Mastectomy for Individuals with Gender Dysphoria Younger Than 26 Years: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Gender dysphoria (GD) refers to psychological distress associated with the incongruence between one's sex and one's gender. In response to GD, birth-registered female patients may choose to undergo mastectomy. In this systematic review, the authors summarize and assess the certainty of the evidence about the effects of mastectomy. METHODS: We searched MEDLINE, Embase, PsycINFO, Social Sciences Abstracts, LGBTQ+ Source, and Sociological Abstracts through June 20, 2023. We included studies comparing mastectomy to no mastectomy in birth-registered patients younger than 26 years with GD. Outcomes of interest included psychological and psychiatric outcomes, and physical complications. Pairs of reviewers independently screened articles, abstracted data, and assessed risk of bias of the included studies. We performed meta-analysis and assessed the certainty of the evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: We included 39 studies. Observational studies ( n = 2) comparing mastectomy to chest binding provided very low-certainty evidence for the outcome of GD. One observational study comparing mastectomy to no mastectomy provided very low-certainty evidence for the outcomes of global functioning and suicide attempts, and low-certainty evidence for the outcome nonsuicidal self-injury (adjusted OR, 0.47; 95% CI, 0.22 to 0.97). Before-and-after ( n = 2) studies provided very low-certainty evidence for all outcomes. Evidence from case series ( n = 34) studies ranged from high to very low certainty. CONCLUSIONS: Case series studies demonstrated high-certainty evidence for the outcomes of death, necrosis, and excessive scarring; however, these are limited in methodologic quality. In comparative and before-and-after studies, the evidence ranged from low to very low certainty.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".