Feasibility and stage at diagnosis for children with cancer: a pilot study on population-based data in a middle-income country using the Toronto childhood cancer stage guidelines
Bibliographic record
Abstract
Background: The aim was to conduct a pilot study in a middle-income country testing the use of the Toronto Childhood Cancer Staging System by Population-Based Cancer Registry (PBCR). Methods: This study involved first the translation of the Australian pediatric cancer staging manual for 16 types of pediatric tumours. Four PBCRs from different regions of Brazil were selected for a pilot study. The study period was from 2005 to 2014, and data were collected from notification sources, including hospitals, pathological laboratories and routine medical records, and staging was done retrospectively. Results: We identified 1,560 pediatric cancer cases diagnosed between 2005 and 2014. Notably, 94.7% met Tier 1 criteria, and 91.9% met Tier 2 criteria. The PBCR from Curitiba (south region) demonstrated higher staging feasibility (99.3% Tier 1; 96.7% Tier 2) than from Aracaju (northeast) (87.5% Tier 1; 81.3% Tier 2). Most cases had localised or regional disease (77.7%), while 14.3% were metastatic, and 8.0% could not be staged. Osteosarcoma had the highest metastasis rate (50.0%). Conclusion: Our study demonstrates the feasibility of collecting pediatric cancer stage data from population-based registries in resource-limited settings, advancing our understanding of pediatric cancer outcomes in Brazil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".