Impact of Nodal Metastases on Prognosis in Patients With Well-Differentiated Thyroid Cancer
Bibliographic record
Abstract
OBJECTIVES: To study the clinical and pathological variables predicting lymph node metastases in patients with well-differentiated thyroid carcinoma and to examine the impact of these metastases on recurrence and survival. DESIGN: Cohort study. Median follow-up, 56 months. SETTING: Tertiary referral university teaching hospital. PATIENTS: The study included 522 consecutive patients with well-differentiated thyroid carcinoma treated between 1964 and 1999. Data were collected on age, sex, family history of thyroid disease, prior radiation exposure, stage of disease, pathological diagnosis, size of tumor, multifocality of disease, recurrence, and survival. INTERVENTION: Total thyroidectomy and postoperative iodine 131 ablation. MAIN OUTCOME MEASURES: Disease-free and overall survival. RESULTS: A total of 347 patients with stage I disease and 118 with stage II disease were identified. The median age of patients with neck disease was 3 years younger than those without neck disease and most had papillary carcinoma. Patients with multifocal disease were more likely to have neck disease (P =.02). On univariate analysis, disease-free and overall survival rates were significantly lower in patients who presented with neck node metastases (P<.001 and P =.005); this difference in survival remained highly significant on multivariate analysis for disease-free survival (P =.001), with a relative hazard of 6.27. CONCLUSIONS: When treated with total thyroidectomy and routine postoperative iodine 131 ablation, patients with well-differentiated thyroid carcinoma who present with neck node metastases outside the central compartment of the neck have an approximately 6-fold risk of developing recurrences, most of which occur in the neck.
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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 | 0.002 |
| 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) | 0.001 | 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".