Race, Ethnicity, and Clinical Outcomes in Hormone Receptor-Positive, HER2-Negative, Node-Negative Breast Cancer in the Randomized TAILORx Trial
Bibliographic record
Abstract
BACKGROUND: Black race is associated with worse outcomes in early breast cancer. We evaluated clinicopathologic characteristics, the 21-gene recurrence score (RS), treatment delivered, and clinical outcomes by race and ethnicity among women who participated in the Trial Assigning Individualized Options for Treatment. METHODS: The association between clinical outcomes and race (White, Black, Asian, other or unknown) and ethnicity (Hispanic vs non-Hispanic) was examined using proportional hazards models. All P values are 2-sided. RESULTS: Of 9719 eligible women with hormone receptor-positive, HER2-negative, node-negative breast cancer, there were 8189 (84.3%) Whites, 693 (7.1%) Blacks, 405 (4.2%) Asians, and 432 (4.4%) with other or unknown race. Regarding ethnicity, 889 (9.1%) were Hispanic. There were no substantial differences in RS or ESR1, PGR, or HER2 RNA expression by race or ethnicity. After adjustment for other covariates, compared with White race, Black race was associated with higher distant recurrence rates (hazard ratio [HR] = 1.60, 95% confidence intervals [CI] = 1.07 to 2.41) and worse overall survival in the RS 11-25 cohort (HR = 1.51, 95% CI = 1.06 to 2.15) and entire population (HR = 1.41, 95% CI = 1.05 to 1.90). Hispanic ethnicity and Asian race were associated with better outcomes. There was no evidence of chemotherapy benefit for any racial or ethnic group in those with a RS of 11-25. CONCLUSIONS: Black women had worse clinical outcomes despite similar 21-gene assay RS results and comparable systemic therapy in the Trial Assigning Individualized Options for Treatment. Similar to Whites, Black women did not benefit from adjuvant chemotherapy if the 21-gene RS was 11-25. Further research is required to elucidate the basis for this racial disparity in prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".