Serum 25-hydroxyvitamin D level is unreliable as a risk factor and prognostic marker in papillary thyroid cancer
Bibliographic record
Abstract
Background: Low levels of vitamin D and altered local vitamin D metabolism have been associated with the prevalence and aggressiveness of several cancers. However, the effect of vitamin D on papillary thyroid cancer (PTC) is controversial. This study aimed to evaluate the impact of preoperative serum vitamin D levels and local vitamin D metabolism on the clinicopathologic characteristics and prognosis of PTC. Methods: In total, 1,578 patients with PTC and 128 patients with benign thyroid diseases were included. Clinical and pathologic data were analyzed to evaluate the role of vitamin D as a risk factor and prognostic marker in PTC. Moreover, a tissue microarray was used to investigate the role of local vitamin D metabolism in PTC progression. Results: Participants with PTC were younger compared to those with benign disease. No significant differences in 25-hydroxy vitamin D [25(OH)D] levels were observed between benign and malignant cases. Among patients with PTC, analyses of prognostic features revealed that decreased 25(OH)D levels were not overtly associated with poor prognosis in PTC. Additionally, local vitamin D metabolism was not associated with the aggressiveness of PTC. Conclusions: Serum 25(OH)D determination may not contribute to risk assessment workup of thyroid nodules. Moreover, decreased preoperative serum vitamin D and local vitamin D metabolism were not associated with poor prognosis of PTC.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".