Economic evaluation of two adjuvant chemotherapy regimens in lung cancer: Vinorelbine and cisplatin versus paclitaxel and carboplatin
Bibliographic record
Abstract
6076 Background: Adjuvant chemotherapy in lung cancer has become the new standard of care. Assuming comparable survival and quality of life among acceptable chemotherapy options, an economic evaluation becomes pivotal in choosing the preferred regimen. Methods: A cost minimization analysis was performed in Canadian dollars of the adjuvant chemotherapy regimens used in the NCIC BR10 and CALGB 9633 trials; VP (Vinorelbine and Cisplatin) and PC (Paclitaxel and Carboplatin), respectively. We examined the direct costs of chemotherapy drug acquisition, supportive medications, laboratory investigations, and health resources utilization based at the Nova Scotia Cancer Center. We also estimated the indirect costs incurred by patients, including the potential loss of income based on the average provincial wages and participation rates. The primary analysis assumes uncomplicated cycles and complete drug delivery. Sensitivity analyses to different factors were performed. Results: Compared to the VP regimen, the PC regimen is associated with a higher direct cost, principally reflecting a higher chemotherapy drug acquisition cost (difference: $3749 / patient) but a less resources utilization cost (difference: $1091/patient). This was offset by a higher indirect cost in the VP regimen, which mounted up to an additional $2629/patient with 100% participation rate, reflecting a higher opportunity cost with this longer chemotherapy schedule. Conclusions: The PC regimen is associated with a higher direct cost compared to the VP regimen; principally reflecting a higher drug acquisition cost. However, the total costs were offset by other factors such as indirect patient costs. When making a decision about adjuvant chemotherapy choices in lung cancer, both the direct and indirect costs incurred should be considered. Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Bristol-Myers Squibb
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".