Variables Predicting Distant Metastases in Thyroid Cancer
Bibliographic record
Abstract
OBJECTIVES: Distant metastases from thyroid cancer are uncommon and have a variable prognosis. We present a series of patients with distant metastases to determine which patients are at risk of developing distant disease and to examine the significant prognostic variables. STUDY DESIGN: Retrospective chart review of 30 patients with distant metastases compared with 633 controls from the Mount Sinai Thyroid Cancer Database and literature review. METHODS: The prevalence of distant metastases was 4.5%, and median follow-up of survivors was 12.7 years. Histologic type was Hurthle cell carcinoma in 3, follicular in 3, papillary in 19, and 5 patients had focal anaplasia either in the primary site or regional metastases. Predictors for distant metastases, locoregional control, and survival were analyzed. RESULTS: Cumulative survival for patients with distant metastases was 49.5% at 10 years and 12.9% at 20 years. Site of metastases was lung in 26, bone in 11 and brain in 1 patient, with 8 patients having multiple sites. The median time to diagnosis of distant metastases was 3 months. Variables that predicted for development of distant disease were male sex, age, size, extrathyroidal extension, regional metastases, and elevated thyroglobulin. Survival in patients without distant disease was significantly better than those with distant metastases (P < .001). Variables that predicted poor outcome in patients with distant metastases on analysis were age greater than 45 years (P = .003) and histologic type of thyroid cancer (P = .009). CONCLUSION: Although patients with thyroid cancer and distant metastases may live prolonged periods with disease, it does significantly impact on patient survival. Age remains an important variable in both predicting for development of distant metastases and also influences long-term survival in patients with existing distant metastases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".