Demographic characteristics and cost of treatment among oncology patients in a publicly funded system, the Ontario Trillium Drug Program: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to characterize the demographic characteristics and investigate the cost of a publicly funded system, the Ontario Trillium Drug Program (TDP), for an oncology patient population. METHODS: We ascertained all TDP claims between April 1997 and December 2016 from the Ontario Drug Benefit database to assess use and cost. Each drug was classified as a cancer treatment drug, cancer supportive therapy drug or noncancer drug. We also identified a cohort of patients with cancer with least 1 TDP claim, for whom we examined demographic and claims-related characteristics. RESULTS: Over the study period, 50 975 293 TDP claims totalling $4.8 billion were made. Although the proportion of cancer claims among all TDP claims remained constant between 1997 and 2016, the total annual cost of cancer treatment drugs increased nearly 40-fold. Imatinib and lenalidomide together accounted for nearly half of the cost of all cancer treatment drugs. We identified a cohort of 49 892 patients with cancer, of whom 18 631 (37.3%) were enrolled in the TDP before their cancer diagnosis and 31 261 (62.7%) were enrolled after their diagnosis. The former were more likely than the latter to be in lower income quintiles and to have more chronic conditions. Significant differences were also found in the distribution of cancer diagnoses between the 2 groups. INTERPRETATION: In the TDP, use increased over time and differed across cancer diagnoses and drugs. These results have public health and policy implications as antineoplastic drug costs continue to rise and place a burden on patients.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".