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Comparative effectiveness of linvoseltamab versus standard-of-care (SOC) treatment (tx) in real-world patients (pts) in the United States (US) with triple-class exposed (TCE) relapsed/refractory multiple myeloma (RRMM).

2024· article· en· W4399480665 on OpenAlexaff
Shaji Kumar, Katja Weisel, Qiufei Ma, Christian Hampp, Olivier Humblet, Mostafa Shokoohi, Nicolle Bonar, Paul Spin, James Harnett, Wenzhen Ge, Jessica J. Jalbert, Rachel E. Sobel, Glenn S. Kroog, Karen Rodriguez-Lorenc, Sundar Jagannath

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsEVERSANA (Canada)
FundersRegeneron Pharmaceuticals
KeywordsMedicineOncologyInternal medicine

Abstract

fetched live from OpenAlex

7561 Background: Pts with TCE RRMM have poor outcomes and a high unmet need, with no established SOC tx. LINKER-MM1 (NCT03761108) is a single-arm, Phase 1/2 study investigating linvoseltamab, a B-cell maturation antigen × CD3 bispecific antibody, in pts with RRMM who were previously treated with a proteasome inhibitor, immunomodulatory drug, and anti-CD38 antibody, or were triple-class refractory (TCR) to these tx. The aim of this study was to contextualize LINKER-MM1 by comparing outcomes with linvoseltamab vs a real-world (RW) external control arm (ECA). Methods: A RW ECA was derived from 2 US electronic health record databases (COTA, Guardian Research Network) of pts who started a new line of therapy (LOT) after classification as TCE or TCR and met key eligibility criteria for LINKER-MM1. Eligibility was assessed at the initiation of each new LOT, and all eligible LOTs were included in the ECA. Data in Phase 2 pts who received linvoseltamab 200 mg in LINKER-MM1 were included (data cutoff: Sep 8, 2023). Inverse probability of tx weighting (IPTW) was used to reduce imbalances between the RW and LINKER-MM1 cohorts. Key prognostic factors were identified using a systematic review and rank ordered by an international committee of MM experts (Kumar et al., 2023). Outcomes included overall response rate (ORR), progression-free survival (PFS), time to next treatment (TTNT), and overall survival (OS). An independent committee of epidemiology and oncology experts reviewed the comparability of the cohorts and endpoint assessments prior to conducting comparative analyses. Results: Comparative analyses were performed in 105 pts in the linvoseltamab cohort and 101 RW pts (137 LOTs). Following IPTW, the distribution of cytogenetic risk, age, TCR status, Eastern Cooperative Oncology Group Performance Status, and platelet count were balanced between the 2 cohorts (absolute standardized mean difference <0.10). After adjustment, pts receiving linvoseltamab had significantly improved ORR, PFS, TTNT, and OS vs the RW ECA (see table). Conclusions: Linvoseltamab significantly improved outcomes vs RW SOC in the US, highlighting its potential as a highly effective tx in pts with TCE RRMM. [Table: see text]

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.131
GPT teacher head0.463
Teacher spread0.332 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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