Staging at Diagnosis and Survival of Hematologic Neoplasms in Children and Adolescents in Mato Grosso, Brazil: A Population-based Study
Bibliographic record
Abstract
OBJECTIVE: To apply the Toronto Childhood Cancer Staging Guidelines (TG) and Estimate the Observed Survival Probabilities for Pediatric Patients with Leukemia and Lymphoma. METHODS: Staging at diagnosis was conducted according to tier 2 of the TG. The study cohort included patients aged 0 -19 years from the Population-Based Cancer Registry (PBCR) of Mato Grosso, diagnosed with leukemia and lymphoma between 2008 and 2017, with follow-up until December 31, 2022. Observed 60-month survivals were calculated using the Kaplan-Meier method. RESULTS: Staging was assigned in 67.3% of cases (n=239), while in 32.7% (n=116), staging could not be applied due to incomplete data. Among the cases of acute lymphoblastic leukemia (ALL), 70.7% (n=133) were staged as CNS1, with an observed survival probability of 75.0%. For acute myeloid leukemia (AML), 42.2% (n=21) were staged as CNS-, with an estimated survival of 60.0%. Most Hodgkin lymphoma (HL) cases were staged as IIA/B (37.7%, n=23) and IIIA/B (21.3%, n=13), with survival probabilities of 91.3% and 91.7%, respectively. Among non-Hodgkin lymphoma (NHL) cases, 32.1% (n=18) were staged as stage III, with a survival probability of 70.6%. CONCLUSION: The application of TG in the PBCR in Mato Grosso proved feasible, allowing for comparability of survival estimates across different stages. However, collecting tier 2 staging information will be a challenge for the PBCR due to incomplete information in medical records.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".