Outcome of eribulin as a late treatment line for Thai metastatic breast cancer patients
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Bibliographic record
Abstract
Background: We report the safety and efficacy of eribulin as a late treatment line in Thai metastatic breast cancer (MBC) patients. Patients and methods: A total of 30 MBC patients treated with eribulin between January 2014 and January 2017 were retrospectively analyzed. The patients were scheduled to receive 1.4 mg/m2 of eribulin on day 1, day 8 and subsequently every 21 days. All patients had previously received at least three chemotherapy regimens including anthracycline and taxane. Response rate and progression-free survival (PFS) were analyzed. Results: The median age was 56 years (range, 40–74 years), with a median follow-up time of 5.7 months (range, 0.2–25 months). The overall response rate was 30% (nine patients): four patients had triple-negative breast cancer, three patients had luminal B breast cancer and two patients had luminal A breast cancer. The median PFS was 2.9 months (range, 0.2–14 months). The median number of previous chemotherapy regimens was 4 (range, 3–9). Univariate analysis showed that the number of regimens (four or fewer) prior to eribulin was statistically associated with superior PFS ( P = 0.009). Multivariate analysis also showed similar statistical association between number of prior regimens (four or fewer) and better PFS adjusted by age group (≥50 years; hazard ratio = 1.29; 95% CI: 1.0–1.65; P = 0.046). There were no toxic deaths or grade 4 toxicities. Nine (30%) patients had grade 3 anemia toxicities, and the other common toxicities were leukopenia and neutropenia. Four (13%) patients required dose reduction and 16 (53%) patients required dose delay because of toxicities. Conclusion: Eribulin is an effective drug for heavily pretreated MBC patients with tolerable toxicities. The benefit was superior in patients who received fewer than four previous chemotherapy regimens. Keywords: eribulin, metastatic breast cancer, late treatment line
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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 it