Neurocognitive outcomes in pediatric brain tumors after treatment with proton versus photon radiation: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Advances in cancer treatments, particularly the development of radiation therapy, have led to improvements in survival outcomes in children with brain tumors. However, radiation therapy is associated with significant long-term neurocognitive morbidity. The present systematic review and meta-analysis aimed to compare the neurocognitive outcomes of children and adolescents with brain tumors treated with photon radiation (XRT) or proton therapy (PBRT). METHODS: A systematic search was conducted (PubMed, Embase, Cochrane, and Web of Science from inception until 02/01/2022) for studies comparing the neurocognitive outcomes of children and adolescents with brain tumors treated with XRT vs. PBRT. The pooled mean differences (expressed as Z scores) were calculated using a random effects method for those endpoints analyzed by a minimum of three studies. RESULTS: Totally 10 studies (n = 630 patients, average age range: 1-20 years) met the inclusion criteria. Patients who had received PBRT achieved significantly higher scores (difference in Z scores ranging from 0.29-0.75, all P < 0.05 and significant in sensitivity analyses) after treatment than those who had received XRT for most analyzed neurocognitive outcomes (i.e., intelligence quotient, verbal comprehension and perceptual reasoning indices, visual motor integration, and verbal memory). No robust significant differences (P > 0.05 in main analyses or sensitivity analyses) were found for nonverbal memory, verbal working memory and working memory index, processing speed index, or focused attention. CONCLUSIONS: Pediatric brain tumor patients who receive PBRT achieve significantly higher scores on most neurocognitive outcomes than those who receive XRT. Larger studies with long-term follow-ups are needed to confirm these results.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".