A Phase 1b Study to Assess the Combination of Selinexor and Daratumumab in Patients with Relapsed / Refractory Multiple Myeloma Previously Exposed to Proteasome Inhibitors (PI) and Immunomodulatory Drugs (IMiDs)
Bibliographic record
Abstract
Abstract Introduction - Selinexor is a first-in-class Selective Inhibitor of Nuclear Export (SINE) compound that binds and inactivates Exportin 1 (XPO1). Selinexor, as a single agent, or in combination with PIs or IMiDs, has shown anti-MM activity in patients (pts) with relapsed or refractory multiple myeloma (RRMM). Daratumumab, an anti-CD38 monoclonal antibody, is approved for the treatment of In this study, we aim to explore the safety and efficacy of selinexor in combination with daratumumab and low dose dexamethasone (SDd) in pts with RRMM. Methods - This is a phase 1b/2 dose escalation study using a standard 3+3 design. The primary endpoint is to determine the maximum tolerated dose and recommended phase 2 dose (RP2D) for SDd. Pts were eligible if they had RRMM and had received ≥ 3 prior therapies, including a PI and IMiD. Selinexor was independently dosed escalated in 2 concurrent cohorts: once-weekly (QW, at 100 mg) or twice-weekly (BIW, at 60 mg) regimens. Daratumumab (16 mg/kg IV) was administered QW and dexamethasone (dex) was given orally 40 mg QW or 20 mg BIW. Results - As of 15-Jul-2017, 6 pts (4 males / 2 females) have been enrolled. Three pts each have been enrolled into the 100 mg QW and 60 mg BIW cohorts. Pts have a median age of 66 years and a median of 3 (range, 3 - 7) prior treatment regimens. Adverse events include: nausea, thrombocytopenia, and anemia. Three pts in the 100 mg QW cohort tolerated the regimen well with no DLT. The 3 pts in the 60 mg BIW cohort have not yet completed DLT evaluation. Based on preliminary tolerability and efficacy, an additional 3 pts will be enrolled in the 100 mg QW cohort to establish the RP2D dose. All 3 pts from the 100 mg QW cohort had a partial response (2 unconfirmed) after C1 and remain on study. Conclusions - Selinexor 100 mg QW, can be combined safely with daratumumab and dex. The activity observed in the first 3 pts is promising with all 3 pts responding to therapy. Enrollment is ongoing and updated data from 100 mg QW cohort, 100 mg QW expansion, and full phase 1 will be updated and presented. Disclosures Gasparetto: Celgene: Research Funding; Janssen, BMS, Celgene: Other: Travel, accommodations, or other expenses paid or reimbursed; Janssen, BMS, Celgene, Takeda: Honoraria; Janssen, BMS, Celgene: Consultancy. Lentzsch: Amgen: Consultancy; BMS: Consultancy; Caelum Biosciences: Other: leadership position and stock. Bensinger: Bayer: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Acetylon: Research Funding; BMS: Consultancy, Research Funding. Bahlis: Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Sebag: Celgene, Janssen: Consultancy. Chen: Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Amgen: Honoraria; Abbvie: Honoraria. Kauffman: Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Shacham: Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Jeha: Karyopharm Therapeutics: Employment. Saint-Martin: Karyopharm Therapeutics: Employment. Shah: Karyopharm Therapeutics: Employment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".