Molecular Diagnosis Using Residual Liquid-Based Cytology Materials for Patients with Nondiagnostic or Indeterminate Thyroid Nodules
Bibliographic record
Abstract
BACKGROUND: Molecular analysis for common somatic mutations in thyroid cancer can improve diagnostic accuracy of fine-needle aspiration cytology (FNAC) in the nondiagnostic or indeterminate category of thyroid nodules. In this study, we evaluated the feasibility of molecular diagnosis from residual liquid-based cytology (LBC) material after cytological diagnosis. METHODS: This prospective study enrolled 53 patients with thyroid nodules diagnosed as nondiagnostic, atypia of undetermined significance (AUS), or follicular lesion of undetermined significance (FLUS) after FNAC. DNAs and RNAs were isolated from residual LBC materials. BRAF(V600E) and RAS point mutations, PAX8/peroxisome proliferator-activated receptor γ (PPARγ), RET/PTC1, and RET/PTC3 rearrangements were evaluated by real-time polymerase chain reaction and pyrosequencing. RESULTS: All DNAs from 53 residual LBC samples could be analysed and point mutations were detected in 10 samples (19%). In 17 AUS nodules, seven samples (41%) had point mutations including BRAF (n=4), NRAS (n=2), and KRAS (n=1). In 20 FLUS nodules, three samples (15%) had NRAS point mutations. RNA from only one FLUS nodule could be analysed for rearrangements and there was no abnormality. CONCLUSION: Molecular analysis for BRAF and RAS mutations was feasible in residual LBC materials and might be useful for diagnosis of indeterminate thyroid nodules.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".