Prosigna Risk of Recurrence score and intrinsic subtypes are associated with adjuvant anthracycline chemotherapy benefit in high-risk breast cancer
Bibliographic record
Abstract
NCIC-CTG MA.5 and DBCG 89D are symmetrically designed randomized trials comparing adjuvant cyclophosphamide, epirubicin, and fluorouracil with cyclophosphamide, methotrexate, and fluorouracil in high-risk breast cancer patients. In a joint analysis we evaluate the predictive value in terms of anthracycline benefit of molecular subtyping by PAM50. A statistically significant interaction ( P = 0.008) between continuous Risk of Recurrence (ROR) score and treatment regimen is evident, translating into a clear distinct treatment effect according to ROR score category with HR 0.51 for ROR score ≥ 72 and HR 1.10 for ROR score < 52 (P interaction = 0.004). The analysis provides evidence of the benefit from anthracycline in HER2-enriched subtype; for patients with discordance of HER2 subtype and clinical HER2 status, HER2-enriched subtype was predictive of anthracycline benefit whereas clinical HER2 positive status was not. Anthracycline-based adjuvant chemotherapy may safely be withheld for patients with a low ROR score while the benefit increases with increasing ROR score.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".