Follow-up of Benign Thyroid Nodules—Can We Do Less?
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of malignancy, follow-up ultrasound (US), and repeat fine needle aspiration (FNA) in thyroid nodules that have been previously biopsied as benign. METHODS: This is a retrospective, descriptive study of benign thyroid nodules evaluated by US between 2010-2011. We determined the frequency of follow-up ultrasounds and FNAs, mean years of follow-up, interval between follow-up US, change in nodule size, reasons for repeat FNA (rFNA), frequency of thyroidectomy, and thyroid malignancy during 5 years of follow-up. RESULTS: A total of 733 benign thyroid nodules were reviewed in 615 patients. Mean years of US follow-up was 3.47 ± 1.65 years; 275 (37.5%) had no follow-up US; 109 (14.9%) had 1 follow-up US; 93 (12.7%) had 2 follow-up US; and 256 (34.9%) had 3 or more follow-up US. Assessment of thyroid nodule size showed that 215 (28.8%) nodules decreased in size, 145 (19.4%) increased in size by less than 50%, and 91 (12.1%) increased in size by more than 50%. Of the 733 nodules, 17 nodules (2.3%) underwent thyroidectomy for which the pathology result of 9 (1.2%) showed malignancy, and 65 (8.9%) thyroid nodules underwent rFNA. When applying the 2015 recommendations for repeat FNA, 35% were done unnecessarily. CONCLUSION: In our sample of initially benign thyroid nodules, only 9 patients (1.2%) had pathology-proven malignancy after a mean follow-up of 3.5 years. Over 30% of patients had more than 3 rUSs. Decreased interval and frequency of rUS should be considered in future guidelines for thyroid management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".