Abstract 12585: Flexible Modeling of the Association Between Cumulative Exposure to Low-Dose Ionizing Radiation From Cardiac Procedures and Risk of Hematopoietic Cancer in Children With Congenital Heart Disease
Bibliographic record
Abstract
Background: High-dose ionizing radiation is a well-established risk factor for childhood malignancies, including hematopoietic cancers (HC). However, data on the effect of low-dose ionizing radiation (LDIR) from medical imaging is conflicting and scant, especially in the pediatric population with congenital heart diseases (CHD). This study evaluated the association between cardiac LDIR exposure and hematopoietic cancers among children with CHD. Methods: A nationwide population-based cohort study was conducted using the Canadian Congenital Heart Disease (CanCHD) database. The study population included children born between 1999 and 2017 with at least one CHD diagnosis in their medical records. The cumulative dose of ionizing radiation corresponding to cardiac diagnostic and therapeutic procedures was quantified considering a 6-month exposure lag. The recency-weighted cumulative exposure (WCE) model, a flexible extension of Cox’s proportional hazards model, was used to assess the association. Results: We identified 139,975 children with CHD born between 1999 and 2017 and followed them for 1,388,681 person-years since birth. In this population, 718 hematopoietic cancer cases were observed. Children with HC were exposed to low-dose ionizing radiation earlier in life (median age at first exposure: 6 vs. 10 months; p=0.03) and had more procedures than those without cancer (mean number of procedures: 0.4 vs. 0.2; p<0.001). The cases received higher cumulative LDIR doses than their counterparts (mean dose: 2.3 vs. 1.1 mSv; p<0.001). We observed that cumulative LDIR doses within five years were associated with increased risk of hematopoietic cancer with the maximum association magnitude around 2 years. Conclusion: This is the first large population-based study documenting increased risk of HC associated with increased dose and recency of the LDIR exposure among children with CHD. Along with these findings, future studies focusing on detecting a threshold effect will help physicians decide the exposure point at which increased surveillance on LDIR exposure should be initiated.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".