Bilateral papillary thyroid cancer and associated histopathologic findings.
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of bilateral papillary thyroid cancer (PTC) at total thyroidectomy (TT) and compare demographic risk factors (gender and age) and histopathologic findings (tumour size, extrathyroidal extension [ETE], T staging, and multifocality) between patients with PTC in both thyroid lobes and those with PTC limited to the ipsilateral lobe and/or isthmus. DESIGN: Retrospective study. SETTING: University teaching hospital. METHODS: The pathology results of 1047 consecutive patients who underwent TT between 2002 and 2008 were reviewed. Statistical significance was obtained using the chi-square test. MAIN OUTCOME MEASURES: Incidence of bilateral PTC and its association with demographic risk factors and histopathologic findings. RESULTS: Among 592 patients with PTC, 13.2% had bilateral PTC and 86.8% had unilateral and/or isthmian PTC. Bilaterality was present in 12.4% of women and 16.7% of men (p = .24) and in 12.9% of patients aged > or = 45 years and 13.5% < 45 years (p = .83). Bilateral PTC was found in 12.6% of patients with a primary tumour < or = 2 cm and 13.5% > 2 cm (p = .75); 23.6% of tumours with ETE demonstrated bilaterality compared to 9.7% without (p < .0001), and 8.7% of pT1 (p = .08), 9.2% of pT2 (p = .02), 23.0% of pT3 (p < .0001), and 12.5% of pT4 (p = .87) tumours were bilateral, respectively. Among bilateral PTC patients, 43.2% had multifoci in at least one lobe compared to 6.4% when nonbilateral (p < .0001). CONCLUSIONS: After TT, 13.2% of patients had bilateral PTC. No significant correlation was established between bilaterality and gender, age, and tumour size. Bilaterality was more commonly found in patients with ETE, advanced T stage, and at least one multifocal lobe.
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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 | 0.001 |
| 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) | 0.004 | 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".