Long-Term Declines of Thyroid Cancer Mortality: An International Age–Period–Cohort Analysis
Bibliographic record
Abstract
Background: Thyroid cancer (TC) incidence rates have been increasing in many countries, predominantly due to overdiagnosis. It is, however, not yet clear whether a true increase in exposure to risk factors might have also contributed to the TC epidemic. We assessed the TC mortality trends, which should not be affected by overdiagnosis, to disentangle the specific contribution of period and cohort effects. Methods: We analyzed long-term mortality data in 24 countries from 5 continents using age–period–cohort (APC) models. Nonidentifiability of the APC models was circumvented by integrating evidence of a consistent relationship between age and TC mortality, allowing to estimate period and cohort linear effects. Results: Substantial heterogeneity existed in the historical TC mortality rates across countries, but long-term rates declined over time in most of the countries, converging around a value of 0.5/100,000. The shape of the age–specific curves was consistently similar across countries and periods, resembling straight lines on the log–log scale, with the slopes ranging between 4.0 and 6.0. Both period and cohort effects showed long-term declines in most countries for both genders. In some countries, such as the United States, Canada, and Australia, substantial long-term declines by period were visible until the 1980s and 1990s, but then stabilized or increased slightly. Declining cohort effects were also seen in almost all countries, and were particularly pronounced in women from Switzerland, whereas stable cohort effects were recorded in South Africa. Although there were some indications of possible increasing risks of deaths among the youngest generations in some countries for both men and women, changes are too recent to be treated as unequivocal and estimates suffered from large statistical variability due to small numbers of deaths. Conclusions: Global long-term declines in TC mortality have been accompanied by downward trends in both period and cohort effects. Our results suggest lack of evidence of a possible major contribution of “real” risk factors in TC mortality, and indirectly confirm the main role of overdiagnosis in the epidemic of TC incidence.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".