Thyrotropin and Thyroid Cancer Diagnosis: A Systematic Review and Dose-Response Meta-Analysis
Bibliographic record
Abstract
CONTEXT: TSH is the major growth factor for thyrocytes and may have a causative role in thyroid cancer. OBJECTIVE: The objective of the study was to systematically assess the association between serum TSH and thyroid cancer. DATA SOURCES: The MEDLINE and EMBASE databases were searched using synonyms for TSH and thyroid cancer, supplemented with reference list searches and author contact. STUDY SELECTION: Prospective cohort, case-control, and cross-sectional studies were identified with TSH the exposure and thyroid cancer the outcome. DATA EXTRACTION: Three reviewers independently extracted data. Studies reporting odds ratio (OR) for TSH levels and thyroid cancer were analyzed via meta-analysis and generalized least-squares trend estimation for dose-response relationships. DATA SYNTHESIS: Data extracted from 28 studies included a total of 42,032 subjects and 5,786 thyroid cancer cases. Dose-response spline analysis revealed a nonlinear relationship (P < 0.001). For TSH levels less than 1 mU/liter, the OR for thyroid cancer was 1.72 (1.42, 2.07) per milliunits per liter. However, the relationship changed for TSH levels 1 mU/liter and greater, with the OR thereafter being 1.16 (1.12, 1.21) per milliunits per liter. Studies controlling for autoimmunity reported the lowest OR [TSH below 2.5 mU/liter, OR 1.23 (1.02-1.47) per milliunits per liter; TSH 2.5 mU/liter or greater, OR 0.98 (0.89-1.09) per milliunits per liter]. Six groups assessed serum TSH in relation to markers of poor thyroid cancer prognosis, with three showing significant positive relationships. CONCLUSIONS: Higher serum TSH concentration is associated with an increased risk of thyroid cancer. Thyroid autoimmunity may partially explain the association, but further epidemiological assessment is required. Future clinical research should investigate the validity of including serum TSH in diagnostic nomograms, its prognostic importance, and the potential for therapeutic TSH suppression in thyroid cancer prevention.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.005 | 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 | 0.002 |
| 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".