GCT-59. EPIDEMIOLOGY OF PEDIATRIC INTRA-CRANIAL GERM CELL TUMORS: COMPARING THE INCIDENCE OF INTRA-CRANIAL GERM CELL TUMORS IN THE NATIVE JAPANESE POPULATION AND IMMIGRANT JAPANESE POPULATIONS ABROAD
Bibliographic record
Abstract
Abstract Pediatric intra-cranial germ cell tumors (iGCTs) occur at an incidence of 0.6–1.2 cases/million/year in Western countries. The incidence is reported up to 5 times higher in the Japan. It is unknown whether this increased incidence is due to tumor biology or environment. The incidence of iGCTs in children ages 0–19 years was evaluated from 12/1/96-12/1/2016 in stable Japanese immigrant populations living abroad compared to current native Japanese registry data. Medulloblastoma incidence was used as a control to account for assumptions in the data. A review of the Brain Tumor Registry of Japan from 1984–2004 revealed an incidence of 2.5 cases/million/year and a lower incidence of medulloblastoma at 1.1 cases/million/year. Sites outside of Japan included Vancouver, Canada, Lima, Peru, and San Paolo, Brazil and together included a population of 853,174 Japanese persons. Within this population, 0 cases of iGCT were identified over a 20-years. The ratio of medulloblastoma to iGCT cases in Japan was identified as 1:2 while the ratio was 2:1, 6.5:1, and 5:1, respectively, in the other three locations. The data suggests increased incidence in the native Japan may not translate to higher incidence in immigrant Japanese populations abroad and a clear genetic component was not found in this preliminary data set. A more precise and comprehensive study is needed to determine the cause of this difference in incidence. This study also emphasizes the importance of national and state registries and is a call to collaborate on state and country level epidemiology studies.
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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 | 0.002 |
| 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) | 0.001 | 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".