Association between hysterectomy, oophorectomy, and risk of breast cancer: a meta-analysis
Bibliographic record
Abstract
Abstract Objectives This meta-analysis seeks to clarify the relationship between hysterectomy, oophorectomy, and the subsequent risk of developing breast cancer. Methods A comprehensive literature search was conducted across PubMed, the Cochrane Library, and Embase to identify relevant studies. The quality of the included studies was assessed using the Newcastle–Ottawa Scale (NOS). Statistical analyses were performed using Stata software (version 14.0), with hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) calculated. Publication bias was assessed using funnel plots and Egger’s test. Results A total of 12 studies were included, comprising 9 cohort studies and 3 case–control studies, with publication years ranging from 1988 to 2023, involving 5,868,660 participants, predominantly from the United States. The analysis revealed that both hysterectomy and oophorectomy are associated with a reduced risk of breast cancer, lowering the risk by 16% (HR 0.84; 95% CI: 0.76–0.92; I 2 = 76.5%; P < 0.001). Standalone hysterectomy was associated with a 13% reduction in breast cancer risk (HR 0.87; 95% CI: 0.77–0.99; I 2 = 82.3%; P = 0.033), while bilateral oophorectomy reduced the risk by approximately 19% (HR 0.81; 95% CI: 0.68–0.96; I 2 = 61.7%; P = 0.016). In contrast, unilateral oophorectomy did not significantly affect the risk of breast cancer (HR 0.89; 95% CI: 0.71–1.11; I 2 = 45.5%; P = 0.288). Patients who underwent bilateral oophorectomy and received hormone therapy experienced a 20% reduction in breast cancer risk (HR 0.80; 95% CI: 0.68–0.93; I 2 = 38.5%; P = 0.005), whereas those who did not receive hormone therapy showed no significant risk reduction (HR 0.87; 95% CI: 0.69–1.10; I 2 = 48.5%; P = 0.254). Premenopausal bilateral oophorectomy was associated with a 13% decrease in breast cancer incidence risk (HR 0.87; 95% CI: 0.79–0.96; I 2 = 0%; P = 0.004), while postmenopausal bilateral oophorectomy had no significant impact (HR 0.95; 95% CI: 0.88–1.03; I 2 = 1.2%; P = 0.196). Conclusions This meta-analysis suggests that both hysterectomy and oophorectomy are significantly associated with a reduction in breast cancer risk. The effectiveness of bilateral oophorectomy appears to be modulated by hormone therapy and menopausal status. Further research is needed to clarify these associations and to explore the underlying biological mechanisms.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.066 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".