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Record W2905066255 · doi:10.1182/blood-2018-99-117349

Selinexor Plus Pomalidomide and Low Dose Dexamethasone (SPd) in Patients with Relapsed or Refractory Multiple Myeloma

2018· article· en· W2905066255 on OpenAlexaffabout
Christine I. Chen, Heather J. Sutherland, Rami Kotb, Michaël Sébag, Darrell White, William Bensinger, Cristina Gasparetto, Richard LeBlanc, Christopher P. Venner, Suzanne Lentzsch, Gary J. Schiller, Brea Lipe, Aldo Del Col, Jatin J. Shah, Jacqueline Jeha, Jean‐Richard Saint‐Martin, Michael Kauffman, Sharon Shacham, Nizar J. Bahlis

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversity of CalgaryHôpital Maisonneuve-RosemontQueen Elizabeth II Health Sciences CentreCancerCare ManitobaVancouver General HospitalDalhousie UniversityRoyal Victoria HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsPomalidomideLenalidomideTolerabilityMedicineMultiple myelomaInternal medicineRefractory (planetary science)DexamethasoneOncologyCarfilzomibIxazomibDosingNeutropeniaPharmacologyAdverse effectGastroenterologyToxicityBiology

Abstract

fetched live from OpenAlex

Abstract Introduction - The nuclear export protein exportin 1 (XPO1) is overexpressed in a wide variety of cancers including multiple myeloma (MM). Selinexor is a first-in-class Selective Inhibitor of Nuclear Export (SINE) compound that binds and inactivates XPO1. Selinexor forces nuclear retention and reactivation of cell cycle regulators such as p53, IkB, and Rb. Pomalidomide/dexamethasone (Pd) is approved in relapsed/refractory MM (RRMM)with an overall response rate (ORR) of 30% and progression-free survival (PFS) rate of <4 months in patients (pts) having received a prior proteasome inhibitor (PI) and IMiD. Strategies to improve the ORR and PFS are needed. In murine MM models, the combination of selinexor with IMiDs shows synergistic anti-MM activity and good tolerability. Methods- Pts with RRMM who received ≥ 2 prior therapies including lenalidomide (len) and a PI were enrolled. Selinexor was evaluated in 2 different dosing schedules of once-weekly (QW, 60 or 80 mg) or twice-weekly (BIW, 60 or 80 mg), with pomalidomide (pom)3 or 4 mg PO daily, and dexamethasone (dex) 20 mg BIW or 40 mg QW. The primary objectives were to determine the maximum tolerated dose (MTD), recommended phase 2 dose (RP2D), safety, and preliminary efficacy of the combination of selinexor, pomalidomide, and low dose dex (SPd) in pts with RRMM. Results- As of July 20th2018, 34 pts (16 male / 18 female) have been enrolled. The median age is 61 years and patients received a median of 4 (range, 2 - 9) prior treatment regimens. Thirty-two patients were IMiD refractory (21 len, 11 pom/len). Six dose limiting toxicities (DLTs) were observed: G3 fatigue (60 mg BIW, pom 4 mg), G3 febrile neutropenia (FN) (60 mg BIW, pom 3 mg), G3 FN and G4 neutropenia (80 mg QW, pom 4), G3 thrombocytopenia (80 mg QW, pom 3 mg) and 4 missed doses in Cycle 1 due to symptomatic hyponatremia (80 mg BIW, pom 4 mg). Enrollment on selinexor 80 mg QW, pom 3 mg is ongoing. Common SPd treatment related adverse events included (all grades, grades 3/4): neutropenia (62%, 56%), thrombocytopenia (59%, 32%), anemia (53%, 29%), anorexia (56%, 0%), fatigue (50%, 9%), nausea (47%, 0% ). Thirty pts were evaluable for response, which is outlined in Table 1. Median PFS is 10.3 months with a median follow up of 9.4 months. Conclusions- Enrollment is ongoing to evaluate once weekly selinexor in combination with Pd , (SPd). This all-oral SPd combination has clinical activity with an ORR 55% in pom-naive pts with heavily pretreated MM compared to previously published data of 30% ORR for Pd alone. Similarly, the PFS on SPd is 10.3 months vs. <4 months for Pd alone. No unexpected adverse events were noted. Phase 1 dose escalation of the combination of SPd is ongoing to define the optimal RP2D. Disclosures Chen: Amgen: Honoraria. Sebag:Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees. White:Amgen, Celgene, Janssen, Takeda: Honoraria. Bensinger:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Speakers Bureau; celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; amgen: Speakers Bureau. Gasparetto:Bristol-Myers Squibb: Consultancy, Honoraria, Other: Travel; Janssen: Consultancy, Honoraria, Other: Travel; Takeda: Honoraria; Celgene: Consultancy, Honoraria, Other: Travel, Research Funding. Leblanc:Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Venner:Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria; Takeda: Honoraria. Schiller:Pharmacyclics: Research Funding; Celator/Jazz Pharmaceuticals: Research Funding. Lipe:Celgene: Consultancy. Shah:Karyopharm Therapeutics: Employment. Jeha:Karyopharm Therapeutics: Employment. Saint-Martin:Karyopharm Therapeutics: Employment. Kauffman:Karyopharm Therapeutics: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Shacham:Karyopharm Therapeutics: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Bahlis:Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.203
Teacher spread0.198 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations5
Published2018
Admission routes2
Has abstractyes

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