Characterization of recurrence patterns and outcomes of medulloblastoma in adults: The University of Texas MD Anderson Cancer Center experience
Bibliographic record
Abstract
Abstract Background Medulloblastoma in adults is rare and treatment decisions are largely driven from pediatric literature. We sought to characterize recurrent medulloblastoma in adults. Methods From a single-institution dataset of 200 adult patients diagnosed with medulloblastoma during 1978–2017, those with recurrence were analyzed for clinical features, treatment, and outcome. Results Of the 200 patients, 82 (41%) with median age of 29 years (18–59) had recurrence after a median follow-up time of 8.4 years (95% CI = 7.1, 10.3). Of these, 30 (37%) were standard-risk, 31 (38%) were high-risk, and 21 (26%) had unknown-risk diseases at the time of initial diagnosis. Forty-eight (58%) presented with recurrence outside the posterior fossa, of whom 35 (43%) had distant recurrence only. Median Progression-free survival (PFS) and OS from initial surgery were 33.5 and 62.4 months, respectively. Neither PFS nor OS from initial diagnosis differed between the standard-risk and high-risk groups in those who experience recurrence (P = .505 and .463, respectively). Median OS from first recurrence was 20.3 months, also with no difference between the standard-risk and high-risk groups (P = .518). Recurrences were treated with combinations of re-resection (20 patients; 25%), systemic chemotherapy (61 patients; 76%), radiation (29 patients; 36%), stem cell transplant (6 patients; 8%), and intrathecal chemotherapy (4 patients; 5%). Patients who received radiation at recurrence had better OS (32.9 months) than those who did not (19.2 months) (P = .034). Conclusions Recurrent medulloblastoma in adults has a poor prognosis irrespective of initial risk stratification. Recurrence commonly arises outside the posterior fossa years after initial diagnosis.
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 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) | 0.000 | 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) | 0.001 | 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".