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Record W3096400445 · doi:10.1182/blood-2020-136415

Isatuximab Plus Carfilzomib and Dexamethasone Versus Carfilzomib and Dexamethasone in Relapsed Multiple Myeloma Patients with Renal Impairment: Ikema Subgroup Analysis

2020· article· en· W3096400445 on OpenAlexaffabout
Marcelo Capra, Thomas G. Martin, Philippe Moreau, Ross Baker, Luděk Pour, Chang‐Ki Min, Xavier Leleu, Mohamad Mohty, Marta Reinoso Segura, Mehmet Turgut, Richard LeBlanc, Marie‐Laure Risse, Laure Malinge, Sandrine Schwab, Meletios Α. Dimopoulos

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsCarfilzomibMedicineLenalidomidePomalidomideDexamethasoneInternal medicineRenal functionMultiple myelomaAdverse effectInterim analysisOncologyUrologyGastroenterologyRandomized controlled trial

Abstract

fetched live from OpenAlex

Introduction: Renal impairment (RI) is a common feature in multiple myeloma (MM) and an adverse predictor of survival. Anti-myeloma treatments that can also improve renal function in patients (pts) with MM are required. Isatuximab (Isa), a monoclonal CD38 antibody, is approved in combination with pomalidomide and dexamethasone (d), in the United States, the European Union, Canada, Australia, Switzerland, and Japan for the treatment of adult pts with relapsed/refractory MM who have received at least two prior therapies, including lenalidomide and a proteasome inhibitor. IKEMA (NCT03275285) was a randomized, open-label, multicenter, Phase 3 study that demonstrated the benefit of adding Isa to carfilzomib (K) plus d vs Kd in pts with relapsed MM. This subgroup analysis of IKEMA examined efficacy, renal response, and safety in pts with RI. Methods: Pts with 1-3 prior lines of therapy were randomized 3:2 and stratified by number of prior lines and revised international staging system (R-ISS) stage to receive Isa-Kd or Kd. The Isa-Kd arm received Isa 10 mg/kg intravenously weekly for 4 weeks, then every 2 weeks thereafter. Both arms received recommended doses of Kd. Treatment continued until disease progression or unacceptable adverse events. Interim efficacy analysis was planned when 65% of the total expected progression-free survival (PFS) events determined by an Independent Response Committee were observed. RI was defined as estimated glomerular filtration rate ([eGFR]; using the Modification of Diet in Renal Disease equation) <60 mL/min/1.73m² at baseline. Complete renal response (CrR) was defined as improvement in eGFR from <50 mL/min/1.73m² at baseline to ≥60 mL/min/1.73m² (no RI) in at least one post-baseline assessment (International Myeloma Working Group recommendations), and was classified as durable if lasting ≥60 days. Results: A total of 302 pts (179 Isa-Kd; 123 Kd) were randomized. Pts with baseline eGFR as low as 15 mL/min/1.73m² (severe RI) were allowed to enroll. more pts with RI in the Isa-Kd arm (26.1%) vs Kd (16.2%). As expected, elderly pts had more RI. The median age in years (range) was 67 (39-86) for Isa-Kd vs 69 (49-90) for Kd among RI pts, and 64 (37-81) for Isa-Kd vs 62 (33-78) for Kd among pts with no RI. In RI pts, 60.5% vs 72.2% pts had ≥2 prior lines of therapy, 11.6% vs 16.7% had R-ISS stage III, and 20.9% vs 27.8% had high risk cytogenetics, in Isa-Kd vs Kd, respectively. More RI pts were still on treatment at the cut-off date in Isa-Kd (55.8%) vs Kd (16.7%). Median PFS for RI pts was not reached for Isa-Kd vs 13.4 months for Kd (HR 0.27; 95% CI 0.11-0.66), and not reached for both study arms among pts with no RI (HR 0.63; 95% CI 0.39-1.00). The overall response rate, ≥very good partial response rate, and minimal residual disease negativity for RI pts was higher with Isa-Kd than Kd: 93.0% vs 61.1%, 79.1% vs 44.4%, and 30.2% vs 11.1%, respectively. CrR accessed in pts with eGFR <50 mL/min/1.73m² (15.2% Isa-Kd vs 11.7% Kd) occurred more frequently in Isa-Kd (52%) vs Kd (30.8%), and these were durable in 32.0% vs 7.7% pts. The treatment exposure was higher in RI pts treated with Isa-Kd, with median number of cycles started and median duration of exposure being 20 vs 9 cycles and 81.0 vs 35.7 weeks in Isa-Kd vs Kd. In pts with RI, Grade ≥3 and serious treatment emergent adverse events (TEAEs) were reported in 79.1% (Isa-Kd) vs 77.8% (Kd) and 62.8% (Isa-Kd) vs 77.8% (Kd) pts, respectively. Grade 5 TEAEs (Isa-Kd, 0%; Kd, 11.1%) and TEAEs leading to treatment discontinuation were lower with Isa-Kd (Isa-Kd, 7.0%; Kd, 27.8%). End-stage renal disease on treatment occurred in 1.8% Isa-Kd vs 2.7% Kd pts. The most common TEAEs in RI pts in Isa-Kd vs Kd were diarrhea (41.9% vs 22.2%), upper respiratory tract infection (39.5% vs 27.8%), infusion reaction (37.2% vs 5.6%), hypertension (34.9% vs 27.8%), fatigue (34.9% vs 22.2%), and dyspnea (32.6% vs 11.1%). The most common Grade ≥3 TEAEs in RI pts in Isa-Kd vs Kd were hypertension (20.9% vs 22.2%) and pneumonia (11.6% vs 22.2%). Conclusions: The addition of Isa to Kd improved PFS and disease response in pts with RI, with a manageable safety profile, consistent with the benefit observed in the overall IKEMA study population. Also, more pts treated with Isa-Kd showed reversal of RI and durable renal responses compared with Kd. Finally, RI pts treated with Isa-Kd received twice the number of cycles and had a lower treatment discontinuation rate compared with Kd pts. Disclosures Martin: AMGEN: Research Funding; Sanofi: Research Funding; GSK: Consultancy; Seattle Genetics: Research Funding; Janssen: Research Funding. Moreau:Novartis: Honoraria; Sanofi: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Honoraria. Baker:Sanofi: Research Funding. Leleu:Karyopharm: Honoraria; Sanofi: Honoraria; Novartis: Honoraria; AbbVie: Honoraria; Amgen: Honoraria; Oncopeptide: Honoraria; Incyte: Honoraria; Merck: Honoraria; Carsgen: Honoraria; Janssen: Honoraria; BMS-celgene: Honoraria; GSK: Honoraria. Mohty:Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Stemline: Consultancy, Honoraria, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding, Speakers Bureau. Leblanc:Celgene: Research Funding; Celgene Canada; Janssen Inc.; Amgen Canada; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Risse:Sanofi: Current Employment. Malinge:AIXIAL: Consultancy. Schwab:Sanofi: Current Employment. Dimopoulos:BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Personal fees, 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)0.003
metaresearch head score (Gemma)0.003
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.012
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.251
Teacher spread0.231 · 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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Citations13
Published2020
Admission routes2
Has abstractyes

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