White matter compromise predicts poor intellectual outcome in survivors of pediatric low-grade glioma
Bibliographic record
Abstract
BACKGROUND: While the impact of cranial radiation on white matter following treatment for pediatric brain tumor has been the focus of many recent studies, the effect of treatment in the absence of radiation has received little attention. The relations between white matter and cognitive outcome have not been explored in patients who have undergone radiation-free treatment. As most patients treated without cranial radiation survive long after their diagnosis, it is critical to identify factors that may impact structural and neurocognitive outcomes. METHODS: Using diffusion tensor imaging, we examined white matter structure in 32 patients with pediatric low-grade glioma (PLGG) (19 with subtentorial location and 13 with supratentorial location) and 32 healthy participants. Indices of intellectual functioning were also evaluated. Radiation was not used to treat this cohort, aged 8-19 years. RESULTS: We detected evidence of deficits in IQ and compromised supra- and subtentorial white matter in patients relative to healthy children (P < .05). Compromise of supratentorial white matter mediated the impact of treatment for PLGG on IQ. Greater white matter compromise was observed in patients who presented without multiple symptoms, were treated with biopsy/no surgery, had positive neurofibromatosis 1 status, were younger age at diagnosis, and whose parents had lower levels of education (P < .05). CONCLUSIONS: Our findings provide evidence of increased risk of intellectual and white matter compromise in patients treated for PLGG without radiation. We identify a neural origin of cognitive deficit useful for predicting outcome and mitigating long-term adverse effects in pediatric brain tumor patients treated without cranial radiation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".