Association between testosterone replacement therapy and cardiovascular events in men: a retrospective propensity-weighted analysis
Bibliographic record
Abstract
BACKGROUND: Testosterone deficiency (TD), or male hypogonadism, affects up to 25% of Canadian men aged 40 to 60. Testosterone replacement therapy (TRT) is widely used to manage symptoms of TD. Despite over seven decades of clinical use, the relationship between TRT and major adverse cardiovascular events (MACE) remains unclear. AIM: To investigate the association between TRT and MACE using a large population-based database. METHODS: A propensity-weighted, retrospective cohort study was conducted using provincial health administrative databases. Men were eligible if they had no prior TRT use or MACE and maintained at least one year of provincial health coverage between April 1, 1995, and December 31, 2018. TRT was defined as having at least two prescriptions filled within one year for testosterone products (capsules, gels, patches, or injections). MACE was defined as the first occurrence of myocardial infarction, coronary revascularization, ischemic stroke, or hospitalization for heart failure. A logistic regression model including age, socioeconomic status, index year, diabetes, hypertension, dyslipidemia, and renal disease generated propensity scores. Stabilized inverse propensity treatment weighting was applied. OUTCOMES: A Cox proportional hazards model was used to assess time to first MACE. RESULTS: Among 6949 men who received TRT and 415 837 controls, TRT was associated with a 27% increased risk of MACE (HR 1.27, 95% CI: 1.16-1.39) in weighted analyses. Among 7306 men diagnosed with TD and 442 602 matched controls, those with TD also showed a 27% increased risk of MACE (HR 1.27, 95% CI: 1.16-1.39). Median time to MACE was 2828 days in the TRT group and 2707 days in controls. MACE occurred in 9.95% of TRT users versus 5.56% of controls. CLINICAL IMPLICATIONS: Clinicians should be aware that both TRT and underlying TD are associated with increased cardiovascular risk. Assessment of comorbidities and patient-specific cardiovascular risk remains essential when initiating TRT. STRENGTHS & LIMITATIONS: This study leverages a large, real-world, population-based dataset with robust propensity weighting methodology. However, unmeasured confounding such as obesity, smoking, or physical activity levels may influence outcomes. Diagnostic coding limitations may also affect TD case identification. CONCLUSIONS: Both TRT use and TD were associated with a significantly increased risk of MACE. Whether TRT independently drives this risk or merely reflects underlying disease requires further investigation. Risk stratification and shared decision-making should guide the initiation of TRT.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".