LINC-21. SURVEY ON THE RESOURCES AVAILABLE FOR PEDIATRIC NEURO-ONCOLOGY IN CHILE, SOUTH AMERICA
Bibliographic record
Abstract
Abstract BACKGROUND We report the human and material resources available in Chilean institutions providing pediatric neuro-oncology services. METHODS A cross-sectional survey was distributed to 17 hospitals providing pediatric neuro-oncology services (Programa Infantil Nacional de Drogas Antineoplásicas (PINDA) centers=11, Private=6). RESULTS Response rate was 71% (PINDA=8; Private=4). Pediatric neuro-oncology services were mainly provided within general hospitals (67%). Registries for pediatric central nervous system (CNS) tumors and chemotherapy-related toxicities were available in 100% and 67% of centers, respectively. Children with CNS tumors were treated by pediatric oncologists in 92% of institutions; none were formally trained in neuro-oncology. The most utilized treatment protocols were the national PINDA protocols followed by the Children’s Oncology Group protocols. All World Health Organization essential medicines for childhood cancer were available in more than 80% of participating institutions except for gemcitabine, oxaliplatin, paclitaxel, and procarbazine. The median number of pediatric neurosurgeons per institution was two (range,0–8). General neuro-radiologists were available in 83% of institutions. Pathology specimens were sent to pediatric neuropathologists (33%), neuropathologists (25%), adult pathologists (25%), and pediatric pathologists (16.7%). In-house pediatric radiation oncologists were available in 25% of centers. Intensity-modulated radiotherapy, conformal radiotherapy and cobalt radiotherapy were utilized by 67%, 58% and 42% of hospitals, respectively. Only one center performed autologous hematopoietic cell transplant for pediatric CNS tumors. CONCLUSIONS These results provide a glimpse into the pediatric neuro-oncology services available in Chile. A wide range of up-to-date treatment modalities is available for children with CNS tumors in Chile. Establishing formal pediatric neuro-oncology training may be beneficial.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".