Real-World Outcomes of Adjuvant Chemotherapy for Node-Negative and Node-Positive HER2-Positive Breast Cancer
Bibliographic record
Abstract
Background: Comparative real-world outcomes for patients with HER2-positive (HER2+) breast cancer receiving adjuvant trastuzumab outside of clinical trials are lacking. This study sought to retrospectively characterize outcomes for patients with node-negative and node-positive breast cancer receiving adjuvant trastuzumab in combination with docetaxel/cyclophosphamide (DCH), docetaxel/carboplatin/trastuzumab (TCH), or fluorouracil/epirubicin/cyclophosphamide followed by docetaxel/trastuzumab (FEC-DH) chemotherapy in Alberta, Canada, from 2007 through 2014. Methods: Disease-free survival and overall survival (OS) analyses for node-negative cohorts receiving DCH (n=111) or TCH (n=371) and node-positive cohorts receiving FEC-DH (n=146) or TCH (n=315) were compared using chi-square, Kaplan-Meier, or Cox multivariable analysis where appropriate. Results: Median follow-up was similar in node-negative (63.9 months) and node-positive (69.0 months) cohorts. The 5-year OS rates in patients with node-negative disease receiving DCH or TCH were similar (95.2% vs 96.9%; P=.268), whereas 5-year OS rates were higher but nonsignificant for patients with node-positive disease treated with FEC-DH compared with TCH (95.2% vs 91.4%; P=.160). Subgroup analysis of node-positive cohorts showed significantly improved OS with FEC-DH versus TCH in patients with estrogen receptor (ER)/progesterone receptor (PR)–positive breast cancer (98.3% vs 91.6%, respectively; P=.014). Conversely, patients with ER/PR-negative disease showed a nonsignificant trend toward higher OS rates with TCH versus FEC-DH (91.6% vs 83.3%, respectively; P=.298). Given the retrospective design, we were unable to capture all potential covariates that may have impacted treatment assignment and/or outcomes. Furthermore, cardiac toxicity data were unavailable. Conclusions: Survival rates of patients with HER2+ breast cancer in our study are comparable to those seen in clinical trials. Our findings support chemotherapy de-escalation in patients with node-negative disease and validate the efficacy of FEC-DH in those with node-positive disease.
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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) | 0.000 | 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".