Association of Bethesda category and molecular mutation in patients undergoing thyroidectomy
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to ascertain the relationship between Bethesda category and molecular mutation of thyroid nodules in patients undergoing thyroidectomy. DESIGN: A retrospective cohort of patients who underwent thyroidectomy following needle biopsy and molecular profile testing was performed. SETTING: Two tertiary care academic hospitals. PARTICIPANTS: Consecutive patients with a dominant thyroid nodule who underwent both USFNA and molecular profile testing followed by thyroidectomy were included in the study. MAIN OUTCOME AND MEASURES: The main outcome was postoperative diagnosis of thyroid cancer and aggressivity of disease based on histopathological variants, nodal metastasis or extra-thyroidal extension. Associations between Bethesda category, molecular mutation and postoperative pathology was assessed using descriptive analysis and chi-square testing. RESULTS: Four hundred fifty-one patients were included. 95.9% (93/97) of patients with a BRAFV600E mutation had a Bethesda category V or VI (p < .001), and all had confirmed thyroid cancer on postoperative pathology. Those with H, K or N RAS or EIF1AX mutations, gene expression profiling (GEP) or copy number alterations showed an association with Bethesda categories III and IV (p ≤ .01). Those with no identified molecular mutation had a lower incidence of aggressive thyroid cancer compared to those with an identified mutation (12.6% vs. 44.3%, p < .01). CONCLUSION: BRAFV600E mutations were associated with thyroid cancer subtypes known to be more aggressive whereas RAS and EIF1AX mutations, copy number alterations, and GEP were related to Bethesda categories III and IV. These findings may help thyroid specialists better identify aggressive thyroid nodules associated with indeterminate Bethesda categories.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".