Brazilian pediatric patients with gliomas: treatment characteristics and survival outcomes
Bibliographic record
Abstract
Background: The current study aimed to determine the overall survival (OS) rates of patients diagnosed with pediatric gliomas in Brazil, accounting for the influence of age, treatment modalities, and tumor site, using a population-based national database. Materials and methods: Patients diagnosed with pediatric gliomas of central nervous system (CNS) from 1999-2020 were identified from The Fundação Oncocentro de São Paulo public database. The Kaplan-Meier and the log-rank test were used for survival analysis. Results: A total of 1296 patients were included. The most common histologic tumor types were glioblastomas (38.27%; n = 496), pilocytic astrocytoma (32.87%; n = 426), and astrocytoma grade II (20.76%; n = 269). A total of 379 (29.24%) had brainstem tumors. The mean follow-up was 135 months [95% confidence interval (CI) 128-142\. The 1-year, 3-year 5-year OS for pilocytic astrocytoma were 93.72%, 89.98%, and 88.97%; for grade II gliomas, 80.36%, 71.89%, and 68.60%; for grade III gliomas, 53.72%; 31.87%, and 28.33%; and for glioblastoma, 52.90%, 28.76%, 25.20%, respectively. Brainstem tumors had the worse OS compared to no brainstem tumors (p = 0.001). For high-grade glioma (grade III/IV), excluding brainstem tumors (n = 570), young patients had greater median OS (0 to 3 years:22 months; 4 to 18 years:13 months; p = 0.005). Regarding the treatment modalities, combined treatments were associated with higher median survival compared to less intensive therapy (surgery: 11 months; surgery and chemotherapy: 16 months; surgery, radiotherapy, and chemotherapy: 20 months; p = 0.005). Conclusion: In our cohort, low-grade gliomas had favorable prognoses and outcomes. Patients diagnosed with glioblastomas and brainstem gliomas had the worst OS. For high-grade gliomas, undergoing treatment de-intensification in the Brazilian pediatric population is associated with worse survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".