Economic evaluation of adjuvant chemotherapy in Stage III (SIII) colon cancer: Capecitabine versus 5FU/LV
Bibliographic record
Abstract
6046 Background: Adjuvant chemotherapy for SIII colon cancer is an accepted standard of care. Oral Capecitabine (C) has been shown to be at least equivalent and possibly superior to 5FU/LV (F) with a superior relapse free survival (RFS). This new option is associated with a higher drug cost. An economic analysis was undertaken to compare these two alternatives. Methods: A cost minimisation analysis was performed in Canadian $ ($) using C and F given as per the X-ACT (X) trial. The direct costs including chemotherapy drug acquisition, supportive medications, laboratory investigation and health resources utilisation were examined based in Nova Scotia. Indirect costs included travel and opportunity cost based on the average provincial wage and participation rates. Complete drug delivery was assumed. A direct payer perspective was used. A cost-effectiveness (CE) model was also constructed to estimate the required lower risk of cancer recurrence for C to be cost effective compared to F at a commonly used CE threshold. The Markov model developed used a hypothetical cohort of 1,000 patients with SIII colon cancer and projected costs and outcomes over 5 years (discounted 3% and in $2,005). All recurrences were modeled to death. Recurrence rates, median survival with recurrent disease, costs and utility scores were derived from the literature. Estimates of background mortality without recurrence were obtained from Canadian Life Tables. Sensitivity analysis (SA) was performed using a range of recurrence risk hazard ratios (HR) including that reported in the X trial. Results: Compared to F, C is associated with higher direct costs, principally reflecting the higher drug cost (difference: $5,589/patient) but less resources utilisation cost (difference: - $1,804/patient). The total indirect costs favour C (difference: - $2,464/patient). For C to be potentially CE compared to 5FU/LV, a ≥ 9% lower relative recurrence risk (HR = 0.91) with C would be required. At the reported RFS HR 0.86, the CE of C relative to F is $15,844 per disease free survival years gained and $22,097 per quality adjusted life years gained. Conclusions: C has more direct costs but has indirect cost savings. It has the potential to be cost effective as seen in the SA and is a CE alternative to F at the HR for RFS reported in the X trial. 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".