Examining the Medical Resource Utilization and Costs of Relapsed and Refractory Chronic Lymphocytic Leukemia in Ontario
Bibliographic record
Abstract
PURPOSE: The purpose of the present study was to collect medical resource utilization data and costs in Ontario for the management of patients with relapsed or refractory chronic lymphocytic lymphoma (cll) who have undergone at least 1 treatment course and have been stratified by Rai staging. METHODS: This retrospective longitudinal cohort study, conducted by chart review, analyzed anonymized patient records from two cancer centres in Ontario. Comprehensive records of 86 patients meeting the inclusion criteria were used to obtain resource utilization, which, multiplied by unit costs, were used to determine overall and mean costs. Descriptive statistics are presented for patient demographics, medical resource utilization, and costing data. RESULTS: The total cost for the cohort was $2.2 million over a mean follow-up period of 4.7 years. The mean total cost per patient (regardless of follow-up) was $25,736. In terms of Rai staging, overall mean costs were highest for stage iv patients. Almost 50% of the total cost was attributable to cll treatments, among which fludarabine-based treatments had the highest utilization. CONCLUSIONS: For this Canadian cll cohort, medical resource utilization and costs were determined to be $2.2 million, with cll treatments accounting for about half the cost. Costs generally increased with Rai stage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".