Fine-Needle Aspiration Biopsy of the Thyroid
Bibliographic record
Abstract
OBJECTIVES: To evaluate the positive predictive value of a thyroid nodule being malignant when categorized as atypical, and to determine the prognostic implications of specific cytopathological features. DESIGN: Retrospective review of consecutive patients undergoing thyroid surgery following fine-needle aspiration biopsy (FNAB) of thyroid nodules. SETTING: Academic teaching hospital in Toronto, Ontario. PATIENTS: A total of 111 consecutive patients with atypical findings from an FNAB who underwent thyroid surgery from January 2000 to November 2005. RESULTS: Of 111 patients included in this study, 62 (56%) were diagnosed with a thyroid malignancy on final histopathological examination. The remaining 49 patients (44%) had benign disease. When comparing patients with a postoperative diagnosis of malignancy vs those with benign disease, micronucleoli (71% vs 49%; P = .01), nuclear grooves (50% vs 31%; P = .03), and powdery chromatin (37% vs 16%; P = .01) were more frequently observed in the group with cancer. The probability of malignancy was 83% if all 3 of these features were present; 32% if none of these features was present (P = .001). CONCLUSIONS: At our institution, when findings from a thyroid nodule FNAB sample were categorized as atypical, the positive predictive value of the nodule being malignant was 56%. In this series of patients, the presence of micronucleoli, nuclear grooves, and powdery chromatin increased the likelihood that an atypical specimen was representative of malignant disease. These features may help guide treatment of patients with atypical findings from a thyroid nodule FNAB sample.
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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) | 0.000 | 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".