Rosai–Dorfman–Destombes disease of the nervous system: a systematic literature review
Bibliographic record
Abstract
Abstract Background Rosai–Dorfman–Destombes disease (RDD) is a rare histiocytic disorder with heterogeneous clinical manifestations and rare neurologic involvement. The existing clinical literature about neurologic RDD has yet to be critically examined. Methods We performed a four-database English-language systematic literature search for cases of RDD neurohistiocytosis, excluding secondary literature. Individual patient data for neurologic symptoms, disease sites, treatments, and responses were captured. Responses to first-line and second-line surgical interventions, post-surgical radiotherapy, and systemic therapies were analyzed. Results Among 4769 articles yielded by literature search, 154 articles were fully reviewed, containing data on 224 patients with neurologic RDD. 128 (83.1%) articles were single case reports. 149 (66.5%) patients were male, 74 (33.5%) female, with a median age of 37.6 years (range 2–79). Presenting neurologic symptoms included headache (45.1%), focal neurological deficits (32.6%), visual symptoms (32.1%), and seizures (24.6%). RDD involvement was multifocal in 32 (14.3%) cases. First-line treatment involved resection in 200 (89.6%) patients, with subsequent progression in 52 (26%), including 41 (78.8%) with unifocal disease. No difference was observed in progression-free survival comparing post-operative radiotherapy to no radiotherapy following partial resection. Chemotherapy given alone as first-line treatment led to complete or partial response in 3/7(43%) patients. Second-line treatments led to complete or partial response in 18/37(37.5%) patients. Mutational data were reported on 10 patients (4.46%). Conclusions This review highlights the limited published data about neurologic RDD, which presents with varied symptomatology and outcome. Further study is needed about its mutational landscape, and more effective therapies are needed for recurrent and refractory disease.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".