DIPG-72. LONG-TERM SURVIVAL OF A CLASSIC DIFFUSE INTRINSIC PONTINE GLIOMA TREATED WITH NIMOTUZUMAB
Bibliographic record
Abstract
Abstract BACKGROUND Long-term survival in diffuse intrinsic pontine glioma is rare, and typically associated with atypical imaging and/or atypical clinical course. Although most patients harbor hotspot mutations in H3.1/3-K27M, a proportion of patients have alternate mutations, despite a typical clinicoradiological course. Herein we describe a long-term survivor with a classical presentation, treated with nimotuzumab, highlighting the challenges associated with such cases. CASE REPORT: A 5 year old male, diagnose in 2012 with a 10 day history multiple cranial neuropathies and a right hemiparesis. Cranial MRI revealed a poorly delimited diffuse pontine tumor and secondary hydrocephalus. Tumor biopsy was not performed due to the classic clinical presentation, and he received 54Gy/30 of radiation plus concomitant weekly nimotuzumab 150mg/m2. Initial tumor dimensions were 43x31x28mm. Nimotuzumab 150mg/m2 was continued every 2 weeks. Image assessment at week 12 of treatment revealed 16.9% volume increase, 4 weeks after radiotherapy completion. Nevertheless, subsequent neuroimaging at 24th, 36th, 60th, 96th and 108th weeks of nimotuzumab therapy showed a sustained and progressive tumor cytoreduction of 47.5%, 59%, 62.2%, 63.8% and 67%, respectively, when compared with post-radiotherapy dimensions. Currently, the patient is 13y old, good school performance, no neurologic disabilities. The last MRI at 394 weeks of nimotuzumab revealed dimensions of 21x19x14mm which corresponds to 70% of reduction compared with initial volume. CONCLUSIONS Our case of progressive cytoreduction over two years of a classic DIPG, diagnosed in the era prior to the discovery of the K27M mutation, highlights the challenges associated with long-term survival of this devastating entity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".