 group. Conclusions: Our study shows that, despite everyone receiving systemic therapy in this patient population, younger patients incur significantly higher costs than elderly patients with advanced NSCLC, both before and after adjusting for survival. While hospitalization accounts for the biggest component of total costs, patients with high income and more recent years of diagnosis drive the higher costs of care, and chemotherapy remains a driver of higher costs amongst younger patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".