Current management of papillary thyroid microcarcinoma in Canada
Bibliographic record
Abstract
INTRODUCTION: The detection of papillary thyroid microcarcinoma (PTMC) is on the rise and its optimal management remains controversial. Our aim was to determine the current self-reported management of PTMC amongst Canadian otolaryngologist-head and neck surgeons (OHNS) and endocrinologists and to identify factors influencing their management decisions. METHODS: A nine item web-based questionnaire was distributed to Canadian OHNS and endocrinologists. The three main domains were demographics, current management of PTMC scenarios, and factors influencing the decisions. RESULTS: One hundred and thirteen OHNS and endocrinologists completed the survey. Respondents were closely divided between recommending hemithyroidectomy (47%) or total thyroidectomy (43%) for a newly diagnosed PTMC in a low risk patient. Observation was the preferred method for managing PTMC detected incidentally after hemithyroidectomy (76%). Respondents chose more aggressive treatment for male patients compared to female patients. A positive history of thyroid cancer or previous radiation exposure was the most important factor influencing the management of PTMC. CONCLUSION: The current practices of Canadian OHNS and endocrinologist largely coincide with available guidelines. The slight variation in practice might be explained by the opposing evidence supporting different management options. Given the dramatic increase in the incidence of PTMC we suggest future guidelines address the management of PTMC independently.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".