Clinical and Genomic Risk for Late Breast Cancer Recurrence and Survival
Bibliographic record
Abstract
BACKGROUND: The 21-gene recurrence score (RS) assay (Oncotype DX) is used to guide adjuvant chemotherapy use for patients with hormone receptor-positive, HER2 (human epidermal growth factor receptor 2)-negative, axillary node-negative breast cancer. Its role, however, in providing prognostic information for late distant recurrence when added to clinicopathologic prognostic factors is unknown. METHODS: A patient-specific meta-analysis including 10,004 women enrolled in three trials was updated using extended follow-up data from TAILORx, integrating the RS with histologic grade, tumor size, and age at surgery for the RSClin tool. Cox models integrating clinicopathologic factors and the RS were compared by using likelihood ratio (LR) tests. External validation of prognosis for distant recurrence in years 0 to 10 and 5 to 10 was performed in an independent cohort of 1098 women in a real-world registry. RESULTS: RSClin provided significantly more prognostic information than either the clinicopathologic factors (ΔLR chi-square, 86.2; P<0.001) or RS alone (ΔLR chi-square, 131.0; P<0.001). The model was prognostic in an independent cohort for distant recurrence by 10 years after diagnosis (standardized hazard ratio, 1.56; 95% confidence interval, 1.25 to 1.94), was associated with late distant recurrence risk between 5 and 10 years after diagnosis (standardized hazard ratio, 1.78; 95% confidence interval, 1.25 to 2.55), and approximated the observed 10-year distant recurrence risk (Lin concordance, 0.87) and 5- to 10-year distant recurrence risk (Lin concordance, 0.92). CONCLUSIONS: The 21-gene RS is prognostic for distant recurrence and overall survival in early breast cancer. A model integrating the 21-gene RS and clinicopathologic factors improved estimates of distant recurrence risk compared with either used individually and stratified late distant recurrence risk. (Funded by the National Cancer Institute, National Institutes of Health [U10CA180820, U10CA180794, UG1CA189859, U10CA180868, and U10CA180822] and others.).
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".