Chronic neutrophilic leukemia: 2020 update on diagnosis, molecular genetics, prognosis, and management
Bibliographic record
Abstract
DISEASE OVERVIEW: Chronic neutrophilic leukemia (CNL) is a rare, often aggressive myeloproliferative neoplasm (MPN) defined by persistent mature neutrophilic leukocytosis, bone marrow granulocyte hyperplasia, and frequent hepatosplenomegaly. The seminal discovery of oncogenic driver mutations in colony-stimulating factor 3 receptor (CSF3R) in the majority of patients with CNL in 2013 anchored a new scientific framework, deepening our understanding of its molecular pathogenesis, providing a diagnostic biomarker, and rationalizing the use of pharmacological targeting. DIAGNOSTIC CRITERIA: /L comprising >80% neutrophils with <10% circulating precursors and rare blasts, and absence of dysplasia or monocytosis, while not fulfilling criteria for other MPN. DISEASE UPDATES: Increasingly comprehensive genetic profiling of CNL has disclosed a complex genomic landscape and additional prognostically relevant mutational combinations. Though prognostic determination and therapeutic decision-making remain challenging, emerging data on prognostic markers and the use of newer therapeutic agents, such as JAK inhibitors, are helping to define state-of-the-art management in CNL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".