Impact of the 21-Gene Recurrence Score Assay on Treatment Decisions and Cost in Patients with Node-Positive Breast Cancer: A Multicenter Study in Quebec
Bibliographic record
Abstract
BACKGROUND: The 21-gene Breast Recurrence Score (RS) assay, "the assay", has led to a paradigm shift for patients with hormone receptor-positive, node-negative early breast cancer and is emerging as an important tool to assist physician-patient decisions in foregoing chemotherapy in node-positive patients. We wanted to better understand the impact of the RS assay in node-positive patients upon physician treatment decisions and treatment cost in Quebec, Canada. PATIENTS AND METHODS: We conducted a multicenter, prospective observational trial for Estrogen/Progesterone Receptor (ER/PR)- positive, Human Epidermal Growth Factor Receptor 2 (HER2)-negative breast cancer patients with 1-3 positive lymph nodes. Physicians completed a questionnaire indicating treatment choice prior to and post availability of RS results. The primary endpoint was change in the physician's recommendation for chemotherapy prior to and post assay results. Secondary endpoints included change in physician's expressed level of confidence, and changes in estimated cost of recommended treatments prior to and post assay results. RESULTS: For the entire cohort, physician recommendation for chemotherapy was reduced by an absolute 67.1% by knowledge of the RS assay result (P < .0001). Physician recommendation of chemotherapy was decreased by 75.9% for patients RS result <14 (P < .0001); and 67.5% for patients with RS result 14-25 (P < .0001). Changes in treatment recommendations were associated with an overall reduction in cost by 73.7% per patient, and after incorporating the cost of the RS test, a cost benefit of $823 CAN at 6-month follow-up. CONCLUSION: Altogether, we established that the assay led to a two-third reduction in the use of chemotherapy, and was a cost-effective approach for hormone receptor-positive, node-positive 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".