A case series of pediatric survivors of anaplastic pleomorphic xanthoastrocytoma
Bibliographic record
Abstract
Abstract Background Anaplastic pleomorphic xanthoastrocytoma (APXA) is a rare subtype of CNS astrocytoma. They are generally treated as high-grade gliomas; however, uncertainty exists regarding the optimal therapy. Here, we report on 3 pediatric cases of APXA. Methods Our institutional database was queried for cases of APXA and 3 cases were identified. Surgical samples were processed for methylation profiling and chromosomal microarray analysis. Methylation data were uploaded to the online CNS tumor classifier to determine methylation-based diagnoses to determine copy number variations (CNVs). Results Two patients were male, 1 female, and all were aged 12 years at diagnosis. All underwent a gross total resection (GTR) and were diagnosed with an APXA. Immunohistochemical analysis demonstrated that 2 cases were BRAF V600E positive. Methylation-based tumor classification supported the APXA diagnosis in all cases. CNV analyses revealed homozygous CKDN2A deletions in all and chromosome 9p loss in 2 cases. All patients received radiation therapy (54 Gy in 30 fractions) with concurrent temozolomide. Two patients received maintenance chemotherapy with temozolomide and lomustine for 6 cycles as per the Children’s Oncology Group ACNS0423. The third patient recurred and went on to receive a second GTR and 6 cycles of lomustine, vincristine, and procarbazine. All are alive with no evidence of disease >4 years post-treatment completion (overall survival = 100%, event free survival = 67%). Conclusions The natural history and optimal treatment of this rare pediatric tumor are not well understood. This case series supports the use of adjuvant chemoradiotherapy in the treatment of APXA. The genetic landscape may be informative for optimizing treatment and prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".