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Record W2949669062 · doi:10.1002/hon.99_2629

CONCORDANCE BETWEEN IMMUNOHISTOCHEMISTRY AND GENE EXPRESSION PROFILING SUBTYPING FOR DIFFUSE LARGE B‐CELL LYMPHOMA IN THE PHASE 3 PHOENIX TRIAL

2019· article· en· W2949669062 on OpenAlexaff
S. Balasubramanian, S. Wang, Chloe’ Major, B. Hodkinson, Michael Schäffer, Laurie H. Sehn, Peter Johnson, Pier Luigi Zinzani, Jodi Carey, G. Liu, Christina Loefgren, Martin Shreeve, Steven Sun, S. H. Zhuang, Jessica Vermeulen, Louis M. Staudt, Anas Younes, Wyndham H. Wilson

Bibliographic record

VenueHematological Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsCanadian Centre for Applied Research in Cancer ControlSpinal Cord Injury BC
Fundersnot available
KeywordsSubtypingImmunohistochemistryConcordanceDiffuse large B-cell lymphomaMedicineOncologyInternal medicineLymphomaGerminal centerPathologyB cellImmunologyAntibody

Abstract

fetched live from OpenAlex

Introduction: Diffuse large B-cell lymphoma (DLBCL) can be classified based on cell-of-origin (COO) into germinal center B-cell–like (GCB), activated B-cell–like (ABC), and unclassified (UNC) subtypes by gene expression profiling (GEP), and GCB and non-GCB subtypes by immunohistochemistry (IHC). In the phase 3 PHOENIX trial (NCT01855750) that enrolled untreated patients (pts) with non-GCB DLBCL by IHC, ibrutinib (ibr) + R-CHOP did not improve event-free survival (EFS) vs placebo (pbo) + R-CHOP in the intent-to-treat (ITT, non-GCB by IHC) or ABC (by GEP) populations; however, an increase in EFS and overall survival with ibr was seen in pts < 60 years (yrs), but not in pts ≥ 60 yrs due to increased toxicity in elderly pts. This work aimed to determine the concordance between IHC and GEP for DLBCL subtyping and outcomes related to subtypes. Methods: Baseline paraffin-embedded, formalin-fixed tissue samples were used to confirm non-GCB DLBCL by Hans-based IHC (Dako pharmDx™ kit) at a central laboratory. Available tumor samples were retrospectively analyzed for ABC subtype by GEP (HTG EdgeSeq DLBCL COO Assay). The concordance was evaluated by comparing non-GCB calls by IHC with ABC + UNC by GEP or GCB calls between IHC and GEP. Survival outcomes were compared between GEP subtypes in each arm and across study arms. Results: In all screened pts, 1111/1336 (83.2%) samples also provided evaluable GEP results; the concordance between GEP and IHC was 80.2% for non-GCB and 61.3% for GCB calls, resulting in an overall concordance of 76.9% (Figure), with 73.7% of non-GCB samples (by IHC) being identified as ABC by GEP. In pts < 60 yrs (n = 506), the concordance for non-GCB, GCB, and overall was 76.1%, 67.6%, and 74.3% respectively. In 747 evaluable samples from 838 enrolled non-GCB pts, 75.9% were ABC by GEP; 17.2% were GCB and 6.8% UNC. In both ITT and age < 60 yrs populations, EFS rate in GCB DLBCL by GEP was higher vs ABC in either arm, although the difference was not statistically significant and even smaller in the ibr arm. When comparing the two arms in the ITT population, EFS was similar between arms regardless of COO. In pts < 60 yrs, EFS was better with the addition of ibr to R-CHOP in ABC pts (HR 0.56 [95% CI, 0.33-0.98]; p = 0.0348; Figure); the difference between arms was not statistically significant in GCB (HR 0.64 [95% CI, 0.22-1.86; p = 0.4119) or UNC (HR 1.12 [95% CI, 0.22-5.97]) subtypes as numbers were small. Keywords: gene expression profile (GEP); ibrutinib; immunohistochemistry (IHC). Disclosures: Balasubramanian, S: Employment Leadership Position: Janssen, Pharmacyclics; Stock Ownership: Pharmacyclics, Johnson & Johnson, Gilead Sciences, Celgene, Vertex, AbbVie. Wang, S: Employment Leadership Position: Janssen; Stock Ownership: Janssen. Major, C: Employment Leadership Position: Janssen; Stock Ownership: Janssen. Hodkinson, B: Employment Leadership Position: Janssen R&D. Schaffer, M: Employment Leadership Position: Janssen; Stock Ownership: Janssen. Sehn, L: Consultant Advisory Role: Celgene, AbbVie, Seattle Genetics, TG Therapeutics, Janssen, Amgen, Roche/Genentech, Gilead Sciences, Lundbeck, Apobiologix, Karyopharm Therapeutics, Kite Pharma, Merck, Takeda Pharmaceuticals, TEVA Pharmaceuticals Industries, TG Therapeutics; Honoraria: Amgen, Apobiologix, AbbVie, Celgene, Gilead Sciences, Janssen-Ortho, Karyopharm Therapeutics, Kite Pharma, Lundbeck, Merck, Roche/Genentech, Seattle Genetics, Takeda Pharmaceuticals, TEVA Pharmaceuticals Industries, TG Therapeutics; Research Funding: Roche/Genentech (Inst). Johnson, P: Consultant Advisory Role: Janssen, Epizyme, Boehringer Ingelheim; Honoraria: Takeda Pharmaceuticals, Bristol-Myers Squibb, Novartis, Celgene, Kite Pharma, Genmab, Incyte, MorphoSys; Research Funding: Janssen, Epizyme; Other Remuneration: Combined use of Fc gamma RIIb (CD32b) and CD20-specific antibodies; WO patent, PCT/GB2011/051572; EU11760819.0. Zinzani, P: Honoraria: Servier, Bristol-Myers Squibb, Gilead, Jansen, Merck Sharp & Dohme, Celltrion, Celgene, Roche; Other Remuneration: Verastem, Servier, Bristol-Myers Squibb, Gilead, Janssen, Merck Sharp & Dohme, Celltrion, Celgene, Roche. Carey, J: Employment Leadership Position: Janssen Research and Development; Stock Ownership: Johnson & Johnson. Liu, G: Employment Leadership Position: Janssen. Loefgren, C: Employment Leadership Position: Janssen; Stock Ownership: Janssen. Shreeve, M: Employment Leadership Position: Janssen; Stock Ownership: Johnson & Johnson, Pfizer. Sun, S: Employment Leadership Position: Johnson & Johnson; Stock Ownership: Johnson & Johnson. Zhuang, S: Employment Leadership Position: Janssen Research & Development; Stock Ownership: Johnson & Johnson. Vermeulen, J: Employment Leadership Position: Janssen; Stock Ownership: Janssen. Staudt, L: Other Remuneration: Patents and patents pending regarding gene expression profiling in lymphoma that have been licensed by Nanostring and for which I receive royalties. Younes, A: Consultant Advisory Role: BMS, Incyte, Janssen, Genentech and Merck; Honoraria: Merck, Roche, Takeda Pharmaceuticals, Janssen, AbbVie; Research Funding: Janssen (Inst), Curis (Inst), Pharmacyclics (Inst), Roche (Inst), AstraZeneca (Inst), Genentech (Inst).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.361
Teacher spread0.327 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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