Supplementary Material for: Exposure to Medical Radiation during Fetal Life, Childhood and Adolescence and Risk of Brain Tumor in Young Age: Results from The MOBI-Kids Case-Control Study
Bibliographic record
Abstract
<b><i>Background:</i></b> We explored the association between ionizing radiation (IR) from pre-natal and post-natal radio-diagnostic procedures and brain cancer risk within the MOBI-kids study. <b><i>Methods:</i></b> MOBI-kids is an international (Australia, Austria, Canada, France, Germany, Greece, India, Israel, Italy, Japan, Korea, New Zealand, Spain, The Netherlands) case-control study including 899 brain tumor (645 neuroepithelial) cases aged 10–24 years and 1,910 sex-, age-, country-matched controls. Medical radiological history was collected through personal interview. We estimated brain IR dose for each procedure, building a look-up table by age and time period. Lifetime cumulative doses were calculated using 2 and 5 years lags from the diagnostic date. Risk was estimated using conditional logistic regression. Neurological, psychological and genetic conditions were evaluated as potential confounders. The main analyses focused on neuroepithelial tumors. <b><i>Results:</i></b> Overall, doses were very low, with a skewed distribution (median 0.02 mGy, maximum 217 mGy). ORs for post-natal exposure were generally below 1. ORs were increased in the highest dose categories both for post and pre-natal exposures: 1.63 (95% CI 0.44–6.00) and 1.55 (0.57–4.23), respectively, based on very small numbers of cases. The change in risk estimates after adjustment for medical conditions was modest. <b><i>Conclusions:</i></b> There was little evidence for an association between IR from radio-diagnostic procedures and brain tumor risk in children and adolescents. Though doses were very low, our results suggest a higher risk for pre-natal and early life exposure, in line with current evidence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".