Incidental detection, imaging modalities and temporal trends of differentiated thyroid cancer in Ontario: a population-based retrospective cohort study
Bibliographic record
Abstract
<h3>Background:</h3> Incidence rates of thyroid cancer in Ontario have increased more rapidly than those of any other cancer, whereas mortality rates have remained relatively stable. We evaluated the extent to which incidental detection of differentiated thyroid cancer during unrelated prediagnostic imaging procedures contributed to Ontario’s incidence rates. <h3>Methods:</h3> We conducted a retrospective cohort study involving Ontarians who received a diagnosis of differentiated thyroid cancer from 1998 to 2017 using linked health care administrative databases. We classified cases as incidentally detected if a nonthyroid diagnostic imaging test (e.g., computed tomography [CT]) preceded an index event (e.g., prediagnostic fine-needle aspiration biopsy); all other cases were nonincidentally detected cases. We used Joinpoint and negative binomial regressions to characterize sex-specific rates of differentiated thyroid cancer by incidentally detected status and to quantify potential age, diagnosis period and birth cohort effects. <h3>Results:</h3> The study included 36 531 patients with differentiated thyroid cancer, of which 78.7% were female. Incidentally detected cases increased from 7.0% to 11.0% of female patients and from 13.5% to 18.2% of male patients over the study period. Age-standardized incidence rates increased more rapidly for incidentally detected cases (4.2-fold for female and 3.7-fold for male patients) than for nonincidentally detected cases (2.6-fold for female and 3.0-fold for male patients; <i>p</i> < 0.001). Diagnosis period was the primary factor associated with increased incidence rates of differentiated thyroid cancer, adjusting for other factors. Within each period, incidentally detected rates increased faster than nonincidentally detected rates, adjusting for age. Our results showed that CT was the most common imaging procedure preceding incidentally detected diagnoses. <h3>Interpretation:</h3> Incidentally detected cases represent a large and increasing component of the observed increases in differentiated thyroid cancer in Ontario over the past 20 years, and CT scans are primarily associated with these cases despite the modality having similar, increasing rates of use compared with magnetic resonance imaging (1993–2004). Recent increases in rates of differentiated thyroid cancer among males and incidentally detected cases among females in Ontario appear to be unrelated to birth cohort effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".