Clinicopathological relevance of antithyroglobulin antibodies in low‐risk papillary thyroid cancer
Bibliographic record
Abstract
OBJECTIVE: The extent of initial surgical management in papillary thyroid cancer (PTC) is controversial. We examined whether the presence of perioperative antithyroglobulin antibodies (TGA) could predict long-term recurrence and occurrence of adverse features among a homogenous group of patients with PTC. METHODS: The clinical features of patients with PTC treated at a single institution (Jewish General Hospital, McGill University, Montreal, Canada) were obtained from the medical records, and all clinicopathologic information was reviewed. Only low-risk PTC without clinical evidence of nodal disease before surgery and treated with 30 mCi of radioactive iodine was included in the study. RESULTS: The chart review retrieved 361 patients with a median follow-up of 85.0 months (Q25-Q75 73-98). Forty-two (11.6%) patients had presence of perioperative TGA. Perioperative TGAs were associated with present extrathyroidal extension (P=.005), unsuspected nodal disease (P=.001) and autoimmune thyroiditis (P<.0001). Overall, 17 (4.7%) patients experienced locoregional recurrence. Perioperative TGAs were a significant predictor of recurrence in univariable (P=.021) but not in multivariable analysis (P=.13). CONCLUSION: Presence of perioperative TGAs is associated with aggressive histological features and the presence of thyroiditis. Detection of TGA perioperatively may encourage surgeons to consider more extensive initial surgery.
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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 | 0.001 |
| 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) | 0.001 | 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".