Characteristics of children ≤36 months of age with DIPG: A report from the international DIPG registry
Bibliographic record
Abstract
BACKGROUND: Children ≤36 months with diffuse intrinsic pontine glioma (DIPG) have increased long-term survival (LTS, overall survival (OS) ≥24 months). Understanding distinguishing characteristics in this population is critical to improving outcomes. METHODS: Patients ≤36 months at diagnosis enrolled on the International DIPG Registry (IDIPGR) with central imaging confirmation were included. Presentation, clinical course, imaging, pathology and molecular findings were analyzed. RESULTS: Among 1183 patients in IDIPGR, 40 were eligible (median age: 29 months). Median OS was 15 months. Twelve patients (30%) were LTS, 3 (7.5%) very long-term survivors ≥5 years. Among 8 untreated patients, median OS was 2 months. Patients enrolled in the registry but excluded from our study by central radiology review or tissue diagnosis had median OS of 7 months. All but 1 LTS received radiation. Among 32 treated patients, 1-, 2-, 3-, and 5-year OS rates were 68.8%, 31.2%, 15.6% and 12.5%, respectively. LTS had longer duration of presenting symptoms (P = .018). No imaging features were predictive of outcome. Tissue and genomic data were available in 18 (45%) and 10 patients, respectively. Among 9 with known H3K27M status, 6 had a mutation. CONCLUSIONS: Children ≤36 months demonstrated significantly more LTS, with an improved median OS of 15 months; 92% of LTS received radiation. Median OS in untreated children was 2 months, compared to 17 months for treated children. LTS had longer duration of symptoms. Excluded patients demonstrated a lower OS, contradicting the hypothesis that children ≤36 months with DIPG show improved outcomes due to misdiagnosis.
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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 | 0.002 |
| 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 | 0.001 |
| 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".