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Neutrophil elastase mutations and risk of leukaemia in severe congenital neutropenia

2007· article· en· W2167772724 on OpenAlexaff
Philip S. Rosenberg, Blanche P. Alter, Daniel C. Link, Steven Stein, Elin Rodger, Audrey Anna Bolyard, Andrew A.G. Aprikyan, Mary Ann Bonilla, Yigal Dror, George Kannourakis, Peter E. Newburger, Laurence A. Boxer, David C. Dale

Bibliographic record

VenueBritish Journal of Haematology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsHospital for Sick Children
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsCongenital NeutropeniaNeutropeniaMedicineInternal medicineNeutrophil elastaseCyclic neutropeniaBone marrow failureAbsolute neutrophil countBone marrowGranulocyte colony-stimulating factorImmunologyMyeloidChemotherapyHaematopoiesisBiologyGeneticsInflammationStem cell

Abstract

fetched live from OpenAlex

Severe congenital neutropenia (SCN) is a heterogeneous bone marrow failure syndrome predisposing to myelodysplastic syndrome and acute myeloid leukaemia (MDS/AML). We studied 82 North American and Australian SCN patients enrolled in the Severe Chronic Neutropenia International Registry who were on long-term treatment with granulocyte colony-stimulating factor and for whom the neutrophil elastase (ELA2) gene was sequenced. There was no significant difference in the risk of MDS/AML in patients with mutant versus wild-type ELA2: the respective cumulative incidences at 15 years were 36% and 25% (P = 0.96). Patients with either mutant or wild-type ELA2 should be followed closely for leukaemic transformation.

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)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.004
GPT teacher head0.226
Teacher spread0.222 · 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

Citations97
Published2007
Admission routes1
Has abstractyes

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