Data from Phase I Study of the Liposomal Formulation of Eribulin (E7389-LF): Results from the Advanced Gastric Cancer Expansion Cohort
Bibliographic record
Abstract
AbstractPurpose: In the dose-expansion part of this open-label, phase I study, we explored the efficacy and safety of E7389-LF (liposomal formulation of eribulin) in Japanese patients with advanced gastric cancer. Patients and Methods: Patients with advanced gastric cancer who had been previously treated with ≥2 lines of chemotherapy received E7389-LF 2.0 mg/m2 every 3 weeks (the previously determined maximum tolerated dose, the primary objective of Study 114). Secondary objectives included objective response rate (ORR), progression-free survival (PFS), and safety; exploratory objectives included disease control rate (DCR) and clinical benefit rate (CBR), as well as pharmacodynamic measurements of serum biomarkers. Results: As of June 24, 2021, 34 patients were enrolled and treated (10 from the original dose-expansion cohort, expanded to include 24 additional patients). Six patients had partial responses, for an ORR of 17.6% [95% confidence interval (CI), 6.8–34.5], and the median PFS was 3.7 months (95% CI, 2.7–4.8). The DCR was 79.4% (95% CI, 62.1–91.3), and the CBR was 32.4% (95% CI, 17.4–50.5). Overall, 32 patients (94.1%) experienced treatment-related adverse events, and 26 patients (76.5%) experienced grade ≥3 events, most commonly neutropenia (41.2%) and leukopenia (29.4%). Of the 8 endothelial cell/vasculature markers tested in this study, 7 were significantly increased among patients treated with E7389-LF; these changes were generally consistent regardless of best overall response. Conclusions: E7389-LF 2.0 mg/m2 every 3 weeks was tolerable and showed preliminary activity for the treatment of patients with gastric cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".