Rates of thyroid malignancy by FNA diagnostic category
Bibliographic record
Abstract
BACKGROUND: Fine needle aspiration (FNA) of thyroid nodules is a cornerstone of surgical decision making in thyroid cancer. The most widely utilized system for reporting thyroid FNA results is the Bethesda System, which includes predicted malignancy rates for each FNA category. To date there have been few studies to determine whether these predictions are widely applicable. METHODS: All thyroid FNA results at the Queen Elizabeth II Health Science Centre from 2006-2010 were included in this study. The results were tabulated by FNA category and the health records were reviewed to determine whether the patient went on to have surgery and the result of surgical histopathology. Rates of malignancy were calculated and compared to published values. RESULTS: A total of 1491 thyroid FNAs were included in the study, representing 1117 individual patients with available health records. The majority of these FNAs were Benign, but the proportion of Unsatisfactory FNAs was higher than predicted while Malignant and Suspicious for Malignancy were lower than predicted. Surgery was performed on 388 patients and 110 were positive for malignancy (28%). The malignancy rate for each FNA category was higher than predicted based on literature values. CONCLUSIONS: The proportions of FNA diagnoses and the rates of malignancy for each FNA category at our institution were not consistent with predicted values. It is important for clinicians to base their surgical recommendations on institution specific malignancy rates, not solely on literature values.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".