The potential economic impact of the 21-gene recurrence score: Guided chemotherapy in a population-based cohort with node-negative and node-positive early-stage breast cancer.
Bibliographic record
Abstract
201 Background: The 21-gene recurrence score (Oncotype DX: RS) appears to augment clinical-pathological prognostication and predicts adjuvant chemotherapy (chemo) benefits in patients with node-negative (N-) and node-positive (N+) hormone-receptor positive early-stage breast cancer. Economic analyses suggest that RS-guided chemo is a cost-effective strategy in N- breast cancer, but no evaluations were reported for N+ disease based on pre RS chemo utilization in clinical practice. We examined the cost-utility (CU) of a RS-guided chemo strategy, compared to current practice without RS in a population based cohort, in N- and N+ early-stage breast cancer. Methods: A generic state-transition model was developed to compute cumulative costs and quality-adjusted life years (QALY) over a 25-year horizon for patients with hormone-receptor positive early-stage breast cancer considered for chemo. We examined outcomes with and without chemo in RS-untested cohorts and in those with low, intermediate and high RS based on the reported prognostic and predictive impact of the RS. Chemo utilizations (current vs RS-guided), costs and utilities were derived from a Nova Scotia population based cohort, local resources and the literature. Sensitivity analyses were conducted for key model assumptions/parameters. Results: RS-guided chemo strategy is associated with incremental costs and QALY gains compared to chemo with no RS testing in both N- and N+ patients. The resultant CU ratios are $17,141/QALY and $5,772/QALY for N- and N+ disease, respectively. These CU ratios are well below commonly quoted thresholds and were most sensitive to RS-distribution, upfront chemo costs, chemo utilization rates and relative benefits of chemo in various RS-strata. Conclusions: RS-guided chemo in a population based cohort appears to be a cost-effective strategy, compared to chemo with no RS testing, in N- and N+ early-stage 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".