Second Primary Malignancy Risk in Thyroid Cancer Survivors: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: To determine the risk of second primary malignancies (SPMs) in thyroid cancer survivors. DESIGN: We performed a systematic review and meta-analysis examining the standardized incidence ratios (SIRs) of SPMs in thyroid cancer survivors (compared to individuals without thyroid cancer). Two independent reviewers screened citations and reviewed all full-text papers deemed potentially relevant. Final consensus was reached on inclusion of papers in the review. Data were pooled using fixed effects models. MAIN OUTCOMES: Thirteen full-text papers were included. The incidence of SPMs in thyroid cancer survivors was increased with an SIR of 1.20 (95% confidence interval 1.17, 1.24) (based on pooled data from six studies of 70,844 thyroid cancer survivors). The SIR of the following SPMs was significantly increased: salivary gland, stomach, colon/colorectal, breast, prostate, kidney, brain/central nervous system, soft tissue sarcoma, non-Hodgkin's lymphoma, multiple myeloma, leukemia, bone/joints, and adrenal. A significantly reduced risk of lung and cervical cancers was observed. CONCLUSIONS: Thyroid cancer survivors are at increased risk of SPMs, which may be related to disease-specific treatments or genetic predisposition.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".