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P957: AN INDIRECT COMPARISON OF ELRANATAMAB’S (ELRA) OBJECTIVE RESPONSE RATE (ORR) FROM MAGNETISMM-3 (MM-3) VERSUS REAL-WORLD EXTERNAL CONTROL ARMS IN TRIPLE-CLASS REFRACTORY (TCR) MULTIPLE MYELOMA (MM)

2023· article· en· W4385667237 on OpenAlexaff
Luciano J. Costa, Thomas W. LeBlanc, Hans Tesch, Pieter Sonneveld, Ryan Kyle, Liliya Sinyavskaya, Patrick Hlavacek, Aster Meche, Jinma Ren, Alex Schepart, Didem Aydin, Marco DiBonaventura

Bibliographic record

VenueHemaSphere · 2023
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsCohortMultiple myelomaMedicineInternal medicineOncologyRefractory (planetary science)Biology

Abstract

fetched live from OpenAlex

Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: ELRA is a BCMAxCD3 bispecific antibody being investigated for the treatment of R/R MM. Aims: The phase 2 MM-3 trial was single-armed; the aim of this study (NCT05565391) was to contextualize the efficacy data from MM-3 with two real-world (RW) external control arms. Methods: A retrospective cohort study was conducted to indirectly compare the efficacy observed in MM-3 Cohort A (BCMA-naïve; N=123) from the 9-month data cut with two US-based oncology electronic health record databases, Flatiron Health (FH) and COTA, as external controls. MM-3 inclusion (eg, prior MM diagnosis, ECOG≤2, refractory to ≥1 PI, ≥1 IMiD, and ≥1 anti-CD38) and exclusion (I/E) criteria (eg, plasma cell leukemia, smoldering MM) were applied to each RW database to obtain comparable patient populations across sources. After imposing MM-3 I/E criteria, comparisons between data sources on ORR were conducted by estimating rate ratios (RRs) using log-binomial regression models (unweighted analysis). RRs were also estimated using both inverse probability treatment weighting (IPTW) and augmented IPTW (doubly robust) analyses to account for key covariates (eg, age, comorbidities, ECOG, ISS, prior lines/refractoriness, cytogenetic risk, extramedullary disease, lab values). Results: The 123 patients from MM-3 Cohort A were compared with the 152 and 233 patients identified from the FH and COTA databases, respectively. Treatment regimens in the RWD sources included various combinations of PIs, IMiDs, and mAbs, among other agents (eg, selinexor). Across unweighted, IPTW, and doubly robust analyses, the ORR for ELRA was significantly higher than treatments used for TCR MM patients from RWD sources (Table 1; all p<.05). Summary/Conclusion: Among TCR MM patients who resemble those of the MM-3 trial, ELRA showed improved ORR compared with treatments currently used in clinical practice.Keywords: Multiple myeloma, Myeloma, Real world data

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.050
GPT teacher head0.351
Teacher spread0.301 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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