A phase I combination dose-escalation study of eribulin mesylate and gemcitabine in patients with advanced solid tumours: a study of the Princess Margaret Consortium
Bibliographic record
Abstract
BACKGROUND: Eribulin mesylate is a synthetic microtubule inhibitor that showed cytotoxic synergy in combination with gemcitabine preclinically. This combination was assessed in a Phase I dose-finding trial in patients diagnosed with advanced solid tumours who had received up to two prior chemotherapy regimens for metastatic disease (CP cohort). METHODS: Dose escalation was performed in a 3+3 design to identify the recommended phase II dose (RP2D). Two additional expansion cohorts in women with gynaecologic cancers at the RP2D (G), and further dose escalation of metastatic chemotherapy-naive patients (CN), were evaluated. RESULTS: 45 patients were treated: 21 (CP), 10 (G) and 14 (CN). The initial combination of eribulin and gemcitabine was administered on days 1, 8, and 15 of a 28-day cycle; however, due to 2 out of 6 dose-limiting haematological toxicities at the first dose level, a reduced dose-intense schedule was assessed. The RP2D was defined at 1.0 mg m(-2) eribulin and 1000 mg m(-2) gemcitabine day 1 and 8 q3 weeks. No other significant toxicities were observed in the G expansion cohort. Neutropenia prevented further dose escalation in the CN cohort. Objective responses were seen in all three cohorts - 2/21 (CP), 1/10 (G) and 2/14 (CN). CONCLUSIONS: The combination of eribulin and gemcitabine was well tolerated at the RP2D.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".