Long-Term Durability of Active Surveillance of Small, Low-Risk Papillary Thyroid Cancer
Bibliographic record
Abstract
Importance: In managing early-stage cancers, active surveillance (AS) may be preferentially favored by older individuals. In counseling patients, it is important to understand the durability of AS in the context of age. Objective: To evaluate the durability of AS in patients with small, low-risk papillary thyroid cancer (PTC) according to age at the time of choosing AS. Design, Setting, and Participants: This single-center, prospective, long-term follow-up cohort study was conducted at a tertiary care hospital in Toronto, Ontario, Canada. Adult patients with small, localized, low-risk PTC less than 2 cm in maximal diameter were enrolled between May 2016 and February 2021. The clinical outcome data were analyzed up to the time point of May 25, 2025, and final data analysis was performed in June 2025. Exposure: All patients were offered the choice of AS or thyroid surgery. Main Outcomes and Measures: The primary outcome was the overall rate of AS crossover to definitive treatment (treatment completed or recommended by an investigator) and the indications. Cumulative crossover incidence function curves were examined according to age, with death from other causes as the competing risk. Results: A total of 200 patients (155 patients under AS and 45 who had immediate surgery) were followed up for a median (IQR) duration of 71 (59-84) months. Overall mean (SD) age was 52.0 (14.9) years, and 153 patients (76.5%) were female. There were no observed thyroid cancer-related deaths or any distant metastatic disease. The overall crossover rate from AS was 23.9% (37/155; 32 completed treatment, 3 declined surgery for disease progression, and 2 awaiting treatment). Crossover reasons included disease progression (56.8% [21/37]), patient preference (40.5% [15/37]), and ultrasound imaging limitations precluding accurate tumor measurement under active surveillance (tumor border not clearly distinguishable from heterogeneous echotexture of the thyroid parenchyma in a patient with Hashimoto thyroiditis; 2.6% [1/37]). The 5-year age-stratified cumulative overall crossover incidence rates were 41.5% (95% CI, 25.6%-56.8%) in patients younger than 45 years, 20.9% (95% CI, 12.3%-31.1%) in those aged 45 to 64 years, and 5.1% (95% CI, 0.9%-15.2%) in those aged 65 years and older (P < .001). Conclusion and Relevance: This single-center Canadian cohort study found that AS is a durable long-term management strategy for small, low -risk PTC, particularly in older individuals. Older individuals may be less likely to cross over to surgery after choosing AS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".