Melanocytic nevi are associated with neurofibromas in neurofibromatosis, type I, but not sporadic neurofibromas. A study of 226 cases*
Bibliographic record
Abstract
BACKGROUND: Neurofibromatosis, type 1, is associated with cutaneous melanin pigmentation, but an association with ordinary melanocytic nevi has not been described. METHODS: This retrospective case-control study was designed to see if neurofibromas in patients with neurofibromatosis, type 1 (NF-1) differ from sporadic neurofibromas (SN) in their incidence of associated melanocytic nevi and other histologic features. Slides from 114 NF-1 were compared with 112 SN and 300 intradermal melanocytic nevi (IDN). RESULTS: Small lentiginous melanocytic nevi were identified over 13 NF-1 (11%) but no SN (P=0.0002). Compared with other NF-1, NF-1 with nevi were more frequently associated with melanocytic hyperplasia, giant melanosomes and diffuse neurofibroma (P<0.03). Compared with SN, NF-1 were also more frequently associated with melanocytic hyperplasia, lentigo simplex-like changes, diffuse neurofibroma and plexiform neurofibroma (P<0.001). Sebaceous hyperplasia (14%), dermal elastosis (9%), lipomatous change (8%), epithelial cysts (4%) and keratin granulomas or folliculitis (3%) were not significantly different in prevalence between NF-1, SN and the control group of IDN. CONCLUSIONS: This study suggests that there is a difference in the potential for melanocytic proliferation in NF-1 compared with SN. NF-1, SN and IDN are associated with a similar range of incidental histologic changes. Ball NJ, Kho GT. Melanocytic nevi are associated with neurofibromas in neurofibromatosis, type 1, but not sporadic neurofibromas. A study of 226 cases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".