P17.01.A THE VALUE OF ETOPOSIDE FOR RECURRENT GLIOMA
Bibliographic record
Abstract
Abstract BACKGROUND There is currently no consensus on how best to treat diffuse glioma in adults at recurrence. Etoposide in combination with carboplatin and/or bevacizumab has been evaluated in recurrent glioma with modest efficacy. This retrospective study investigates the efficacy of etoposide monotherapy in adults with recurrent diffuse glioma. MATERIAL AND METHODS In this single center retrospective series, all adult patients with radiographically proven multiply recurrent diffuse glioma (WHO grade 2-4) treated with etoposide between 2016 and 2020 were evaluated. Progression-free survival (PFS) and overall survival (OS) after initiating etoposide were calculated for the total group and for different histologic tumor types. In addition, toxicity was recorded after initiation of etoposide. RESULTS 48 patients with a median age 43 (range 24-78) were included. Etoposide was given as 3rd line of treatment in 18 patients (37.5%) and as 4th or 5th line of treatment in 30 patients (62.5%). The majority were diagnosed with a glioblastoma, WHO grade 4 (27, 56.3%). The median PFS was 8.6 weeks (95% confidence interval [CI]: 8.3-8.9). The median OS of the total population was 4.0 months (95% CI: 2.4-5.6). Patients with an oligodendroglioma had the best OS (median 13 months), compared to astrocytoma and glioblastoma, but the difference was not statistically significant (p=0.152). Etoposide was stopped due to progression or toxicity. Only 1 patient had a grade 3 toxicity. CONCLUSION Etoposide is a well-tolerated chemotherapy in adult patients with recurrent diffuse glioma, but has limited efficacy in this cohort of multiply recurrent and heavily pretreated patients.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.003 |
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".