Langerhans cell histiocytosis and Erdheim–Chester disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide an updated overview of the pathogenesis and treatment of Langerhans cell histiocytosis (LCH) and Erdheim-Chester disease (ECD). RECENT FINDINGS: There is ongoing debate as to the exact pathogenesis of these disorders and their classification as reactive versus neoplastic. Proinflammatory cytokines are known to play a role in both LCH and ECD and strengthen the hypothesis that, at least in part, they are disorders of immune dysregulation. The recent discovery of activating mutations in the proto-oncogene BRAF in a subset of LCH patients suggests that LCH is in fact a neoplastic disorder. Understanding of the mechanisms that promote proliferation and migration of histiocytes has led researchers to explore targeted immune-modulatory therapies for ECD. Similarly for LCH, alternative chemotherapeutic agents and reduced-intensity hematopoietic stem cell transplant are being evaluated for refractory disease. SUMMARY: More research is needed to better understand the cause of these disorders and may help in identifying new targeted therapies, particularly for patients with refractory or relapsed disease. Multinational trials are ongoing for LCH and are urgently needed for ECD.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".