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Record W2564657504 · doi:10.1182/blood.v110.11.348.348

Gene Expression Signatures Predict Overall Survial in Diffuse Large B Cell Lymphoma Treated with Rituximab and Chop-Like Chemotherapy.

2007· article· en· W2564657504 on OpenAlexaff
Georg Lenz, George W. Wright, Sandeep S. Davé, Alexander Kohlmann, Wenming Xiao, John Powell, Hong Zhao, Weihong Xu, Randy D. Gascoyne, Joseph M. Connors, Lorraine F. May, Dennis D. Weisenburger, T. C. Greiner, Julie M. Vose, Jamés O. Armitage, Javeed Iqbal, Martin Bast, Kai Fu, Elı́as Campo, Emili Montserrat, Armando López‐Guillermo, Pedro Jares, Antonio Martı́nez, Betty L. Gibbs, Lisa M. Rimsza, Richard I. Fisher, Rita M. Braziel, R. Tubbs, J. E. Cook, Brad Pohlman, John Sweetenham, Gunhild Trøen, Erlend B. Smeland, Jan Delabie, Stein Kvaløy, Harald Holte, Elaine S. Jaffe, Wyndham H. Wilson, Nicole Grant, Elena Hartmann, Andreas Rosenwald, German Ott, Hans–Konrad Müller–Hermelink, T. Andrew Lister, Mickey Williams, Lothar Wieczorek, Wing C. Chan, Louis M. Staudt

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsDiffuse large B-cell lymphomaRituximabCHOPLymphomaOncologyChemotherapy regimenMedicineInternal medicineChemotherapyCancer researchBiology

Abstract

fetched live from OpenAlex

Abstract Gene expression profiling has been used to distinguish two major subtypes of diffuse large B cell lymphoma (DLBCL), termed germinal center B cell-like (GCB) DLBCL and activated B cell-like (ABC) DLBCL. Following CHOP-like chemotherapy, GCB and ABC DLBCLs had distinct 5-year survival rates of ∼60% and ∼30%, respectively. Prognostic gene expression signatures in CHOP-treated DLBCL include the lymph node signature, which reflects a non-malignant host response, the MHC class II signature, both favorable when expressed and the proliferation signature which is adverse when expressed. The addition of rituximab to CHOP chemotherapy (R-CHOP) has significantly improved the outcome for DLBCL patients. We therefore investigated, if gene expression signatures that predicted survival among DLBCL patients treated with CHOP remained predictive for DLBCL patients treated with R-CHOP. Gene expression profiling was performed on 156 samples from previously untreated patients with DLBCL using Affymetrix U133 plus arrays. All patients received rituximab and CHOP-like chemotherapy. Samples were classified as GCB DLBCL, ABC DLBCL, or unclassified, and were assessed for expression of the lymph node and proliferation signatures. A Cox-proportional hazards model was used to determine the association of these gene expression features with overall survival (OS). 71 DLBCL samples were classified as GCB DLBCL, 63 as ABC DLBCL, and 22 were unclassified. The addition of rituximab improved OS for both GCB and ABC DLBCL compared to historical controls treated with CHOP-like chemotherapy alone. After a median follow-up of 2.3 years, GCB DLBCL had a more favorable OS than ABC DLBCL, with 3-year OS rates of 86% vs. 68% (p = 0.014). The 3-year OS rate of unclassified DLBCLs was 69%. The lymph node signature was associated with favorable OS (p = 0.023) and the proliferation signature with inferior OS (p = 0.009), whereas the MHC class II signature was not associated with OS (p = 0.44). In summary, addition of rituximab to CHOP-like chemotherapy improved OS for both GCB and ABC DLBCL but ABC DLBCL remained inferior to GCB DLBCL. The prognostic value of the lymph node and proliferation signatures were maintained in the context of R-CHOP therapy. An understanding of the biological attributes of DLBCL tumors that are reflected in these gene expression signatures remains critical to our ability to improve survival of these patients.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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

Citations18
Published2007
Admission routes1
Has abstractyes

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