Progesterone Is Important for Transgender Women’s Therapy—Applying Evidence for the Benefits of Progesterone in Ciswomen
Bibliographic record
Abstract
BACKGROUND: Although the 2017 Endocrine Society Guidelines for gender dysphoria stipulated that cross-sex hormone therapy (CHT) achieve gonadal steroid levels equivalent to those of a cisperson of the chosen sex, for transgender women (male-to-female gender dysphoria), current gonadal therapy is usually estradiol. Accumulated evidence indicates that normally ovulatory menstrual cycles are necessary for ciswomen's current fertility, as well as for later-life bone and cardiovascular health and the prevention of breast and endometrial cancers. EVIDENCE ACQUISITION: Extensive past clinical experience with transgender women's CHT using estradiol/estrogen combined with progesterone/medroxyprogesterone and pioneering the addition of spironolactone. Comprehensive progesterone physiology research plus a brief review of transgender women's literature to assess current therapy and clinical outcomes, including morbidity and mortality. PURPOSE: To emphasize that both ovarian hormones, progesterone as well as estradiol, are theoretically and clinically important for optimal transgender women's CHT. EVIDENCE SYNTHESIS: It is important to add progesterone to estradiol and an antiandrogen in transgender women's CHT. Progesterone may add the following: (i) more rapid feminization, (ii) decreased endogenous testosterone production, (iii) optimal breast maturation to Tanner stages 4/5, (iv) increased bone formation, (v) improved sleep and vasomotor symptom control, and (vi) cardiovascular health benefits. CONCLUSIONS: Evidence has accrued that normal progesterone (and ovulation), as well as physiological estradiol levels, is necessary during ciswomen's premenopausal menstrual cycles for current fertility and long-term health; transgender women deserve progesterone therapy and similar potential physiological benefits.
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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 | 0.010 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".