Histologic Findings in Surgical Pathology Specimens From Individuals Taking Feminizing Hormone Therapy for the Purpose of Gender Transition
Bibliographic record
Abstract
CONTEXT.—: Transgender men and transmasculine persons experience a discordance between the female sex they were assigned at birth and their gender. They may choose to take hormone therapy and/or undergo surgery to masculinize the body. Understanding the common (and less common) histologic changes present in patients taking masculinizing hormones will empower pathologists to better serve this unique patient population. OBJECTIVE.—: To summarize histologic findings in surgical pathology specimens from persons taking masculinizing hormones as a part of gender transition. DATA SOURCES.—: A systematic review of the OVID Medline and PubMed databases was performed to identify all studies describing histologic findings in surgical pathology specimens from transgender men from January 1946 to January 2021. CONCLUSIONS.—: Publication in this area has markedly increased in the last 2 decades. However, most of the studies identified were descriptive and case reports describing changes seen in specimens removed as a part of masculinizing surgical procedures. Benign histologic findings include stromal hyalinization and epithelial atrophy in the breast, polycystic ovarian syndrome-like changes in the ovary, and transitional cell metaplasia in the cervix. The most commonly reported neoplastic finding was adenocarcinoma of the breast, with rare cases of ovarian, endometrial, cervical, vaginal, pituitary, pancreatic, and cardiovascular neoplasia also reported. Ongoing research in this area is needed to better characterize the histologic findings in persons taking masculinizing hormones to provide a deeper understanding of the effect of these treatments on different tissues and facilitate better patient management.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".