Extrathyroidal Extension in Well-Differentiated Thyroid Cancer
Bibliographic record
Abstract
OBJECTIVE: To examine the prognostic difference in well-differentiated thyroid cancer between macroscopic extrathyroidal extension (ETE), which is appreciated in the operating room, vs microscopic ETE, which is only appreciated under the microscope by the pathologist. DESIGN: Retrospective medical record review. SETTING: Tertiary care academic hospital. PATIENTS: Among 582 patients, those who were surgically treated for stage III well-differentiated thyroid cancer with a minimum 5-year follow-up were included. Fifty-five patients (10%) (17 males and 38 females [mean age, 53.1 years]) met the selection criteria. MAIN OUTCOME MEASURES: Disease-specific survival and overall survival. RESULTS: Thirty-two patients (58%) had macroscopic ETE, while 23 patients (42%) had microscopic ETE. Twenty-year disease-specific survival in the macroscopic group was 47% (8 of 17) and 45% (5 of 11) in the microscopic group (P=.45). Twenty-year overall survival in the macroscopic group was 27% (3 of 11) and 24% (4 of 17) in the microscopic group (P=.59). The only confounding factor was external beam radiation therapy (EBRT). More patients with macroscopic ETE were treated with EBRT (P=.007). When survival was stratified according to EBRT, patients with macroscopic ETE who did not receive EBRT had diminished disease-specific survival (P=.07) and overall survival (P=.12). On multivariate analysis, EBRT was the only predictor of improved disease-specific survival (P=.02) and overall survival (P=.06). CONCLUSIONS: In selected patients with macroscopic ETE, we recommend postoperative EBRT. Further investigation is required to determine whether macroscopic ETE vs microscopic ETE is an independent predictor of outcome.
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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) | 0.001 | 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".