Massive plexiform neurofibromas in childhood: natural history and management issues
Bibliographic record
Abstract
OBJECT: The authors review their experience with massive plexiform neurofibromas (PNs) in patients with pediatric neurofibromatosis Type 1 (NF1) to better characterize the natural history and management of these complex lesions. METHODS: The authors performed a retrospective review of data obtained in seven patients with NF1 in whom massive PNs were diagnosed at The Hospital for Sick Children in Toronto, Ontario, Canada. These patients attended routine follow-up examinations conducted by a number of specialists, and serial neuroimaging studies were obtained to monitor disease progression. The most common presenting feature of PN was that of a painful, expanding lesion. Furthermore, two patients harbored multiple, distinct PNs affecting different body sites. With respect to management, two patients were simply observed, undergoing serial neuroimaging studies; two patients underwent biopsy sampling of their plexiform lesions; two patients underwent attempted medical treatment (farnesyl transferase inhibitor, R11577, and cyclophosphamide chemotherapy); and three patients required surgical debulking of their PNs because the massive growth of these tumors caused functional compromise. Ultimately, one patient died of respiratory complications due to progressive growth of the massive PN lesion. CONCLUSIONS: In this review of their experience, the authors found certain features that underscore the presentation and natural history of PNs. The management of these complex lesions, however, remains unclear. Slow-growing PNs may be observed conservatively, but the authors' experience suggests that resection should be considered in selected cases involving significant deterioration or functional compromise. Nevertheless, patients with massive PNs will benefit from close surveillance by a team of specialists to monitor for ongoing disease progression.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".