Molecular subtypes of anaplastic oligodendroglioma: implications for patient management at diagnosis.
Bibliographic record
Abstract
PURPOSE: In a prior study of anaplastic oligodendrogliomas treated with chemotherapy at diagnosis or at recurrence after radiotherapy, allelic loss of chromosome 1p correlated with better chemotherapeutic response and overall survival. However, in this group of patients in whom therapeutic management was not uniform, loss of 1p did not identify all chemosensitive tumors, nor did all patients whose tumors harbor a 1p loss have long survival. EXPERIMENTAL DESIGN: To clarify the clinical relevance of molecular genetic testing at the time of diagnosis for patients with anaplastic oligodendrogliomas, we studied a larger, more homogeneous group of 50 patients with histologically defined anaplastic oligodendrogliomas treated with a chemotherapeutic regimen as the principal initial therapy. RESULTS: We demonstrate that these tumors can be divided genetically into four therapeutically and prognostically relevant subgroups. Patients whose tumors have combined but isolated losses of 1p and 19q have marked and durable responses to chemotherapy associated with long survival, with or without postoperative radiation therapy. Other tumors with chromosome 1p alterations also respond to chemotherapy, but with shorter duration of response and patient survival. Tumors lacking 1p loss can also be divided into two subgroups: those with TP53 mutations, which may also respond to chemotherapy but recur quickly, and those without TP53 mutations, which are poorly responsive, aggressive tumors that are clinically and genotypically similar to glioblastomas. CONCLUSIONS: These data raise the possibility, for the first time, that therapeutic decisions at the time of diagnosis might be tailored to particular genetic subtypes of anaplastic oligodendroglioma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".