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Record W4416256839 · doi:10.3171/2025.6.jns25872

Malignant peripheral nerve sheath tumors in schwannomatosis: a case series

2025· article· en· W4416256839 on OpenAlexaffabout
Ken Porche, Kirsten M. Hayford, Chloe Gui, Suganth Suppiah, Robert J. Spinner

Bibliographic record

VenueJournal of neurosurgery · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMalignant peripheral nerve sheath tumorPeripheral nerveNerve sheathNerve sheath neoplasmPeripheralRadiation therapySurgical resectionResection

Abstract

fetched live from OpenAlex

OBJECTIVE: Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas predominantly associated with neurofibromatosis type 1 (NF1). However, their occurrence within NF type 2 (NF2)-related and SMARCB1-related schwannomatosis remains rare and poorly characterized. Accurate and timely diagnosis is challenging due to clinical and radiological similarities with benign schwannomas, potentially delaying appropriate management and impacting outcomes. This study presents an institutional case series aiming to better characterize the clinical presentations specifically for MPNSTs arising in patients with NF2- and SMARCB1-related schwannomatosis. METHODS: This retrospective case series included patients diagnosed with schwannomatosis who subsequently developed histopathologically confirmed MPNSTs. Conducted at Mayo Clinic (Rochester, Minnesota) and University Health Network (Toronto, Canada), the study spanned January 1, 2003, to November 1, 2024. Patients were selected based on clinical or genetic diagnoses of schwannomatosis using International Consensus Group on Neurofibromatosis Diagnostic Criteria. Comprehensive clinical, radiological, and pathological data, including demographics, presenting symptoms, tumor features (size, location, immunohistochemistry, genetics), treatments (resection, chemotherapy, radiotherapy), and follow-up outcomes were extracted from electronic medical records. RESULTS: The authors identified 8 patients with a mean age of 36 years, half of whom had NF2-related schwannomatosis. The most common presenting symptom was pain (71%). The mean tumor size was 8.2 ± 7.0 cm, with gross-total resection being the most common surgical treatment (67%), typically supplemented with radiation therapy (78%). More than half of the patients (56%) exhibited metastatic disease, and all tumors with reported grading were Fédération Nationale des Centres de Lutte Contre le Cancer grade 3. No tumors were associated with LZTR1 mutations. One notable case involved a 39-year-old male with SMARCB1-related schwannomatosis who had a femoral MPNST resected 13 years prior and subsequently developed a sciatic nerve MPNST that was managed successfully with neoadjuvant chemotherapy, radiation therapy, and negative margin resection. Of note, the second lesion arose from a hybrid neurofibroma/schwannoma. Another case, a 33-year-old male with SMARCB1-related schwannomatosis, had an incidental finding of epithelioid MPNST in a minimally symptomatic small palmar lesion. CONCLUSIONS: This case series highlights that MPNSTs, although uncommon, can arise in NF2- and SMARCB1-related schwannomatosis without prior radiation exposure, presenting significant diagnostic challenges due to their similarity to benign schwannomas. The findings underscore the importance of maintaining clinical vigilance and employing individualized management strategies, balancing thorough resection with the preservation of function and patient quality of life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.019
GPT teacher head0.269
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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