Growing Pains With the Bethesda System for Reporting Thyroid Cytopathology (BSRTC): Our Institution's Experience in the First 3 Years
Bibliographic record
Abstract
The Bethesda system is the standard for reporting thyroid cytopathology and for stratifying patients based on the risk of malignancy. Reproducible application of the diagnostic categories and their quoted risk of malignancy remains challenging. The category of atypia of undetermined significance (AUS), estimated to carry a 5%-10% risk of malignancy, has been shown to be particularly variable between institutions and cytopathologists. Since the BSRCT was adopted by our department, 332 thyroid fine-needle aspirates (FNAs) and 146 resections were performed on 349 patients over a 3-year period. Diagnosis rates in each category were tabulated for cytopathologist (n = 5) and institution (n = 2) where the procedure was performed. Cytology-histology correlation was assessed for those cases that went on to resection. The 332 FNAs were classified as follows: 28% unsatisfactory, 33% benign, 26% AUS, 6% follicular or suspicious for follicular neoplasm, 4% suspicious for malignancy, and 3% positive for malignancy. Significant differences were found between pathologists in the rates of AUS (P < .05). In the absence of a suspicious or positive for malignancy result, the diagnosis of AUS in at least 1 FNA carried a risk of malignancy of 42%. Between institutions performing FNAs, the ratio of unsatisfactory to satisfactory specimens was significantly higher in specimens from the community compared with the academic hospital (P < .01). Reproducibility of the BSRCT remains challenging. Our results show that the rates of AUS and the risk of malignancy associated with each category is dependent on the individual cytopathologist. In addition, despite following the system's guidelines, our institutions rates for each diagnostic category differ from the reported rates in the literature. Finally, our preliminary results suggest that there are factors unique to the academic setting that contribute to a higher rate of satisfactory aspirates, suggesting a role for continuing education.
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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 | 0.038 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".