06 Prognostic factors for survival and recurrence in adult medulloblastoma
Bibliographic record
Abstract
BACKGROUND: Adult medulloblastomas account for less than 1% of adult neoplasms. They are challenging to treat due to their rarity and the heterogeneity of treatment options, all of which have limited evidence. In this retrospective review, we examined cases of adult medulloblastoma diagnosed in Alberta during a 70-year period. METHODS: We reviewed the charts of patients diagnosed with medulloblastoma between 1944 and 2014. We performed Cox and logistic regression analysis to elucidate features that may influence recurrence risk and survival. RESULTS: We found 86 and analyzed 78 cases. The median age at diagnosis was 27 (range 16 to 71). Most were male (68%). Most had surgery (92%). By COG risk stratification, 54% were standard risk while 21% were poor risk. RT was administered to 85% of patients, and craniospinal irradiation (CSI) to 81%. Chemotherapy was administered to 48%. Median survival was 4.4 years from diagnosis (range 0 to 20). At last follow-up, 39% were alive and recurrence-free. Patients who had CSI and posterior fossa boost had longer survival (p=0.047 and<0.01, respectively) and were less likely to recur (p=0.041 and<0.01). Chemotherapy was also associated with decreased recurrence (p=0.025). CONCLUSIONS: Medulloblastomas carry a significant recurrence risk, especially for patients who had subtotal resection. CSI and posterior fossa boost were associated with fewer recurrences and improved survival. COG risk stratification, Chang staging, desmoplastic histology, vermian location, 4th ventricle involvement, tumor enhancement, presence of hydrocephalus and cerebrospinal fluid (CSF) involvement are not significantly prognostic.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".