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Record W2548326868 · doi:10.1182/blood.v110.11.52.52

LMO2 Protein Expression Predicts Survival in Patients with Diffuse Large B-Cell Lymphoma in the Pre- and Post-Rituximab Treatment Eras.

2007· article· en· W2548326868 on OpenAlexaff
Yasodha Natkunam, Pedro Farinha, Eric D. Hsi, Christine P. Hans, Robert Tibshirani, Laurie H. Sehn, Joseph M. Connors, Shuchun Zhao, Brad Pohlman, John Spinelli, Martin Bast, Arnon Nagler, Ronald Levy, Randy D. Gascoyne, Izidore S. Lossos

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsDiffuse large B-cell lymphomaRituximabMedicineInternal medicineCHOPLymphomaOncologyGerminal centerAnthracyclineTissue microarrayBCL6Chemotherapy regimenInternational Prognostic IndexRegimenChemotherapyImmunohistochemistryImmunologyCancerB cellAntibody

Abstract

fetched live from OpenAlex

Abstract Finding new prognostic markers in diffuse large B-cell lymphoma (DLBCL) is of importance because the disease is heterogeneous and current therapies fail to cure many affected patients. Previously, we showed that the expression of LMO2 mRNA was the strongest single predictor of superior outcome in patients with DLBCL in a multivariate model based on the expression of six genes (Lossos et al, NEJM 2004). Subsequently, we generated an anti-LMO2 monoclonal antibody and showed that LMO2 protein is expressed in a subset of germinal center-derived B-cell lymphomas including DLBCL, and that its expression predicted a superior outcome in DLBCL patients who were treated with anthracycline-based regimens (Natkunam et al, Blood 2006 & 2007). We have now expanded this cohort to include DLBCL patients treated at five international medical centers and have also tested the prognostic impact of LMO2 in patients treated with the addition of rituximab to CHOP (R-CHOP), a regimen which was recently demonstrated to improve the outcome of DLBCL patients (Coiffier et al, NEJM 2002; Sehn et al, JCO 2005; Habermann et al, JCO 2006; Pfreundschuh et al, Lancet Oncol 2006). Immunohistochemistry for LMO2 was performed on tissue microarrays containing cores of diagnostic biopsy specimens from patients with de novo DLBCL treated with anthracycline-based chemotherapy (280 patients) or with R-CHOP (80 patients) who had been followed for clinical outcome. The results show that in the pre-rituximab group staining for LMO2 was strongly correlated with overall survival (OS) and progression-free survival (PFS) (p=0.0018 and p=0.00071, respectively). Similarly, in the post-rituximab group LMO2 protein expression was associated with a significantly longer OS (p=0.0048) and PFS (p=0.0087). In multivariate Cox regression analyses, the expression of the LMO2 protein was found to be independent of the clinical IPI and most strikingly, was more robust than the conventional IPI in predicting OS and PFS, particularly in the post-rituximab DLBCL group of patients (OS p = 0.03, PFS p = 0.01). The capacity of LMO2 protein to identify DLBCL patients with improved outcome in an IPI-independent manner indicates its potential role in risk stratification of this disease. We conclude that the prognostic value of LMO2 protein expression remains significant in the era of R-CHOP treatment and recommend its assessment in all newly diagnosed DLBCL patients to confirm these results and eventually to optimize patient management.

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 score0.002

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)0.0010.000

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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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