Influence of age and primary tumor size on the risk for residual/recurrent well‐differentiated thyroid carcinoma
Bibliographic record
Abstract
BACKGROUND: Though age and primary tumor size predict cancer-specific survival in well-differentiated thyroid carcinoma (WDTC), their influence on residual/recurrent disease has not been elucidated. METHODS: In a retrospective study, residual/recurrent disease was defined by the surrogate outcome of positive (>or=2 microg/L) follow-up stimulated thyroglobulin after surgery and radioactive remnant ablation. Age, primary tumor size, and clinical staging systems were examined in the context of stimulated thyroglobulin outcome. RESULTS: A total of 246 patients were followed up for a mean of 5.8 years. No significant difference in age (t(239) = 0.61, p > .05) or tumor size (t(237) = 0.16, p > .05) was found among patients with positive follow-up stimulated thyroglobulin compared with those with negative results. pTNM staging failed to demonstrate significant, stage-dependent increase in the percentage of patients with positive stimulated thyroglobulin, chi(2)(2, N = 229) = 0.17, p > .05, unlike staging based solely on surgical pathology, chi(2)(2, N = 241) = 34.97, p < .001. CONCLUSION: Age, primary tumor size, and pTNM staging do not predict risk for residual/recurrent WDTC, whereas extrathyroidal extension at initial surgery is predictive.
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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 | 0.001 | 0.003 |
| 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".