Cost Effectiveness of tac versus fac in Adjuvant Treatment of Node-Positive Breast Cancer
Bibliographic record
Abstract
BACKGROUND: This economic analysis aimed to determine, from the perspective of a Canadian provincial government payer, the cost-effectiveness of docetaxel (Taxotere: Sanofi-Aventis, Laval, QC) in combination with doxorubicin and cyclophosphamide (TAC) compared with 5-fluorouracil, doxorubicin, and cyclophosphamide (FAC) following primary surgery for breast cancer in women with operable, axillary lymph node-positive breast cancer. METHODS: A Markov model looking at two time phases-5-year treatment and long-term follow-up-was constructed. Clinical events included clinical response (based on disease-free survival and overall survival) and rates of febrile neutropenia, stomatitis, diarrhea, and infections. Health states were "no recurrence," "locoregional recurrence," "distant recurrence," and "death." Costs were based on published sources and are presented in 2006 Canadian dollars. Model inputs included chemotherapy drug acquisition costs, chemotherapy administration costs, relapse and follow-up costs, costs for management of adverse events, and costs for granulocyte colony-stimulating factor (G-CSF) prophylaxis. A 5% discount rate was applied to costs and outcomes alike. Health utilities were obtained from published sources. RESULTS: For TAC as compared with fac, the incremental cost was $6921 per life-year (LY) gained and $6,848 per quality-adjusted life-year (QALY) gained. The model was robust to changes in input variables (for example, febrile neutropenia rate, utility). When G-CSF and antibiotics were given prophylactically before every cycle, the incremental ratios increased to $13,183 and $13,044 respectively. CONCLUSIONS: Compared with FAC, TAC offered improved response at a higher cost. The cost-effectiveness ratios were low, indicating good economic value in the adjuvant setting of node-positive breast cancer patients.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".