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Record W2990206078 · doi:10.1182/blood-2019-124443

Clinical Impact of Ibrutinib with R-CHOP in Untreated Non-GCB DLBCL Co-Expressing BCL2 and MYC Genes in the Phase 3 Phoenix Trial

2019· article· en· W2990206078 on OpenAlexaff
Peter Johnson, Sriram Balasubramanian, Brendan P. Hodkinson, Michael Schäffer, Lori Parisi, S. Martin Shreeve, Steven Sun, Jessica Vermeulen, Laurie H. Sehn, Louis M. Staudt, Anas Younes, Wyndham H. Wilson

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsSpinal Cord Injury BC
Fundersnot available
KeywordsHazard ratioInternal medicineMedicinePopulationOncologyCHOPDiffuse large B-cell lymphomaIbrutinibVincristineRituximabCyclophosphamideLymphomaConfidence intervalLeukemiaChronic lymphocytic leukemiaChemotherapy

Abstract

fetched live from OpenAlex

Introduction In the phase 3, double-blind, placebo (pbo)-controlled PHOENIX trial (NCT01855750), 838 patients (pts) with non-germinal center B-cell-like (non-GCB) diffuse large B-cell lymphoma (DLBCL) were randomized 1:1 to ibrutinib (IBR; 560 mg/day orally) + rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) or pbo + R-CHOP. IBR + R-CHOP did not improve event-free survival (EFS) in the intent-to-treat (ITT) non-GCB population (hazard ratio [HR] 0.934; 95% confidence interval [CI], 0.726-1.200). However, in an exploratory analysis, pts < 60 years benefited from the addition of IBR (HR 0.579; 95% CI, 0.380-0.881 for EFS), whereas pts ≥ 60 years did not (HR 1.228; 95% CI, 0.887-1.699 for EFS) due to increased toxicity and reduced R-CHOP exposure. Based on evidence that co-expression of BCL2 and MYC by immunohistochemistry (IHC) have a worse outcome with R-CHOP, we examined their clinical prognostic effect in the 2 arms of the PHOENIX trial. Methods Pretreatment formalin-fixed paraffin-embedded biopsy samples were collected. RNA was extracted and profiled with Illumina RNAseq. Raw sequence reads were aligned to the hs37d5 genome build with STAR v2.5.1b, and gene-level quantification was conducted using RSEM v1.2.23. The median transcript per million mapped reads (TPM) values for BCL2 and MYC gene expression across all pts with RNAseq data (n = 766) were used as the cutoffs between high and low expression for each gene. BCL2 IHC data were available from 184 pts, and based on these, the threshold expression value from RNAseq data that could best approximate positive calls from IHC (≥ 50% lymphoma cells positive) was determined. This threshold value was very close to the median level calculated above and therefore supported the use of the median expression levels as the cutoffs to define high and low expressors in the subsequent analyses. The relationship between expression by RNAseq and survival (EFS, overall survival [OS]) in the 2 study arms was analyzed by Kaplan-Meier estimate with Cox regression to determine HRs and log-rank testing to assess significance. Results Based on a cutoff at the median TPM value, the percentage of non-GCB pts with BCL2-high + MYC-high (n = 234, 30.5%) was consistent with previous literature. In the IBR + R-CHOP (n = 386) and pbo + R-CHOP (n = 380) arms, respectively, 123 (31.9%) and 111 (29.2%) pts were MYC-high + BCL2-high by RNAseq. In the pbo + R-CHOP arm, pts with MYC-high + BCL-2-high had worse EFS (HR 1.820; 95% CI, 1.264-2.620; p = 0.0011) and OS (HR 1.662; 95% CI, 1.014-2.724; p = 0.0415) versus those with low expression of 1 or both markers in the ITT population (Figure), consistent with known poor outcomes associated with these genes. However, there was no difference in outcome for high versus low expression of these genes in the IBR + R-CHOP arm in the ITT population. In the ITT population, pts with MYC-high + BCL2-high had better EFS (HR 0.648; 95% CI, 0.423-0.993; p = 0.045) with IBR + R-CHOP versus pbo + R-CHOP, but there was no significant difference in OS (HR 0.783; 95% CI, 0.446-1.372; p = 0.39; Figure). We also examined the outcome of the 97 (30.6%) pts < 60 years of age (n = 317) with MYC-high + BCL2-high and observed an improved EFS and OS with IBR + R-CHOP versus pbo + R-CHOP (HR 0.393; 95% CI, 0.198-0.780; p = 0.0056 for EFS; HR 0.191; 95% CI, 0.055-0.666; p = 0.0037 for OS; Figure). There was no significant difference in EFS or OS in pts < 60 years with MYC-low + BCL2-low or in pts ≥ 60 years with MYC-high + BCL2-high in the 2 arms. Conclusions In this exploratory analysis, IBR was associated with improved EFS in combination with R-CHOP compared with pbo + R-CHOP in pts with MYC-high + BCL2-high expression in the ITT (non-GCB) population, without a significant improvement in OS. In pts aged < 60 years, both EFS and OS were significantly better with IBR, while there was no significant difference in older pts. These data suggest that IBR + R-CHOP may particularly benefit pts with MYC-high + BCL2-high-expressing lymphomas, a hypothesis warranting further testing in other DLBCL cohorts. Disclosures Johnson: Novartis: Honoraria; Genmab: Honoraria; Kite: Honoraria; Celgene: Honoraria; Takeda: Honoraria; Bristol-Myers Squibb: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Epizyme: Honoraria, Research Funding; Incyte: Honoraria; Boehringer Ingelheim: Honoraria. Balasubramanian:Janssen: Employment; Johnson & Johnson: Equity Ownership; Gilead Sciences: Equity Ownership; Celgene: Equity Ownership; Vertex: Equity Ownership; AbbVie: Equity Ownership. Hodkinson:Janssen: Employment. Schaffer:Johnson & Johnson: Equity Ownership; Janssen: Employment. Parisi:Janssen: Employment. Shreeve:Johnson & Johnson: Equity Ownership; Janssen: Employment. Sun:Janssen: Employment; Johnson & Johnson: Equity Ownership. Vermeulen:Johnson & Johnson: Equity Ownership; Janssen: Employment. Sehn:Abbvie: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Janssen-Ortho: Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; Janssen-Ortho: Honoraria; Lundbeck: Consultancy, Honoraria. Staudt:Nanostring: Patents & Royalties. Younes:AstraZeneca: Research Funding; Biopath: Consultancy; Genentech: Research Funding; Pharmacyclics: Research Funding; Syndax: Research Funding; BMS: Research Funding; HCM: Consultancy; Epizyme: Consultancy, Honoraria; Xynomics: Consultancy; Roche: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Janssen: Honoraria, Research Funding; Curis: Honoraria, Research Funding; Merck: Honoraria, Research Funding; Abbvie: Honoraria; Takeda: Honoraria.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.036
GPT teacher head0.417
Teacher spread0.381 · 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 designRandomized trial
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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Citations12
Published2019
Admission routes1
Has abstractyes

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