A review of menopausal hormone therapy: recalibrating the balance of benefit and risk
Bibliographic record
Abstract
While menopausal hormone therapy (MHT) was initially marketed to women of menopausal age to prolong youth, it has endured a tumultuous history evaluating the risk-to-benefit ratio. In response to evidence that MHT may confer cardioprotective effects, 2 landmark randomized controlled trials tested this hypothesis, and both were stopped prematurely due to increased incident cancers and cardiovascular events, creating much controversy and confusion. As women and physicians grew reticent to use MHT, most symptomatic menopausal women remained untreated. Further evaluation of available data has since lent support for the "timing hypothesis," which posits that younger women may not be at risk of adverse events following the use of MHT and may instead experience a survival advantage. Most recently, the 18-year follow-up data of postmenopausal women in the Women's Health Institute trial did not show any change in long-term survival associated with the use of MHT at any age. More recent studies have evaluated alternative treatments for high-risk women, including lower doses and newer formulations of MHT, along with combined new therapies such as selective estrogen receptor modulators, antidepressants, and exercise therapies, which are effective in reducing vasomotor symptoms and improving menopause-specific quality of life. These alternatives provide new options to symptomatic women who are unable or unwilling to take conventional MHT and allow for more person-centered decision making strategies to support women through the menopause.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".