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Concordance between blinded independent central review committee and physician-assessed responses: Analyses based on a real-world external control arm in relapsed/refractory multiple myeloma using International Myeloma Working Group data.

2025· article· en· W4410805241 on OpenAlexaff
Brian G.M. Durie, Laura Rosiñol, Katja Weisel, Sundar Jagannath, Muhaimen Siddiqui, Nicolle Bonar, Mostafa Shokoohi, Michael L. West, Paul Spin, Christian Hampp, James Harnett, Olivier Humblet, Jeannette Green, Alexander Breskin, Glenn S. Kroog, Qiufei Ma, Shaji Kumar

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsEVERSANA (Canada)
FundersRegeneron Pharmaceuticals
KeywordsMedicineMultiple myelomaConcordanceInternal medicineOncology

Abstract

fetched live from OpenAlex

e19521 Background: Blindedindependent central review (BICR) committees are often established for oncology trials to assessbestoverall response (BOR), while real-world (RW) studies typically rely on physician-assessed responses. To emulate clinical trial rigor, a BICR committee was implemented in the R5458-ONC-21101 RW data-derived external control arm study (NCT05673967) to evaluate BOR using International Myeloma Working Group (IMWG) criteria. A pre-specified concordance analysis compared BOR assessments between the BICR committee and treating site physicians. Methods: RW data were obtained from chart reviews at 15 participating International Myeloma Foundation IMWG sites. The BICR committee, comprised of three multiple myeloma experts, evaluated BOR through consensus voting. Per protocol, the committee reviewed case report forms consisting of data on serum and urine myeloma protein and free light chain levels; and, where available, bone marrow plasma cell percentage, presence of plasmacytomas, and bone lesion changes. Concordance between BICR- and physician-assessed BOR was evaluated for objective response rate defined as ≥partial response (PR), ≥very good partial response (VGPR), ≥complete response (CR), and stringent complete response (sCR), with non-evaluable responses excluded from the analysis. Cohen’s kappa (κ) was used to measure agreement, with values >0.6 indicating strong concordance. 1 Results: Of 279 evaluable lines of therapy from 203 patients (Table), the BOR of ≥PR was 45.2% by BICR assessment and 42.3% by treating physicians (κ=0.622). Concordance improved for BOR of ≥VGPR (22.2% by BICR vs 24.7% by treating physicians; κ=0.731) but was low for BOR of ≥CR (3.9% vs. 10.8%; κ=0.508) and sCR (1.1% vs. 4.7%; κ=0.364). Conclusions: BICR- and physician-assessed responses showed strong concordance for BOR of ≥PR and ≥VGPR. However, as expected, lower concordance for ≥CR and sCR was observed, as evaluation of CR per IMWG criteria requires a bone marrow biopsy, which is rarely performed in clinical practice. While the reliability of CR and sCR in RW data is less certain, these results suggest that BOR of ≥VGPR or ≥PR may be reliably ascertained in academic settings based on treating physician evaluations. 1. Landis JR, Koch GG. Biometrics 1977;33(1):159–74. Clinical trial information: NCT05673967 . Agreement of BICR- and physician-assessed responses. BICR assessed Physician assessed Observed agreement, % Cohen’s kappa* Number of evaluable lines of therapy 279 279 - - ≥PR, n (%) 126 (45.2) 118 (42.3) 81.4 0.622 ≥VGPR, n (%) 62 (22.2) 69 (24.7) 90.3 0.731 ≥CR, n (%) 11 (3.9) 30 (10.8) 93.2 0.508 sCR, n (%) 3 (1.1) 13 (4.7) 96.4 0.364 *A kappa value >0.6 indicates strong concordance. 1

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)0.026
metaresearch head score (Gemma)0.203
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.203
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.684
GPT teacher head0.644
Teacher spread0.040 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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