Marked Increase in Incident Gynecomastia: A 20-Year National Registry Study, 1998 to 2017
Bibliographic record
Abstract
CONTEXT: Gynecomastia, the proliferation of mammary glandular tissue in the male, is a frequent but little-studied condition. Available prevalence data are based on selected patient populations or autopsy cases with their inherent bias. OBJECTIVE: The objective of this work is to evaluate the age-related incidence and secular trends in gynecomastia in the general population. DESIGN: An observational, 20-year national registry study was conducted. SETTING: This population-based study used nationwide registry data. PARTICIPANTS: Participants included all Danish males (age 0-80 years) with a first-time diagnosis of gynecomastia. MAIN OUTCOME MEASURES: All Danish males (age 0-80 years) were followed up for incident diagnosis of gynecomastia in the Danish National Patient Registry from 1998 to 2017 using the International Codes of Diseases, 10th revision, and the Danish Health Care Classification System. Age-specific incidence rates were estimated. The hypothesis tested in this study was formulated prior to data collection. RESULTS: Overall, a total 17 601 males (age 0-80 years) were registered with an incident diagnosis of gynecomastia within the 20-year study period, corresponding to 880 new cases per year and an average 20-year incidence of 3.4 per 10 000 men (age 0-80 years). The average annual incidence was 6.5/10 000 in postpubertal males age 16 to 20 years and 4.6/10 000 in males age 61 to 80 years, with a respective 5- and 11-fold overall increase in these 2 age groups over the 20-year period. CONCLUSIONS: The incidence of gynecomastia has dramatically increased over the last 20 years, implying that the endogenous or exogenous sex-steroid environment has changed, which is associated with other adverse health consequences in men such as an increased risk of prostate cancer, metabolic syndrome, type 2 diabetes, or cardiovascular disorders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".