A phase III, open-label, randomized study of eribulin mesylate versus capecitabine in patients with locally advanced or metastatic breast cancer (MBC) previously treated with anthracyclines and taxanes: Subgroup analyses.
Bibliographic record
Abstract
1049^ Background: This phase III study, comparing eribulin versus capecitabine, showed a non-significant trend for superior overall survival (OS; hazard ratio [HR] 0.88 [95% confidence interval (CI) 0.77, 1.00]; p = 0.056) but not progression-free survival (PFS; HR 1.08 [95% CI 0.93, 1.25]; p = 0.31). Pre-specified exploratory subgroup analyses previously presented showed that patients with triple-negative, ER-negative or HER2-negative disease may have a greater benefit in OS with eribulin compared with capecitabine. Here we present further pre-specified exploratory analyses of OS and PFS. Methods: Patients (eribulin n=554; capecitabine n=548) with locally advanced or MBC had received ≤3 prior chemotherapy regimens (≤2 for advanced disease), including an anthracycline and a taxane. Patients were randomized (stratified for geographic region and HER2 status) 1:1 to 21-day cycles of eribulin mesylate 1.4 mg/m2 i.v. on days 1 and 8 or capecitabine 1.25 g/m2BID orally on days 1-14. Further pre-specified exploratory subgroups included: age; receptor status; number and setting of prior chemotherapy regimen(s); sites of disease; number of organs involved; and time to progression after last chemotherapy. Results: From analyses for OS, patients with only non-visceral disease (HR 0.51; 95% CI 0.33, 0.80), with >2 organs involved (HR 0.75; 95% CI 0.62, 0.90), who had progressed >6 months after last chemotherapy (HR 0.70; 95% CI 0.52, 0.95), or who had received an anthracycline and/or a taxane in the metastatic setting (HR 0.84; 95% CI 0.72, 0.98), appeared to benefit more from treatment with eribulin compared with capecitabine. For OS, in no subgroup was a trend favoring capecitabine seen. Data for other pre-specified subgroups for both OS and PFS will be presented. Conclusions: In addition to patients with triple-, ER-, or HER2-negative disease, further pre-specified exploratory analyses suggest that other patient subgroups may particularly benefit from treatment with eribulin; further studies are warranted to address these hypotheses. Clinical trial information: NCT00337103.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".