The Value of Etoposide for Recurrent Glioma
Bibliographic record
Abstract
BACKGROUND: For multiply recurrent glioma, options are few and choices are very limited. Etoposide in combination with carboplatin and/or bevacizumab has been evaluated in recurrent glioma with modest efficacy. This retrospective study describes the efficacy of etoposide monotherapy in adults with multiply recurrent diffuse glioma. 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, treatment-related toxicity was recorded. RESULTS: Totally, 48 patients with a median age 43 years-old (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 = 0.15). Etoposide was stopped due to progression in the majority of the patients (81.3%). Only 1 patient had a grade 3 toxicity. CONCLUSION: Etoposide is a well-tolerated chemotherapy in heavily pretreated patients with multiply recurrent glioma and could be considered when other options are not available. OS was 4 months after initiating etoposide.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".