Cost-effectiveness (CE) analysis of CHOP and rituximab for diffuse large B-cell lymphoma (DLBCL) in British Columbia (BC)
Bibliographic record
Abstract
6623 Background: The BC Cancer Agency (BCCA) provides province-wide, population-based care. Outcomes are monitored to verify therapeutic effectiveness and justify funding for systemic treatment policies. The CE of rituximab with CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) (CHOP-R) for DLBCL was compared to its predecessor, CHOP alone. Methods: This was a pragmatic population-based CE analysis based on the original cohort of advanced DLBCL patients described by Sehn et al (JCO 2005) who received either CHOP or CHOP-R between Sept 1999 and Aug 2002 (18-months pre and post availability of rituximab in BC) according to standard BCCA treatment policy at the time. The primary endpoint was CE in terms of life-expectancy (LE) at a median follow-up of 4 years (cost-per-life-year-gained). Costs were incorporated into a decision analysis including primary systemic therapy and downstream chemotherapy, radiotherapy, and stem-cell transplant (SCT). Actual incidence of each downstream therapy was converted to a probability for each group. Downstream therapy costs were then multiplied by these probabilities and added to the respective primary treatment costs. The CE analysis took the BCCA perspective which includes all direct costs for active cancer treatment, and hospitalization for SCT, but not ambulatory supportive care. Sensitivity analyses varying LE to the extremes of its 95% CI, modeling out to 15 years and discounting at 0, 3, and 5% were performed. Results: 292 patients were included and categorized to treatment received: 148 CHOP and 144 CHOP-R (median follow- up 5.4 and 4 years respectively). LE to 4 years was 30.18 months for CHOP and 39.44 for CHOP-R. OS at 4 years was 48.8% and 70.1% for CHOP and CHOP-R respectively (p<0.0001) Respective costs of primary and downstream therapy were $4,682 and $7,198 for CHOP versus $26,366 and $6,228 for CHOP-R. The incremental CE ratio at 4 years median follow-up was $26,844 CDN per life year gained. Results were robust across univariate sensitivity analyses conducted. Conclusions: At 4 years median follow-up, CHOP-R improves LE and appears to be economically attractive at conventional thresholds. CE is an increasingly useful tool for the BCCA in making decisions about new cancer therapies. No significant financial relationships to disclose.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".