Selinexor plus low-dose bortezomib and dexamethasone for patients with relapsed or refractory multiple myeloma
Bibliographic record
Abstract
Abstract Selinexor is an oral inhibitor of the nuclear export protein exportin 1. Preclinical studies demonstrated synergistic antimyeloma activity between selinexor and proteasome inhibitors (PI) through suppression of NF-κB signaling and nuclear retention of tumor suppressor proteins. We tested selinexor in combination with low-dose bortezomib and dexamethasone (SVd) for the treatment of relapsed or refractory multiple myeloma (MM). The primary objectives of this study were to determine the safety profile, overall response rate (ORR), and a recommended phase 2 dose (RP2D) of SVd. We enrolled 42 patients to receive selinexor (60, 80, or 100 mg orally) plus bortezomib (1.3 mg/m2 subcutaneously) and dexamethasone (20 mg orally) once or twice weekly in 21- or 35-day cycles. Patients had a median of 3 (range 1-11) prior lines of therapy, and 50% were refractory to a PI. Treatment-related grade 3 or 4 adverse events reported in ≥10% of patients were thrombocytopenia (45%), neutropenia (24%), fatigue (14%), and anemia (12%). Incidence (4 patients, 10%) and grade (≤2) of peripheral neuropathy were low. The ORR for the entire population was 63%: 84% ORR for PI nonrefractory and 43% for PI-refractory patients. The median progression-free survival for all patients was 9.0 months; 17.8 months for PI nonrefractory, and 6.1 months for PI refractory. SVd treatment produced high response rates in patients with relapsed or refractory MM, including borezomib-refractory MM, with no unexpected side effects. The RP2D is selinexor (100 mg once weekly), bortezomib (1.3 mg/m2 once weekly for 4 weeks), and dexamethasone (40 mg once weekly) per 35-day cycle. This trial was registered at www.clinicaltrials.gov as #NCT02343042.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".