Primary Central Nervous System Tumors in Adolescents: A Population-Based Study on Epidemiology and Clinical Pathways in a Challenging Age Group
Bibliographic record
Abstract
BACKGROUND: Oncological care of adolescent patients is often inconsistent, as they frequently fall between pediatric and adult services. The Childhood Cancer Registry of Campania (CCRC) is the Italian largest population-based registry specializing in children 0-19 years old, with a target population of approximately 1.1 million inhabitants. MATERIAL AND METHODS: This report presents epidemiological indicators and clinical pathways on primary brain tumors in adolescents (15-19 years) from the Campania region. RESULTS: Over the study period (2008-2020), the cohort included 219 adolescents with newly diagnosed central nervous system (CNS) tumors with an annual average incidence rate (IR) of 48.9 cases per million/year. The 5-year observed survival rate after diagnosis of CNS tumor was 84.8%. Overall, the most common tumor site was the pituitary gland and craniopharyngeal duct, representing 22.4% of all tumors. The most frequently occurring malignant primary CNS tumor was germinoma, while the most common non-malignant tumor was pituitary adenoma. Most patients were referred to adult services and nearly half migrated outside the region to receive cancer care. CONCLUSIONS: Challenges in the care of adolescent oncology patients include limited access to specialized care, difficulties in transitioning from pediatric to adult institutions, distinct tumor biology, and the underrepresentation of adolescents in clinical trials. The care of adolescents with CNS tumors is fragmented across institutions and significant variations in practice exist between adult and pediatric practitioners.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".