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Record W2143651540 · doi:10.3109/10428194.2015.1034699

Isolated<i>MYC</i>cytogenetic abnormalities in diffuse large B-cell lymphoma do not predict an adverse clinical outcome

2015· article· en· W2143651540 on OpenAlexaff
Gabriel C. Caponetti, Bhavana J. Davé, Anamarija M. Perry, Lynette M. Smith, Smrati Jain, Paul N. Meyer, Martin Bast, Philip J. Bierman, R. Gregory Bociek, Julie M. Vose, Jamés O. Armitage, Patricia Aoun, Kai Fu, Timothy C. Greiner, Wing C. Chan, Warren G. Sanger, Dennis D. Weisenburger

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2015
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBCL6Fluorescence in situ hybridizationLymphomaDiffuse large B-cell lymphomaInternal medicineMedicineOncologyCancer researchBiologyB cellImmunologyGeneGenetics

Abstract

fetched live from OpenAlex

In this study, we investigated the significance of MYC, BCL2 and BCL6 gene abnormalities in a cohort of 205 diffuse large B-cell lymphoma (DLBCL) patients studied by conventional and/or fluorescence in situ hybridization cytogenetic analysis. Combining these methods, 172 cases (84%) were classified as MYC-, 17 (8%) were MYC+/BCL2-/BCL6-, and 16 (8%) were double/triple-hit lymphomas (i.e. MYC+/BCL2+, MYC+/BCL6+, or MYC+/BCL2+/BCL6+). We found a significant difference in event-free survival (EFS) among the three groups (p = 0.02), with the double/triple-hit group having the worst EFS. Patients who were MYC+, but BCL2- and BCL6-, had the best EFS. We conclude that patients with MYC+ DLBCL, but without BCL2 or BCL6 abnormalities, do not have a worse outcome when compared to those who are MYC-. However, patients with double/triple-hit DLBCL have a very poor outcome and should be treated with aggressive or novel therapies.

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 score0.003

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 head0.037
GPT teacher head0.306
Teacher spread0.268 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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