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Record W2164059454 · doi:10.3324/haematol.2011.040840

TET2 mutations in secondary acute myeloid leukemias: a French retrospective study

2011· article· en· W2164059454 on OpenAlexfundno aff
Olivier Kosmider, Éric Delabesse, Véronique Mansat‐De Mas, Pascale Cornillet‐Lefèbvre, Odile Blanchet, Alain Delmer, C. Récher, Stéphane Raynaud, Didier Bouscary, F Viguié, C. Lacombe, Olivier Bernard, Norbert Ifrah, François Dreyfus, Michaëla Fontenay

Bibliographic record

VenueHaematologica · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
FundersInstitute of Cancer ResearchInstitut National Du Cancer
KeywordsMyeloid leukemiaMedicineChromosomal translocationMyeloidRetrospective cohort studyInternal medicineKaryotypeMutationHematologyOncologyGastroenterologyImmunologyCancer researchGeneBiologyGeneticsChromosome

Abstract

fetched live from OpenAlex

Ten-eleven translocation 2 (TET2) mutations have been involved in myeloid malignancies. This retrospective study aims at evaluating the frequency and impact of TET2 mutations in 247 secondary acute myeloid leukemia cases referred to as myelodysplasia-related changes (n=201) or therapy-related (n=46) leukemias. Mutation of at least one copy of the TET2 gene was detected in 49 of 247 (19.8%) patients who presented with older age, higher hemoglobin level, higher neutrophil and monocyte counts, and lower platelet count. TET2 mutations were significantly less frequent in therapy-related (8.7%) than myelodysplasia-related changes (22.3%; P=0.035) leukemias and strongly associated with normal karyotype (P<0.001). TET2 mutations did not significantly associate with NPM1, FLT3-ITD or FLT3-D835, WT1, or N- or K-RAS mutations. Complete remission was achieved in 57% of evaluable patients who had received intensive chemotherapy. In this group, TET2 mutations did not influence the complete remission rate or overall survival.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.307
Teacher spread0.266 · 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.

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

Citations40
Published2011
Admission routes1
Has abstractyes

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