The Prospective Implementation of the 2015 ATA Guidelines and Modified ATA Recurrence Risk Stratification System for Treatment of Differentiated Thyroid Cancer in a Canadian Tertiary Care Referral Setting
Bibliographic record
Abstract
Objective: To present clinical outcomes of the prospective implementation of the 2015 American Thyroid Association (ATA) guidelines for the management of thyroid nodules and differentiated thyroid cancer (DTC) using the modified ATA recurrence risk (RR) stratification system. Methods: We prospectively analyzed 612 patients with DTC treated between April 2017 and December 2021 in Calgary, Alberta. Each patient was prospectively assigned a modified ATA RR and American Joint Committee Cancer 8th edition stage. Initial risk stratification and consideration of the 2015 ATA guidelines guided surgical management as well as the indication for and dose of radioiodine (RAI) and other adjuvant therapies. Patients were assessed for their response to treatment (RTT) at 2-years postoperatively. Results: There were 479 patients who had 2-year follow-up data and were included in the study. Of these patients, there were 253 (53%) low-, 129 (27%) intermediate-, and 97 (20%) high-RR patients. Of these, 227 patients (47%) underwent total thyroidectomy (TTX) plus RAI, 178 (37%) underwent TTX only, and 74 (16%) underwent lobectomy. The RTT at 2 years was excellent for 89% (66) of patients with lobectomy, 84% (149) for TTX only, and 53% (121) for TTX plus RAI. Among 253 patients who were deemed low RR, 85% (216) had excellent RTT, 13% (32) indeterminate RTT, 2% (4) biochemical incomplete RTT, and 1 patient had structural incomplete RTT. The intermediate RR group had the following RTT outcomes: 64% (83) excellent, 23% (30) indeterminate, 6% (7) biochemical incomplete, and 7% (9) structural incomplete. The high RR group had the worst RTT outcomes, with 38% (37) excellent, 19% (18) indeterminate, 10% (10) biochemical incomplete, and 33% (32) structural incomplete RTT. Conclusions: The 2015 ATA RR stratification system is useful for predicting disease status at 2-year post-treatment in patients with DTC. The 2015 ATA guidelines and modified ATA RR stratification treatment recommendations may reduce thyroid cancer overtreatment by including lobectomy as a definitive treatment option for low-risk thyroid cancers and selective use of RAI for intermediate and high-risk patients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".