The Selinexor in Advanced Liposarcoma (SEAL) study: A phase 2/3, multicenter, randomized, double blind study of selinexor versus placebo in patients with advanced, unresectable, dedifferentiated liposarcoma (DDLS).
Bibliographic record
Abstract
TPS11072 Background: DDLS represents progression from low- to high-grade non-lipogenic morphology within well-differentiated liposarcoma (WDLS) with the potential to metastasize and a higher mortality rate. Selinexor is an oral, selective inhibitor of nuclear export that specifically blocks XPO1, leading to the nuclear accumulation and re-activation of tumor suppressor proteins and growth modulators. Selinexor demonstrated potent anti-tumor activity in liposarcoma (LPS) cell line and murine models. Sarcoma patients received selinexor in two Phase 1 studies, resulting in stable disease in 14/18 (78%) of patients with advanced LPS; notably, 6 of these had stable disease ≥ 4 months. Tumor reduction of 2-23% was noted in 14 patients. There were no clinically significant cumulative toxicities. Hence, we designed a Phase 2/3 multi-center, randomized, double blind study to assess whether selinexor can improve progression-free survival (PFS) of patients with advanced unresectable DDLS compared to placebo. Methods: Eligible patients have DDLS with measurable disease, radiologic evidence of progressive disease (PD) within 6 months, and have had at least one prior line of systemic therapy. Patients with pure WDLS, myxoid/round cell or pleomorphic subtypes are not eligible. Patients will be randomized 1:1 (selinexor:placebo) during Phase 2, and 2:1 during Phase 3 and will receive selinexor 60 mg or placebo twice weekly on a 42 day cycle until PD or intolerability. Patients with PD on placebo can crossover to selinexor. The primary endpoint is PFS. The study is powered to detect a 50% improvement with selinexor versus placebo. Secondary endpoints include overall survival and response rate. Planned total sample size (Phase 2+3) is 245. Enrollment began in January 2016. Clinical trial information: NCT02606461.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".