Patient and tumor factors contributing to distant metastasis in well-differentiated thyroid cancer: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Distant metastasis in thyroid cancer significantly reduces survival in patients with well-differentiated thyroid carcinoma (WDTC). There is limited information available to clinicians regarding pathological features that confer a higher risk of distant metastasis (DM). This study aimed to identify patient and tumor factors that were associated with the development of DM over time in patients with WDTC. METHODS: A retrospective cohort analysis of patients with WDTC (n = 584) at our institution was performed between 2007 and 2017. A total of 39 patients with DM and 529 patients with no DM (NDM) were included. Patient demographics, tumor characteristics and patient survival were compared between the DM and NDM groups using a univariate analysis. Multivariate Cox-proportional hazards model was used to evaluate the risk of developing distant metastasis over time. Kaplan-Meier analysis was used to compare survival between the DM and NDM groups. RESULTS: Distant metastasis had a substantial impact on disease-specific survival (DSS) at 5 and 10-years in the DM group; 71.0% (SE 8.4%) and 46.9% (SE 11.6%) respectively, compared to 100% survival in the NDM group (p < 0.001). The DM group had significantly higher proportions of males, lymphovascular invasion (LVI), nodal metastasis (NM), large tumor size (TS), extrathyroidal extension (ETE), positive resection margins, multifocality, follicular thyroid cancer (FTC), tall cell variant of papillary thyroid cancer (PTC), and Hurthle cell carcinoma (HCC), when compared to the NDM group (p < 0.05). A TS ≥ 2 cm (Hazard Ratio (HR) 1.370), NM (HR 3.806) and FTC (HR 7.068) were associated with a significantly increased hazard of developing distant metastasis in patients with WDTC. CONCLUSIONS: TS ≥ 2 cm, NM and FTC are associated with a significantly increased propensity for developing DM in our cohort of WDTC patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".