No Association between Radiation Dose from Pediatric CT Scans and Risk of Subsequent Hodgkin Lymphoma
Bibliographic record
Abstract
Abstract Background: We examined the relationship between estimated radiation dose from CT scans and subsequent Hodgkin lymphoma in the UK pediatric CT scans cohort. Methods: A retrospective, record linkage cohort included patients ages 0 to 21 years who underwent CT scans between 1980 and 2002 and were followed up for cancer or death until 2008. Poisson regression analysis was used to evaluate the relationship between estimated radiation dose (lagged by 2 years) and incident Hodgkin lymphoma diagnosed at least 2 years after the first CT scan. Results: There were 65 incident cases of Hodgkin lymphoma in the cohort of 178,601 patients. Neither estimated red bone marrow dose nor mean lymphocyte dose from CT scans was clearly associated with an increased risk of Hodgkin lymphoma (RR for 20+ mGy vs. <5 mGy = 0.92 (0.38–2.22) Ptrend > 0.5 and 1.44 (0.60–3.48) Ptrend > 0.5), respectively. Conclusions: Radiation exposure from pediatric CT scans 2 or more years before diagnosis was not associated with Hodgkin lymphoma in this large UK cohort. Impact: These findings are consistent with the majority of previous studies, which do not support a link between ionizing radiation and Hodgkin lymphoma. The results contrast our previous positive findings in this cohort for brain tumors and leukemia, both of which are known to be strongly linked to radiation exposure during childhood. Cancer Epidemiol Biomarkers Prev; 26(5); 804–6. ©2017 AACR.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".