Re-irradiation for children with diffuse intrinsic pontine glioma and diffuse midline glioma
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Diffuse intrinsic pontine glioma (DIPG) and diffuse midline glioma (DMG) are incurable brain malignancies. In this study, we report one of the largest known single-institution cohorts of DIPG/DMG patients undergoing re-irradiation (RT2) to evaluate its effect on survival. MATERIALS AND METHODS: Children aged less than 18 years treated for DIPG/DMG with initial fractionated photon radiotherapy (RT1) and had subsequent recurrence were retrospectively reviewed. Patients treated with or without RT2 were compared. The primary outcomes were overall survival (OS) from time of recurrence after RT1, and from start of RT2 (for the RT2 group). RESULTS: A total of 118 children were included, 39 of whom received RT2. Children treated with RT2 had superior OS, with 6-month OS of 66 % vs 22 % in those who did not undergo RT2 (p < 0.0001). Median survivals were 6.9 months for the RT2 group vs 2.7 months for RT1 only. Median time from RT1 to RT2 was 7.7 months; patients with a greater than 1-year latent time between RT1 and RT2 had longer OS from start of RT2 (median 10.9 months vs 5.5 months, p = 0.023). 61 % of those treated with RT2 experienced improvement of neurologic symptoms post-RT2. Multivariate analysis identified younger age, adverse imaging findings on the 4-week post-RT1 reassessment MRI (including pseudoprogression), and the absence of RT2 as poor prognostic factors for OS. CONCLUSION: Re-irradiation was associated with improved survival and neurological recovery in children with recurrent DIPG and DMG. There is a need to identify novel biomarkers to better select patients who respond best to RT2.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".