Three cases of BRAF mutation negative Erdheim-Chester disease with a challenging distinction from IgG4-related disease
Bibliographic record
Abstract
BACKGROUND: Erdheim-Chester disease (ECD) is a rare non-Langerhans histiocytosis with slow progression over the years that is particularly difficult to diagnose. CASES: Here we report three cases of ECD without BRAF mutation presenting with a renal mass, hairy kidney appearance, and a rather benign course, for which the diagnosis of ECD was delayed, characterized by multiple investigations and unsuccessful treatments attempts. In two cases the distinction from IgG4-related disease required multiple investigations and reevaluation of the clinical, radiological, histological, and immunological characteristics. CONCLUSION: A correct diagnosis of ECD may take several years and often requires revisiting previous hypotheses. Reassessment of histological slides and more modern complementary exams such as PET-CT or BRAF and MAPK-ERK mutation analysis can help to confirm the diagnosis of ECD and to select effective therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".