Subclinical hypothyroidism and the risk of cancer incidence and cancer mortality: a systematic review
Bibliographic record
Abstract
BACKGROUND: Thyroid hormone has been shown to be involved in carcinogenesis via its effects on cell proliferation pathways. The objective of this study is to determine the association between subclinical hypothyroidism (SCH) and the risk of incident cancer and cancer mortality via systematic review. METHODS: A systematic search was performed on Medline and Pubmed to identify relevant studies. Randomized controlled trials, and observational studies assessing SCH or its treatment and the risk of incident cancer or cancer mortality were identified. RESULTS: A total of 7 cohort and 2 case-control studies met our inclusion criteria. In general, these studies were of medium to good quality. Overall, studies revealed no association between SCH and breast and prostate cancer. One study found that untreated SCH may be associated with an increased risk of colorectal cancer (adjusted odds ratio [OR]: 1.16; 95% confidence interval [CI]: 1.08-1.24). One study showed an increased risk in thyroid cancer incidence (adjusted OR: 3.38; 95% CI: 2.05-5.59) associated with elevation of a thyroid stimulating hormone (TSH) of > 1.64mIU/L. Two studies found an increase in cancer mortality among patients with SCH compared to euthyroid individuals; in contrast one study found no association between subclinical hypothyroidism and cancer mortality among aging men. CONCLUSION: The number of studies examining thyroid dysfunction and cancer risk and mortality is limited. Future studies assessing the association between thyroid dysfunction and cancer risk and mortality are needed, which will further address the need to treat subclinical hypothyroidism.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".