Preoperative diagnosis of thyroid nodules using the Bethesda System for Reporting Thyroid Cytopathology: a comprehensive review and meta-analysis
Bibliographic record
Abstract
Fine-needle aspiration biopsy (FNAB) is the test of choice for the evaluation of nodules, arriving at a cancer diagnosis, and guiding surgical management. This review and meta-analysis aims to objectively evaluate the Bethesda System for Reporting Thyroid Cytopathology (BSRTC) based upon literature reports of histopathological outcomes following cytopathological diagnoses. Thirteen studies were reviewed and the risk of malignancy (ROM) for each of the BSRTC diagnostic categories were calculated as: Non-diagnostic 11-26%, Benign 4-9%, AUS/FLUS 19-38%, FN/SFN 27-40%, SFM 50-79%, and Malignant 98-100%. In typical clinical utilization, the sensitivity and specificity of thyroid FNAB diagnosis using the BSRTC were 96% and 46%, respectively. The BSRTC represents an important advance in standardizing thyroid FNAB cytopathological reporting. Close attention should be paid to the observation that the AUS-FLUS and FN-SFN DCs have overlapping ROMs, and the potential clinical implications of this finding on patient management.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".