Evaluation of the Pediatric Neuro-Oncology Resources Available in Chile
Bibliographic record
Abstract
PURPOSE: Pediatric neuro-oncology resources are mostly unknown in Chile. We report the human and material resources available in Chilean hospitals 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] hospitals, 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 CNS tumors and chemotherapy-related toxicities were available in 100% and 67% of hospitals, respectively. CNS tumors were treated by pediatric oncologists in 92% of hospitals; none were formally trained in neuro-oncology. The most used treatment protocols were the national PINDA protocols. All WHO essential medicines for childhood cancer were available in more than 80% of the hospitals except for gemcitabine, oxaliplatin, paclitaxel, and procarbazine. The median number of pediatric neurosurgeons per hospital was two (range, 2-6). General neuroradiologists were available in 83% of the centers. Pathology specimens were sent to neuropathologists (58%), adult pathologists (25%), and pediatric pathologists (17%). Intensity-modulated radiotherapy, conformal radiotherapy, and cobalt radiotherapy were used by 67%, 58%, and 42% of hospitals, respectively. Only one private hospital performed autologous hematopoietic cell transplant for children with CNS tumors. CONCLUSION: A wide range of up-to-date treatment modalities are available for children with CNS tumors. Our survey highlights future directions to improve the pediatric neuro-oncology services available in Chile such as the expansion of multidisciplinary clinics, palliative care services, long-term cancer survivorship programs, dedicated clinical research support teams, establishing standardized mechanism for sending pathologic specimen for second opinion to international specialized centers, and establishing specialized neuro-oncology training program.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".