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 -test, 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, test >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, =0.0039). Slightly significantly more AEs in females were addressed with treatment compared with males (78.1% vs 66.7%, =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 ( test =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.