Linear reduction in thyroid cancer risk by oral contraceptive use: a dose–response meta-analysis of prospective cohort studies
Bibliographic record
Abstract
STUDY QUESTION: Is there an association between oral contraceptive (OC) use and thyroid cancer risk in females? SUMMARY ANSWER: OC use is inversely associated with the risk of thyroid cancer in females. WHAT IS KNOWN ALREADY: OC use may be relevant to the risk of thyroid cancer as suggested by some epidemiological studies. However, the findings are inconsistent regarding the effect direction and size. STUDY DESIGN, SIZE, DURATION: This systematic review and meta-analysis included a total of 1906 patients from about 1.3 million individuals who had participated in 9 prospective cohort studies. The follow-up length ranged 7.5-15.9 years. PARTICIPANTS/MATERIALS, SETTING, METHODS: PubMed (MEDLINE) was searched through to January 2015 for eligible studies. References of relevant review articles were also manually screened. Prospective cohort studies that evaluated the association between OC use and thyroid cancer risk were included. Study characteristics including patients' characteristics, length of the follow-up and risk estimates were extracted. The quality of the studies was also assessed. MAIN RESULTS AND THE ROLE OF CHANCE: The included studies were of high methodological quality according to the Newcastle-Ottawa Quality Assessment Scale. After pooling risk estimates from all the studies, there was a significant inverse association between the longest versus shortest duration of OC use and the risk of thyroid cancer [relative risk (RR) = 0.84, 95% confidence interval (CI) 0.73-0.97], with no considerable heterogeneity (I(2) = 26.1%). There was no significant publication bias. The significant association persisted in the subgroup of high-quality studies (RR = 0.84, 95% CI 0.72-0.97). By dose-response analysis, there was a linear relationship (P = 0.0001) between the duration of OC use and thyroid cancer risk. The summary RR for an increment of 1 year of OC use was 0.96 (95% CI 0.94-0.98), with no significant heterogeneity. LIMITATIONS, REASONS FOR CAUTION: Individual patient data were unavailable for a more accurate estimation. WIDER IMPLICATIONS OF THE FINDINGS: These results indicate that OC use may decrease the risk of thyroid cancer in females. This may have implications for women's decisions regarding the use of OC. STUDY FUNDING/COMPETING INTERESTS: No funding was involved for this study. No conflicts of interest are declared.
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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 | 0.027 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.078 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".