Review of the Clinical Studies Using the 21-Gene Assay
Bibliographic record
Abstract
PURPOSE: A major challenge in treating early-stage hormone receptor (HR)(+) breast cancer is selecting women who, after initial surgery, do not require chemotherapy. Better prognostic and predictive tests are needed. The 21-gene assay is the only widely commercially available gene signature that can be performed on formalin-fixed paraffin-embedded tissue. METHODS: We conducted a review of the literature supporting the prognostic and predictive ability of the 21-gene assay in HR(+) node-negative and node-positive breast cancer patients in chemotherapy-/endocrine-treated and untreated populations. We considered: (a) How accurate is the recurrence score (RS) as a prognostic factor for distant recurrence? (b) How accurate is the RS as a predictive factor for benefit from systemic therapy? (c) How does the RS compare with other prognostic/predictive factors such as tumor size, tumor grade, patient age, and integrated decision aids such as Adjuvant! Online? (d) How do patients and physicians view the 21-gene assay? (e) What are the cost implications of the 21-gene assay? RESULTS: The 21-gene assay: (a) provided accurate risk information; (b) predicted response to cyclophosphamide, methotrexate, and 5-fluorouracil and to cyclophosphamide, doxorubicin, and 5-fluorouracil chemotherapy; (c) added additional information to traditional biomarkers; (d) was viewed positively by both physicians and patients; and (e) fell within the cost-effectiveness values in North America. CONCLUSION: This assay may be offered to patients with node-negative HR(+) breast cancer to assist in adjuvant treatment decisions. Data are accumulating to support the use of the 21-gene assay in HR(+) node-positive patients.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".