The value of second opinion in thyroid cytology: A review
Bibliographic record
Abstract
BACKGROUND: Second-opinion diagnosis (SOD) on pathological material is an accepted practice before definitive therapy is considered for referred patients. The thyroid gland is an anatomical site prone to diagnostic disagreement between pathologists. We performed a review of the literature that addressed the role of interinstitutional SOD on thyroid fine-needle aspirations (FNAs). METHODS: Nine studies comprising second opinions on thyroid FNAs were selected. The parameters analyzed included: discordances between the initial diagnoses (IDs) and SODs; cytohistologic correlation; changes in the clinical management of the patients with thyroid nodules after SOD. The same parameters were applied to the "indeterminate" diagnostic category comprising cases initially reported as "atypia," "atypia of undetermined significance/follicular lesion of undetermined significance," "suspicious for a follicular neoplasm," "follicular neoplasm," "suspicious," and "suspicious for malignancy." RESULTS: A total of 7154 thyroid FNAs were retrieved, showing an overall discordance rate between ID and SOD of 28.6%. In general, SOD was better supported by clinical follow-up and histological diagnosis, showing higher diagnostic accuracy in comparison with ID. Almost one-third (30.4%) of the discordant cases resulted in changes in the clinical management of patients with thyroid nodules. Numerous thyroid FNAs initially categorized as "indeterminate" were definitively classified as benign or malignant by SOD, with an overall diagnostic resolution rate of 42.5%, sensitivity of 97.9%, and diagnostic accuracy of 73.7%. CONCLUSIONS: Second-opinion review of thyroid FNA improves diagnostic accuracy and potentially changes clinical management. SOD also demonstrates a significative rate of diagnostic resolution for thyroid FNAs originally diagnosed as "indeterminate."
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".