Evaluate multiple adverse events in crossover design bioequivalence clinical trials

Area of Science:

• Clinical research methodology
• Biostatistics

Background:

• Evaluating clinical adverse events is crucial for drug safety.
• Existing methods may not fully capture the dynamic nature of adverse events.

Purpose of the Study:

• To develop a statistical model for evaluating the relationship between clinical adverse events and treatments.
• To provide a more accurate assessment of treatment-related adverse event rates.

Main Methods:

• Adverse event data was collected in time intervals.
• Repeatedly measured count data represented event onset and duration.
• Generalized estimating equation (GEE) technique with mixed-effects models was employed.

Main Results:

• The statistical model demonstrated that adverse event onset and duration impact the relative rate.
• Total person-days (patient exposure) also influenced the relative rate of adverse events.
• The model effectively integrates multiple factors in adverse event evaluation.

Conclusions:

• The proposed statistical approach offers a valuable alternative for evaluating clinical adverse events.
• This method supplements existing approaches for a comprehensive safety assessment.
• The model enhances the understanding of treatment-related adverse event dynamics.