Cost‐effectiveness of switching to exemestane versus continued tamoxifen as adjuvant therapy for postmenopausal women with primary breast cancer
Bibliographic record
Abstract
BACKGROUND: Sequential tamoxifen/exemestane therapy reportedly improves disease-free survival in women with primary breast cancer compared with continued tamoxifen therapy. The objective of the current study was to assess the cost-effectiveness of switching to exemestane after 2 to 3 years of tamoxifen versus continued tamoxifen in postmenopausal women with primary breast cancer for a total of 5 years of adjuvant therapy. METHODS: A Markov model based on the Intergroup Exemestane Study (IES) population compared switching to exemestane versus continued tamoxifen for 2.5 years of therapy and 5 years of postadjuvant therapy follow-up. Disease progression and hazards ratios (HR) for recurrence and survival were determined from datasets (IES and the Surveillance, Epidemiology, and End Results program of the National Cancer Institute) and from the published literature. An expert panel validated treatment patterns, outcomes, and resource utilization. Direct medical costs were included based on published sources. Cost-effectiveness ratios were determined, and extensive sensitivity analyses were conducted. RESULTS: Exemestane was found to be more effective than tamoxifen alone with regard to disease-free survival (2.6% absolute improvement), life-years gained (0.1028 LY), and quality-adjusted life-years gained (0.1195 QALY), at an additional cost of 2,889 Can dollars per person over 7.5 years. Incremental cost-effectiveness ratios were 28,119 Can dollars/LY gained and 24,185 Can dollars/QALY gained. The model was most sensitive to distant recurrence HR but was robust to variations in clinical, cost, and utility parameters. CONCLUSIONS: Switching to adjuvant exemestane after 2 to 3 years of tamoxifen is cost-effective in postmenopausal women with primary breast cancer.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".