Gender differences in the adverse events’ profile registered in seven observational studies of a wide gender-medicine (MetaGeM) project: the MetaGeM safety analysis

BACKGROUND MetaGeM is a wide gender-medicine project comprising post hoc and meta-analyses by gender of clinical outcomes, therapeutic approaches, and safety data from previously conducted observational studies to explore possible gender differences in real-life clinical settings. We report the results of the safety meta-analysis of seven MetaGeM studies, evaluating gender differences in adverse event (AE) incidence and severity. METHODS Data were collected between February 2002 and July 2013. Male and female patients were compared for the main safety variables, using Student's t-test, χ2 test, or Fisher's exact test as appropriate. As supportive analysis, a logistic regression model was estimated to evaluate associations between gender and outcome. RESULTS In total, 4,870 patients (46% females, 54% males) were included in the analysis; age was higher for females (mean ± standard deviation 61.2±18.3 years) than males (56.3±16.6 years). Overall, 264 AEs were reported (59.1% in males). There were no significant gender differences in the percentage of patients with at least one AE: 3.0% for females versus 3.9% for males, χ2 test P>0.05. According to the logistic regression model results, no association between gender and AEs occurrence seems to exist. A statistically significant gender difference in the percentage of drug-related AEs emerged (37.6% in females vs 20.8% in males, χ2P=0.0039). Slightly significantly more AEs in females were addressed with treatment compared with males (78.1% vs 66.7%, χ2P=0.0485). Total serious AEs (SAEs) were 47 (72% in males). The frequency of patients with ≥1 SAE was 0.6% in females versus 1.2% in males (χ2 test P=0.0246). CONCLUSION This safety analysis on a large sample of almost 5,000 patients with different diseases and treated with a wide range of different drugs provides a useful overview on possible gender differences in drug tolerability, which may be helpful in more accurately designing future clinical trials from a gender-specific perspective.