Uncommon histiocytic disorders: The non‐Langerhans cell histiocytoses
Bibliographic record
Abstract
BACKGROUND: Histiocytic disorders are currently identified by their component cells. The non-Langerhans Cell Histiocytoses (non-LCH) are a group of disorders defined by the accumulation of histiocytes that do not meet the phenotypic criteria for the diagnosis of Langerhans cells (LCs). The non-LCH consist of a long list of diverse disorders which have been difficult to categorize. A conceptual way to think of these disorders that make them less confusing and easier to remember is proposed based on immunophenotyping and clinical presentation. RESULTS: Clinically the non-LCH can be divided into 3 groups, those that predominantly affect skin, those that affect skin but have a major systemic component, and those that primarily involve extracutaneous sites, although skin may be involved. Immunohistochernically many of the non-LCH appear to arise from the same precursor cell namely the dermal dendrocyte. Juvenile Xanthogranuloma (JXG) is the model of the dermal dendrocyte-derived non-LCH. Other non-LCH with differing clinical presentation and occurring at different ages but with an identical immunophenotype appear to form a spectrum of the same disorder, deriving from the same precursor cell at different stages of maturation. They should be considered as members of a JXG family. Non-JXG family members include Sinus histiocytosis with massive lymphadenopathy (Rosai-Dorfman disease). CONCLUSION: The non-LCH can be classified as JXG family and non-JXG family and subdivided according to fairly clear-cut clinical criteria. Utilization of this type of approach will allow better categorization, easier review of the literature and more accurate therapy decision-making.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".