Guiding Management of Bethesda V Thyroid Nodules: The Role of Molecular Testing
Bibliographic record
Abstract
OBJECTIVE: The 2023 Bethesda System update introduced molecular testing as a management option for Bethesda V cytology nodules, aiming to guide surgical decision-making. This study investigates the correlation between molecular profiling and malignancy aggressiveness. DESIGN: We conducted a retrospective multicenter study involving patients with Bethesda V cytology and confirmed malignant pathology who underwent molecular profiling between 2018 and 2021. PATIENTS: A total of 156 patients with Bethesda V cytology and final malignant histology were included. MEASUREMENTS: Malignancy aggressiveness was assessed based on histopathological features following 2015 ATA guidelines. Demographic data, pathology results, and genetic variants were analyzed. Molecular profiling results were stratified according to variant risk levels. RESULTS: We identified 161 Bethesda V nodules, of which 153 (95.0%) were malignant on final pathology. Genetic stratification revealed no detected mutations in 39.7% (n = 56), low-risk (n = 49, 31.4%), and intermediate-risk variants (n = 45, 28.8%). Only one patient had a high-risk variant. Patients with intermediate-risk variants had a sixfold risk of aggressive disease compared to those with low-risk variants (49% vs. 8.2%, p < 0.001). RAS mutations were the most common among the low-risk group (68.8%) and BRAF V600E predominated in the intermediate-risk group (93.3%). CONCLUSIONS: Our findings suggest that molecular profiling offers insights into risk stratification for Bethesda V thyroid lesions, demonstrating a very low incidence of aggressive pathology in the low-risk molecular group.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".