Second Primary Cancers in Thyroid Cancer Patients: A Multinational Record Linkage Study
Bibliographic record
Abstract
CONTEXT: Increasing incidence and improved prognosis of thyroid cancer have led to concern about the development of second primary cancers, especially after radioiodine treatment. Thyroid cancer can also arise as a second primary neoplasm after other cancers. OBJECTIVE: The objective of the study was to assess the risk of second primary cancer after thyroid cancer and vice versa. DESIGN: This was a multinational record linkage study. SETTING: The study was conducted at 13 population-based cancer registries in Europe, Canada, Australia, and Singapore. PATIENTS OR OTHER PARTICIPANTS: A cohort of 39,002 people (356,035 person-yr of follow-up) with primary thyroid cancer were followed up for SPN for up to 25 yr, and 1,990 cases of thyroid cancer were diagnosed after another primary cancer. MAIN OUTCOME MEASURES: To assess any possible excess of second primary neoplasms after thyroid cancer, the observed numbers of neoplasms were compared with expected numbers derived from age-, sex-, and calendar period-specific cancer incidence rates from each of the cancer registries, yielding standardized incidence ratios (SIRs). The SIR of second primary thyroid cancer after various types of cancer was also calculated. RESULTS: During the observation period, there were 2821 second primary cancers (all sites combined) after initial diagnosis of thyroid cancer, SIR of 1.31 (95% confidence interval 1.26-1.36) with significantly elevated risks for many specific cancers. Significantly elevated risks of second primary thyroid cancer were also seen after many types of cancer. CONCLUSION: Pooled data from 13 cancer registries show a 30% increased risk of second primary cancer after thyroid cancer and increased risks of thyroid cancer after various primary cancers. Although bias (detection, surveillance, misclassification) and chance may contribute to some of these observations, it seems likely that shared risk factors and treatment effects are implicated in many. When following up patients who have been treated for primary thyroid cancer, clinicians should maintain a high index of suspicion for second primary cancers.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".