Randomized study evaluating optimal dose, efficacy and safety of E7386 + lenvatinib versus treatment of physicians’ choice in advanced/recurrent endometrial carcinoma previously treated with anti–PD-(L)1 immunotherapy.
Bibliographic record
Abstract
TPS5632 Background: E7386 is an inhibitor of protein-protein interaction between β-catenin and CREB binding protein (CBP). E7386 + lenvatinib has demonstrated manageable safety and promising antitumor activity in the dose-expansion cohort of Study 102 that included patients with advanced endometrial cancer previously treated with immunotherapy (Lee JY et al., Ann Oncol 2024). Considering these results, we are conducting a dose-optimization part of Study 102 (NCT04008797) in patients with advanced/recurrent endometrial carcinoma (aEC). Methods: Eligible patients (≥18 years) must have a confirmed diagnosis of aEC, and prior treatment with platinum-based chemotherapy and PD-(L)1-directed therapy. Up to 3 prior lines of therapy, regardless of setting, are allowed; prior hormonal therapy and radiation do not count as lines of therapy. Patients will be randomized (1:1:1:1) to E7386 120 mg BID + lenvatinib 14 mg QD (n=30); E7386 60 mg BID + lenvatinib 14 mg QD (n=30); lenvatinib 24 mg QD monotherapy (n=30); or treatment of physician’s choice (TPC, doxorubicin 60 mg/m 2 Q3W or paclitaxel 80 mg/m 2 QW [3 weeks on/1 week off]; n=30 in total). Randomization will be stratified by region (Asia/North America/Rest of the World). The primary objective is to determine the optimal dose of E7386 + lenvatinib in aEC; additional objectives include: safety, assessing the contribution of E7386 to the overall treatment effect of E7386 + lenvatinib, and assessing the efficacy of E7386 + lenvatinib relative to TPC. Tumors will be assessed by investigators (per Response Evaluation Criteria in Solid Tumors [RECIST] version 1.1) every 8 weeks from the first dose. Adverse events will be monitored and graded according to Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. This multinational study is actively recruiting. Clinical trial information: NCT04008797 .
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".