Follow-up and transition of care for low recurrence risk thyroid cancer patients in Canada
Bibliographic record
Abstract
The incidence of differentiated thyroid cancer (DTC) has increased significantly in recent decades. Following initial diagnosis, DTC patients are classified according to the American Thyroid Association (ATA) as low, intermediate, and high risk for recurrence. Patients in the ATA low recurrence-risk category have a recurrence risk of ≤5%, with 20-year disease-specific mortality of <1%. Accordingly, there has been a shift to de-escalating initial treatment, including the relaxation of thyroid-stimulating hormone suppression. In addition, fewer low-risk patients undergo total thyroidectomy or radioactive iodine therapy. However, the optimal long-term surveillance strategy remains unclear, with many patients continuing follow-up in speciality clinics for many years. In addition, emerging evidence suggests that long-term surveillance can be effectively managed in primary care settings. To enhance understanding among Canadian thyroid practitioners and to improve care for Canadian patients diagnosed with low-risk DTC, we developed this consensus statement by collecting feedback from a multidisciplinary team led by one chairperson (endocrinologist), an additional eight endocrinologists, two surgeons, and one patient partner. This consensus statement reflects current evidence and expert opinion regarding initial management and long-term surveillance of low-risk DTC patients. This work is valuable to Canadian thyroid practitioners as it provides standardized guidelines to ensure optimal care and improved outcomes for low-risk DTC patients.
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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".