Soy, Red Clover, and Isoflavones and Breast Cancer: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Soy and red clover isoflavones are controversial due to purported estrogenic activity and possible effects on breast cancer. We conducted a systematic review of soy and red clover for efficacy in improving menopausal symptoms in women with breast cancer, and for potential impact on risk of breast cancer incidence or recurrence. METHODS: We searched MEDLINE, Embase, the Cochrane Library, and AMED from inception to March 2013 for human interventional or observational data pertaining to the safety and efficacy of soy and red clover isoflavones in patients with or at risk of breast cancer. RESULTS: Of 4179 records, we included a total of 131 articles: 40 RCTs, 11 uncontrolled trials, and 80 observational studies. Five RCTs reported on the efficacy of soy for hot flashes, showing no significant reductions in hot flashes compared to placebo. There is lack of evidence showing harm from use of soy with respect to risk of breast cancer or recurrence, based on long term observational data. Soy intake consistent with that of a traditional Japanese diet (2-3 servings daily, containing 25-50mg isoflavones) may be protective against breast cancer and recurrence. Human trials show that soy does not increase circulating estradiol or affect estrogen-responsive target tissues. Prospective data of soy use in women taking tamoxifen does not indicate increased risk of recurrence. Evidence on red clover is limited, however existing studies suggest that it may not possess breast cancer-promoting effects. CONCLUSION: Soy consumption may be associated with reduced risk of breast cancer incidence, recurrence, and mortality. Soy does not have estrogenic effects in humans. Soy intake consistent with a traditional Japanese diet appears safe for breast cancer survivors. While there is no clear evidence of harm, better evidence confirming safety is required before use of high dose (≥ 100 mg) isoflavones can be recommended for breast cancer patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".