Second Primary Malignancy Risk After Radioactive Iodine Treatment for Thyroid Cancer: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: The risk of second primary malignancies (SPMs) associated with cancer therapies is an important concern of thyroid cancer survivors and physicians. Our objective was to determine if the risk of SPMs is increased in individuals with thyroid cancer treated with radioactive iodine (RAI), compared to those not treated with RAI. METHODS: We performed a systematic review of the literature and meta-analysis. Two independent reviewers screened citations and reviewed full-text papers. If not reported by the primary authors, the relative risk (RR) of SPMs was calculated by dividing the standardized incidence ratio of SPM in individuals with thyroid cancer treated with RAI compared to those not treated with RAI (with associated 95% confidence intervals [CI]). The natural logarithms of RRs of respective SPMs, weighted by the inverse of the variance, were pooled using fixed effects models and the exponential of the results was reported. RESULTS: Two multi-center studies (one from Europe and the other from North America) were included in this review. The RR of SPMs in thyroid cancer survivors treated with RAI was significantly increased at 1.19 (95% confidence interval [CI] 1.04, 1.36, p = 0.010), relative to thyroid cancer survivors not treated with RAI (data from 16,502 individuals), using a minimum latency period of 2 to 3 years after thyroid cancer diagnosis. The RR of leukemia was also significantly increased in thyroid cancer survivors treated with RAI, with an RR of 2.5 (95% CI 1.13, 5.53, p = 0.024). We did not observe a significantly increased risk of the following cancers related to prior RAI treatment: bladder, breast, central nervous system, colon and rectum, digestive tract, stomach, pancreas, kidney (and renal pelvis), lung, or melanoma of skin. CONCLUSIONS: The risk of SPMs in thyroid cancer survivors treated with RAI is slightly increased compared to thyroid cancer survivors not treated with RAI.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.036 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".