Indices of peripheral leukocytes predict longer overall survival in breast cancer patients on eribulin in Japan
Bibliographic record
Abstract
BACKGROUND: It was reported that eribulin regulates the tumor microenvironment, including the immune system, by inducing vascular remodeling. Lymphocyte counts are a critical index of immune response in patients. The non-Asian, global EMBRACE study has suggested that baseline absolute lymphocyte count (ALC) may be a predictor of the survival benefit of eribulin in breast cancer patients. We examined whether the baseline ALC is a potential predictor of overall survival (OS) in Japanese patients with HER2-negative advanced breast cancer treated with eribulin. METHODS: This was a post hoc analysis of data from a post-marketing observational study of eribulin in Japan. The OS by baseline ALC was estimated using the Kaplan-Meier method, with the cut-off value of 1500/μL for ALC. The OS by baseline neutrophil-to-lymphocyte ratio (NLR), a general prognostic index in breast cancer patients, was also estimated, with the cut-off value of 3. RESULTS: The median OS was longer in patients with an ALC of ≥ 1500/μL than in those with an ALC of < 1500/μL (19.4 vs. 14.3 months; hazard ratio [HR]: 0.628; 95% confidence interval [CI]: 0.492, 0.801). Patients with an NLR of ≥ 3 showed shorter OS than those with an NLR of < 3 (13.2 vs. 18.8 months; HR: 1.552; 95% CI 1.254, 1.921), and NLR also separated OS in patients with an ALC of < 1500/μL. CONCLUSIONS: Consistent with the findings of a previous study involving a non-Asian, Western population, our study suggested that baseline ALC may be a predictive factor for the survival benefit of eribulin in Japanese 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) | 0.001 | 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) | 0.003 | 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".