DIPG-91. CLINICAL, RADIOGRAPHIC, HISTOPATHOLOGIC, AND MOLECULAR CHARACTERISTICS OF LONG-TERM SURVIVORS OF DIFFUSE INTRINSIC PONTINE GLIOMA-AN UPDATE FROM THE INTERNATIONAL AND EUROPEAN SOCIETY FOR PEDIATRIC ONCOLOGY DIPG REGISTRIES (IDIPGR/SIOPE-DIPGR)
Bibliographic record
Abstract
Abstract BACKGROUND Diffuse intrinsic pontine glioma (DIPG) is a childhood tumor with median survival of < 1 year. Survival-associated factors for this rare disease are poorly understood. METHODS Clinical, radiological, and histo-molecular data were abstracted from databases of the IDIPGR and SIOPE-DIPGR and analyzed using descriptive statistics. Survival was estimated by the Kaplan Meier method. Short term survivors (STS) were defined as overall survival (OS) < 2 years, and long term survivors (LTS) had OS >2 years. We present data from the IDIPGR with additional analyses forthcoming. RESULTS Analysis included 1123 patients with DIPG, with 476 undergoing central radiographic review. Median OS for the entire cohort was 11 months (IQR 7-15 months), with 2 yr OS 6.9% (5.6% to 8.6%). Median age at diagnosis was 6.6 years (5-9.7 years) for 1045 STS (93.1%) and 6.8 years (3.7-13 years) for 78 LTS (6.9%). Factors significantly associated with LTS included longer symptom duration (STS 73.7% vs LTS 42%; p<0.001), age < 3 and > 10 years (STS 4.5 and 22.8% vs LTS 17.9 and 35.9%; p<0.0001), and receipt of chemotherapy at any time during therapy (STS 54.7% vs LTS 67.9%; p=0.025). A similar percentage of STS and LTS received EGFR, MTOR, PI3K, HDAC, local delivery and immunotherapy, although more LTS used VEGF inhibition (20.5 % vs 8.6%; p = 0.002). Of 104 patients with molecular data, 69 harbored the H3.3 histone mutations (7 LTS, 62 STS), and 15 had H3.1(3 LTS, 12 STS). CONCLUSION Early analysis of factors associated with survival in patients with DIPG reveal similar findings as the prior IDIPGR/SIOPE-DIPGR study in 2018. These findings will be updated for the final presentation to include ~400 more cases and additional radiological and molecular data.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".