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Pomalidomide (POM) + Low-Dose Dexamethasone (LoDEX) Safety and Efficacy in Patients (pts) with Relapsed and/or Refractory Multiple Myeloma (RRMM) Previously Treated with a Proteasome Inhibitor (PI) and in Whom Last Prior Therapy with Lenalidomide (LEN) Failed

2017· article· en· W2782099884 on OpenAlexaff
David Siegel, Gary J. Schiller, Kevin Song, Richy Agajanian, Ketih Stockerl-Goldstein, Hakan Kaya, Michaël Sébag, Christy Samaras, Ehsan Malek, Giampaolo Talamo, Christopher S. Seet, Jorge Mouro, Faiza Zafar, Weiyuan Chung, Shankar Srinivasan, Max Qian, Amit Agarwal, Anjan Thakurta, Nizar J. Bahlis

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of CalgaryRoyal Victoria HospitalVancouver General Hospital
Fundersnot available
KeywordsMedicinePomalidomideInternal medicineNeutropeniaMultiple myelomaLenalidomideBortezomibClinical endpointCohortAdverse effectSurgeryPopulationGastroenterologyRandomized controlled trialChemotherapy

Abstract

fetched live from OpenAlex

BACKGROUND POM + LoDEX is a standard of care for the treatment of pts with RRMM. The MM-014 (NCT01946477) trial is investigating the treatment sequence of POM + LoDEX as third-line treatment in pts with RRMM with LEN-based treatment failure as last prior therapy (cohort A). Outcomes are reported for cohort A, including a subset analysis of pts who received prior PI and/or bortezomib (BORT). METHODS Adult pts with RRMM who had received 2 prior lines of treatment and had progressive disease (PD) after ≥ 2 cycles of second-line LEN-based therapy were eligible. Pts received POM 4 mg/day on days 1 through 21 + LoDEX 40 mg/day (20 mg/day if aged > 75 years) on days 1, 8, 15, and 22 of 28-day cycles, with mandatory thromboprophylaxis. The primary endpoint was overall response rate (ORR; ≥ partial response) by modified International Myeloma Working Group criteria. Secondary endpoints included progression-free survival (PFS), safety, and second primary malignancies (SPMs). RESULTS At the data cutoff date of May 3, 2017, median follow-up was 23.8 months in the surviving pts.Baseline characteristics for all 56 pts enrolled in cohort A and for pt subgroups with prior PI or BORT exposure are shown in Table 1. Of 50 pts with cytogenetic data by fluorescence in situ hybridization, 4, 4, and 2 pts were positive for del17p, t(4;14), and t(14;16), respectively. Median duration of prior LEN-containing treatment was 23.6 months (range, 3.5-107.0 months), with 60.7% of pts receiving an immediately prior LEN dose of 25 mg/day. All pts were refractory or relapsed to their most recent prior LEN-containing regimen: 92.7% and 92.3% of pts were LEN refractory in the prior PI and prior BORT exposure subgroups, respectively. Response and PFS outcomes in the overall cohort A population and by prior treatment exposure are reported in Table 2. Among the 56 pts, 50 discontinued treatment, with 29 pts (58%) discontinuing due to PD, 6 due to withdrawal, 5 due to adverse event (AEs), 3 due to lack of efficacy, 2 due to death, and 5 due to other reasons. Grade 3/4 treatment-emergent AEs included anemia (26.8%), neutropenia (10.7%), and infections (23.2%, including pneumonia [14.3%]). Two pts experienced grade 3/4 pulmonary embolism, and 2 pts had SPMs. CONCLUSIONS POM + LoDEX is safe and effective when sequenced in third line following second-line LEN-based treatment failure in pts with RRMM who had also received prior BORT or other PI. With > 10 months of additional follow-up as previously reported (Siegel et al. EHA 2017 [abstract E1248]), median PFS was sustained at 13.8 months. The nearly 2-year duration of prior LEN treatment is reflective of pts receiving continuous treatment until PD. In cohort A, hematologic AE rates were lower and median PFS was longer with third-line use, including in the subset of pts with prior PI or BORT exposure, than what has been previously reported for any study in which POM + LoDEX was used in later treatment lines. These results support the benefit of third-line POM + LoDEX immediately following LEN + PI-based therapy in pts with RRMM. Disclosures Siegel: Celgene, Takeda, Amgen Inc, Novartis and BMS: Consultancy, Speakers Bureau; Merck: Consultancy. Schiller: bluebird bio: Research Funding; mateon therapeutics: Research Funding. Kaya: Millennium, Novartis, Celgene, Onyx, Amgen: Honoraria, Speakers Bureau. Sebag: Celgene, Janssen: Consultancy. Malek: Celgene: Speakers Bureau; Sanofi: Membership on an entity9s Board of Directors or advisory committees; Takeda: Membership on an entity9s Board of Directors or advisory committees, Speakers Bureau. Talamo: Penn State Hershey Cancer Institute: Employment. Mouro: Celgene Corporation: Employment, Equity Ownership. Zafar: Celgene Corporation: Employment. Chung: Celgene Corporation: Employment, Equity Ownership. Srinivasan: Celgene: Employment. Qian: Celgene Corporation: Employment, Equity Ownership. Agarwal: Celgene Corporation: Employment. Thakurta: Celgene Corporation: Employment, Equity Ownership. Bahlis: Amgen: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Research Funding, Speakers Bureau.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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