Utilization of neoadjuvant chemotherapy in high‐risk, node‐negative early breast cancer
Bibliographic record
Abstract
BACKGROUND: Controversy exists regarding the optimal sequence of chemotherapy among women with operable node-negative breast cancers with high-risk tumor biology. We evaluated national patterns of neoadjuvant chemotherapy (NACT) use among women with early-stage HER2+, triple-negative (TNBC), and high-risk hormone receptor-positive (HR+) invasive breast cancers. METHODS: Women ≥18 years with cT1-2/cN0 HER2+, TNBC, or high recurrence risk score (≥31) HR+ invasive breast cancers who received chemotherapy were identified in the National Cancer Database (2010-2016). Cochran-Armitage and logistic regression examined temporal trends and likelihood of undergoing NACT versus adjuvant chemotherapy based on patient age and molecular subtype. RESULTS: Overall, 96,622 patients met study criteria; 25% received NACT and 75% underwent surgery first, with comparable 5-year estimates of overall survival (0.90, 95% CI 0.892-0.905 vs 0.91, 95% CI 0.907-0.913). During the study period, utilization of NACT increased from 14% to 36% and varied according to molecular subtype (year*molecular subtype p < 0.001, p-corrected < 0.001). Women with HER2+ (OR 4.17, 95% CI 3.70-4.60, p < 0.001, p-corrected < 0.001) and TNBC (OR 3.81, 95% CI 3.38-4.31, p < 0.001, p-corrected < 0.001) were more likely to receive NACT over time, without a change in use among those with HR+ disease (OR 1.58, 95% CI 0.88-2.87, p = 0.13, p-corrected = 0.17). CONCLUSION: Among women with early-stage triple-negative and HER2+ breast cancers, utilization of NACT increased over time, a trend that correlates with previously reported improved rates of pCR and options post-neoadjuvant treatment with residual disease. Future research is needed to better understand multidisciplinary decisions for NACT and implications for breast cancer patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".