Association between thyroid disorders and the Risk of developing prostate cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
Objective: To determine the association between thyroid disorders and the Risk of developing prostate cancer. Methods: We conducted this review following the recommendations of the Cochrane Collaboration and the PRISMA Statement. From the moment to the present, we have conducted a search strategy using MEDLINE, WEB OF SCIENCE, and GOOGLE SCHOLAR. We included cohort and case-control studies that examined the relationship between thyroid disorders and the Risk of developing prostate cancer. We assessed the Risk of bias using the Newcastle Ottawa Quality Assessment scale. Meta-analysis was conducted in Review Manager 5.4.1 (Revman ® ). Results: We included nine studies in the analysis. The studies included were classified into two groups: those that studied hypothyroidism and those that studied hyperthyroidism. The results showed no association between thyroid abnormalities and prostate cancer risk, with an HR of 1.05 (95% CI: 0.90–1.22). Hyperthyroidism also showed no association with an HR 1.64 (95% CI: 1.00–2.69), characterized by increased serum T4 and decreased TSH. There was also no significant association with hypothyroidism, with an HR of 0.85 (95% CI: 0.67–1.10). Conclusion: Thyroid disorders were not associated with the Risk of developing prostate cancer.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.023 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".