Direct and indirect economic evaluation of upfront and sequential adjuvant treatment in postmenopausal women with breast cancer based on the BIG 1–98 trial
Bibliographic record
Abstract
6594 Background: The monotherapy arms of the BIG 1–98 trial established the clinical superiority of upfront letrozole (LET) relative to tamoxifen alone (TAM) but direct comparison of sequential TAM-LET, LET-TAM and upfront LET did not establish a clinically superior strategy. We undertook an economic evaluation to identify an economically preferred strategy based on the relative cost-effectiveness (CE) of TAM, LET, TAM-LET, and LET-TAM in terms of cost per quality-adjusted life year gained (QALYG). Methods: A state-transition model was developed to calculate cumulative costs and QALYs over a 25yr horizon for hypothetical cohorts of postmenopausal women with HR+ breast cancer undergoing adjuvant hormonal treatment. As the sequential arms were not directly compared to TAM alone, it was not possible to directly compare all strategies. As such, the analysis conducted direct within-arm comparisons and an indirect between-arm comparison. DFS endpoints and relative DFS benefit were derived from the monotherapy and sequential arms of BIG 1–98. Adverse events were not included as these have not yet been reported. Sensitivity analyses were conducted for the key parameters and assumptions, including the baseline recurrence risk and the duration of carry-over benefit. Costs and utility weights were derived from the literature. The analysis took a Canadian direct payer perspective and drug costs were based on 2008 Canadian average wholesale prices. Costs and outcomes were discounted at 3%. Results: In the monotherapy arms LET had a CE of $16,650 relative to TAM. In the sequential arms LET-TAM had superior QALYGs and cost savings relative to LET and TAM-LET. In economic terms, LET-TAM dominated LET and TAM-LET. In the indirect comparison, LET-TAM dominated LET and TAM-LET and had superior QALYGs at increased cost relative to TAM for a CE of $178. Conclusions: Direct comparisons confirm the economic favourability of LET relative to TAM and establish the dominance of LET-TAM over LET and TAM-LET. These indirect comparisons support the strong economic favourability of LET-TAM relative to TAM in the indirect comparison. In the absence of superior clinical outcomes, economic evaluation is a useful in suggesting a preferred strategy. 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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".