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Selinexor, daratumumab, and dexamethasone in patients with relapsed/refractory multiple myeloma (MM).

2020· article· en· W3031418164 on OpenAlexaff
Cristina Gasparetto, Suzanne Lentzsch, Gary J. Schiller, Natalie S. Callander, Sascha A. Tuchman, Nizar J. Bahlis, Darrell White, Christine Chen, Muhamed Baljević, Heather J. Sutherland, Rami Kotb, Michaël Sébag, Richard LeBlanc, Christopher P. Venner, William Bensinger, Adriana Rossi, Heidi Sheehan, Melina Arazy, Kazuharu Kai, Brea Lipe

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsHôpital Maisonneuve-RosemontMcGill University Health CentreVancouver General HospitalCancerCare ManitobaQueen Elizabeth II Health Sciences CentrePrincess Margaret Cancer CentreDalhousie University
FundersKaryopharm Therapeutics
KeywordsTolerabilityMedicineDaratumumabInternal medicineDexamethasoneRefractory (planetary science)Phases of clinical researchOncologyGastroenterologyAdverse effectPharmacologyLenalidomideClinical trial

Abstract

fetched live from OpenAlex

8510 Background: Selinexor is a first-in-class oral Selective Inhibitor of Nuclear Export (SINE) compound that binds and inactivates exportin 1 (XPO1). Selinexor in combination with low dose dexamethasone (Sel-dex) was approved by the FDA, based on data from the STORM study, wherein Sel-dex induced an overall response rate (ORR) of 26.2% in patients (pts) with relapsed/refractory MM (RRMM). Single agent daratumumab has demonstrated an ORR of 29% in MM reftactory to proteasome inhibitors (PIs)/immunomodulatory drug (IMiDs). We evaluated the safety, tolerability and preliminary efficacy of the combination of Sel-dex and daratumumab (SDd) in pts with MM refractory to PIs/IMiDs. Methods: This is a multicenter, open-label, phase 1b/2 dose escalation and expansion study. Pts were eligible if they had received ≥ 3 prior lines of therapy, including a PI and an IMiD, or whose MM was refractory to a PI and an IMiD. In the expansion phase, pts were required to be anti-CD38 monoclonal antibody-naïve. One dose level was tested at each schedule: selinexor once-weekly (QW at 100 mg) or twice-weekly (BIW at 60 mg) with dexamethasone 40 mg. Daratumumab 16 mg/kg IV was administered per label. Primary objective was to determine the maximum tolerated dose and recommended phase 2 dose (RP2D), and assess safety, tolerability and efficacy of SDd in pts with RRMM. Results: A total of 34 pts were enrolled; 3 in the 60 mg BIW and 31 in the 100 mg QW cohorts. Median age was 69 and median number of prior treatment regimens was 3 (range, 1–10). Out of 34 pts, 62% and 65% were refractory to bortezomib and lenalidomide respectively. Common treatment related adverse events (all grades, grades 3/4) included: thrombocytopenia (71%, 47%), fatigue (62%, 18%), nausea (71%, 9%), anemia (62%, 32%) and neutropenia (50%, 26%). Two dose limiting toxicities (DLTs) were reported in the 60 mg BIW cohort: Grade 3 thrombocytopenia and Grade 2 fatigue requiring dose reduction in selinexor to 100 mg QW. In the 100 mg QW escalation cohort (n = 6), no DLTs occured. 32 patients were evaluable for efficacy. The ORR was 73% (11 VGPR, 11 PR) for 30 daratumumab-naïve pts. Median progression-free survival was 12.5 months in both groups. Conclusions: Based on tolerability and efficacy, the RP2D of SDd is selinexor 100 mg, daratumumab 16 mg/kg and dexamethasone 40 mg, administered QW. In pts with PI and IMiD refractory MM, weekly SDd demonstrated promising activity with an ORR of 73% in daratumumab-naïve pts and a median PFS of 12.5 months. This supports further development of a novel non-PI, non-IMiD backbone in earlier lines of therapy. Clinical trial information: NCT02343042 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.068
GPT teacher head0.376
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

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Citations19
Published2020
Admission routes1
Has abstractyes

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