Risk-benefits assessment of tamoxifen or raloxifene as chemoprevention for risk reduction of breast cancer among BRCA1 and BRCA2 carriers: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Breast cancer is a major global health burden, with hereditary factors such as BRCA1/2 mutations significantly increasing the lifetime risk. This meta-analysis aimed to evaluate the outcomes of selective estrogen receptor modulators (SERMs), tamoxifen, and raloxifene as chemopreventive agents for breast cancer risk reduction in BRCA1/2 mutation carriers. METHODS: A meta-analysis was conducted according to the PRISMA guidelines. PubMed, Cochrane Library, and MEDLINE databases were searched for relevant studies published between 2000 and 2024. Case-control studies and observational cohort studies examining the use of tamoxifen/raloxifene in BRCA1/2 carriers were included. Data on the incidence and risk ratios of breast cancer were also extracted. Quality was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was performed using Review Manager (version 5.4.0). RESULTS: Nine studies (13,676 women) were included. Two studies had low risk, and the remaining seven studies had moderate risk, as assessed by the NOS checklist. Pooled analysis showed tamoxifen/raloxifene decreased breast cancer risk compared to controls (RR 0.80, 95% CI 0.72-0.88, p = 0.04). The risk ratio of breast cancer incidence among BRCA1/2 carriers was reduced after tamoxifen use (RR 1.82, 95% CI 1.48-2.23, p < 0.00001). Subgroup analysis revealed reduced breast cancer risk with SERM use in both BRCA1 (RR 1.51, 95% CI 1.48-1.51) and BRCA2 carriers (RR 1.48, 95% CI 1.40-1.58). The heterogeneity ranged from 51 to 85%, representing high significance and variation in true effect sizes underlying the different included studies. Whereas the heterogeneity among subgroups BRCA1 and BRCA2 was 98%, and the difference was 0%, showing no difference in response to SERM for risk reduction of breast cancer. CONCLUSION: This meta-analysis provides evidence that tamoxifen and raloxifene significantly reduce the breast cancer risk in women with BRCA1/2 mutations. Chemoprevention efficacy was similar for both BRCA1 and BRCA2 carriers. Further research is needed to validate these findings and to optimize their use in high-risk populations.
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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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.087 |
| Bibliometrics | 0.007 | 0.005 |
| 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".