Post-treatment neuroendocrine outcomes among pediatric brain tumor patients: Is there a difference between proton and photon therapy?
Bibliographic record
Abstract
Purpose: Pediatric brain tumor patients are vulnerable to radiotherapy (RT) sequelae including endocrinopathies. We compared post-RT neuroendocrine outcomes between pediatric brain tumor patients receiving photons (XRT) versus protons (PRT). Methods: Using a prospectively maintained single-institution database, we analyzed 112 pediatric primary brain tumor patients (80 XRT, 32 PRT) from 1996 to 2019. Patient/treatment characteristics and endocrinopathy diagnoses (growth hormone deficiency [GHD], sex hormone deficiency [SHD], hypothyroidism, and requirement of hormone replacement [HRT]) were obtained via chart review. Univariable/multivariable logistic regression identified neuroendocrine outcome predictors. Time-adjusted propensity score models accounted for treatment type. Craniospinal irradiation (CSI) patients were evaluated as a sub-cohort. Results: Median follow-up was 6.3 and 4.4 years for XRT and PRT patients respectively. Medulloblastoma was the most common histology (38%). Half of patients (44% in XRT, 60% in PRT) received CSI. Common endocrinopathies were GHD (26% XRT, 38% PRT) and hypothyroidism (29% XRT, 19% PRT). CSI cohort PRT patients had lower odds of hypothyroidism (OR 0.16, 95% CI[0.02-0.87], p = 0.045) on multivariable regression and propensity score analyses. There were no significant differences in endocrinopathies in the overall cohort and in the odds of GHD or HRT within the CSI cohort. SHD developed in 17.1% of the XRT CSI group but did not occur in the PRT CSI group. Conclusion: Endocrinopathies were common among pediatric brain tumor survivors. Among CSI patients, PRT was associated with lower risk of hypothyroidism, and potentially associated with lower incidence of SHD. Future studies should involve collaborative registries to explore the survivorship benefits of PRT.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".