La industria agroalimentaria en Aragón: competitividad y estrategias empresariales
Bibliographic record
Abstract
Gene expression profiling (GEP) testing using 12-gene recurrence score (RS) assay (EndoPredict®), 58-gene RS assay (Prosigna®), and 21-gene RS assay (Oncotype DX®) is available to aid in chemotherapy decision-making when traditional clinicopathological predictors are insufficient to accurately determine recurrence risk in women with axillary lymph node-negative, hormone receptor-positive, and human epidermal growth factor-receptor 2-negative early-stage breast cancer. We examined the cost-effectiveness of incorporating these assays into standard practice. A decision model was built to project lifetime clinical and economic consequences of different adjuvant treatment-guiding strategies. The model was parameterized using follow-up data from a secondary analysis of the Anastrozole or Tamoxifen Alone or Combined randomized trial, cost data (2017 Canadian dollars) from the London Regional Cancer Program (Canada) and secondary Canadian sources. The 12-gene, 58-gene, and 21-gene RS assays were associated with cost-effectiveness ratios of $36,274, $48,525, and $74,911/quality-adjusted life year (QALY) gained and resulted in total gains of 379, 284.3, and 189.5 QALYs/year and total budgets of $12.9, $14.2, and $16.6 million/year, respectively. The total expected-value of perfect information about GEP assays' utility was $10.4 million/year. GEP testing using any of these assays is likely clinically and economically attractive. The 12-gene and 58-gene RS assays may improve the cost-effectiveness of GEP testing and offer higher value for money, although prospective evidence is still needed. Comparative field evaluations of GEP assays in real-world practice are associated with a large societal benefit and warranted to determine the optimal and most cost-effective assay for routine use.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".