MétaCan
Menu
Back to cohort

P908: IDENTIFICATION OF CYTOKINES ASSOCIATED WITH RESPONSE AND CYTOKINE RELEASE SYNDROME – ANALYSIS OF MAGNETISMM-3 COHORT A

2023· article· en· W4385704654 on OpenAlexaff
Katja Weisel, Nizar J. Bahlis, Paula Rodríguez‐Otero, Andrea Viqueira, Shen‐Wu Wang, Sangeetha Sathiah, Douglas S. Robinson, Thomas O'Brien, Hang Quach

Bibliographic record

VenueHemaSphere · 2023
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsInstitute of Cancer ResearchUniversity of Calgary
Fundersnot available
KeywordsMedicineCytokineCytokine release syndromeInternal medicineCohortMultiple myelomaImmunologyGastroenterologyImmunotherapyImmune system

Abstract

fetched live from OpenAlex

Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: MagnetisMM-3 (NCT04649359) is a phase 2 study of elranatamab monotherapy in patients with multiple myeloma refractory to at least 1 proteasome inhibitor, 1 immunomodulatory drug, and 1 anti-CD38 antibody. Promising efficacy and safety have been observed in patients who were naïve to B-cell maturation antigen (BCMA)-directed therapy (Cohort A) in MagnetisMM-3 (Bahlis et al., ASH 2022). Aims: This analysis examined the relationship between cytokine levels and elranatamab response, and cytokine levels and cytokine release syndrome (CRS), in BCMA-naïve patients from MagnetisMM-3. Methods: In MagnetisMM-3, patients received subcutaneous elranatamab in 28-day cycles with step-up doses of 12 mg on C1D1 and 32 mg on C1D4 followed by 76 mg QW beginning C1D8. Serum samples were collected on C1D1 prior to first priming dose, and on C1D2, pre-dose C1D4, C1D5, pre-dose C1D8, C1D15, and C1D22. Levels of 45 peripheral cytokines were analyzed by proximity extension assay and a longitudinal mixed effects model was applied to each cytokine separately. Cytokines with a significant 2-fold differential expression in responders (defined as patients with best overall response of very good partial response [VGPR] or better) vs non-responders (defined as patients with best overall response of partial response or worse) and in patients with CRS vs no CRS at any timepoint are reported. Clinical data cutoff was Oct 2022 with a median follow up of 10.4 months. Results: Baseline levels of IL-6 (2.6-fold), IL-17C (2.0-fold), and MIP-1α (2.1-fold) were lower in patients who achieved a response. After the first priming dose, 13 cytokines in the panel, including CCL8, IFN-γ, IL-2, and IL-27, were differentially expressed in responders vs non-responders. At baseline, no cytokines were found to predict CRS. After the first priming dose, 18 cytokines in the panel, including CCL8, IFN-γ, IL-10, IL-2, IL-27, IL-6 (Figure), and IL-17A, were differentially expressed in patients with CRS vs no CRS. The maximal differential expression for 17/18 cytokines occurred at C1D2, ~24 hours post the first priming dose. Summary/Conclusion: Lower baseline levels of IL-6, IL-17C, and MIP-1α correlated with a response of VGPR or better in BCMA-naïve patients from MagnetisMM-3, suggesting that lower levels of these cytokines might reflect a favorable immune environment. Many cytokines were differentially expressed at higher levels in patients who experienced CRS vs those who did not; the most prominent cytokines included CCL-8, IFN-γ, and IL-10. The timing of induction of CCL-8, IFN-γ, and IL-10 occurred by C1D2 suggesting a potential contribution of these cytokines in driving CRS.Keywords: Cytokine, Clinical trial, Multiple myeloma, Myeloma

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0020.000

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 head0.017
GPT teacher head0.286
Teacher spread0.269 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHemaSphereSame topicMultiple Myeloma Research and TreatmentsFrench-language works237,207