Assessing the Real-World Cost-Effectiveness of Adjuvant Trastuzumab in HER-2/neu Positive Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Among women with surgically removed, high-risk HER-2/neu-positive breast cancer, trastuzumab has demonstrated significant improvements in disease-free and overall survival. The objective of this study is to evaluate the cost-effectiveness of the currently recommended 12-month adjuvant protocol of trastuzumab using a Markov modeling approach and real-world cost data. METHODS: A 10-health-state Markov model tracked patients' quarterly transitions between health states in the local and advanced states of breast cancer. Clinical data were obtained from the joint analysis of the National Surgical Adjuvant Breast and Bowel Project and North Central Cancer Treatment Group, as well as from the metastatic study conducted by Norum et al. Clinical outcomes were adjusted for quality of life using utility estimates published in a systematic review. Real cost data were obtained from the British Columbia Cancer Agency and were evaluated from a payer perspective. Costs and utilities were discounted at 5% per year, respectively, for a 28-year time horizon. RESULTS: In the base case analysis, treatment with a 12-month adjuvant trastuzumab regimen resulted in a gain of 1.38 quality-adjusted life years or 1.17 life years gained at a cost of $18,133 per patient. Thus, the cost per QALY gained for the base case is $13,095. Cost per LYG is $15,492. CONCLUSIONS: Over the long term, treatment of HER-2/neu mutation positive breast cancer with a 12-month protocol of trastuzumab in the adjuvant setting is predicted to be cost-effective in a Canadian context.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".