A phase 1b study of erlotinib and momelotinib for the treatment of EGFR-mutated, tyrosine kinase inhibitor-naive metastatic non-small cell lung cancer
Bibliographic record
Abstract
INTRODUCTION: Preclinical evidence suggests the feedforward cytokine loop of interleukin-6/Janus kinases (JAK)/STAT3 plays a role in epidermal growth factor receptor tyrosine kinase inhibitor (EGFR TKI) resistance in EGFR-mutated non-small cell lung cancer (NSCLC). METHODS: In this phase 1b study, the JAK1/2 and TANK-binding kinase 1 (TBK1) inhibitor momelotinib was evaluated in combination with erlotinib in patients with EGFR TKI-naive, EGFR-mutated NSCLC. After erlotinib lead-in (50, 75, 100, or 150 mg oral daily [QD]), momelotinib was combined and dose escalated in a 3 + 3 study design. The primary endpoint of maximum tolerated dose (MTD) of momelotinib was determined based on the incidence of dose-limiting toxicities (DLTs) during the first 28-day cycle. Secondary endpoints included efficacy and pharmacokinetics (PK). RESULTS: Eleven patients were enrolled across 3 dose levels of momelotinib (100 mg QD, 200 mg QD, and 100 mg twice daily [BID]). The MTD was momelotinib 200 mg QD in combination with erlotinib. Two DLTs of grade 4 neutropenia without fever and grade 3 diarrhea occurred at momelotinib 100 mg BID. Most common treatment-emergent adverse events included diarrhea, dry skin, fatigue, and decreased appetite; the vast majority being grades 1-2. The overall response rate was 54.5% (90% CI 27.1-80.0; all partial) and median progression-free survival was 9.2 months (90% CI 6.2-12.4). Momelotinib did not affect the PK of erlotinib. CONCLUSIONS: The JAK1/2 and TBK1 inhibitor momelotinib in combination with erlotinib did not appear to enhance benefit over the historical data of erlotinib monotherapy in patients with EGFR-mutated NSCLC. CLINICALTRIALS. GOV IDENTIFIER: NCT02206763.
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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) | 0.000 | 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".