Estimation of a Suitable Number of Patients for Selective Safety Data Collection (ICH E19 Draft Guideline): When is the Safety Profile of a Drug Well Characterized?

PURPOSE: We propose methods to estimate a suitable number of patients for implementing selective safety data collection (SSDC) in clinical investigations based on a confidence interval of the incidence rate or risk difference using Monte Carlo simulation. METHODS: The incidence rates and risk differences of adverse events (AEs) were based on the safety outcome measures. A suitable number of patients for implementing SSDC was estimated based on the probability that the half-width of the two-sided 95% confidence interval of incidence rate or risk difference was equal to or less than a pre-specified cut-off value (0.5-3.0%). Monte Carlo simulation was used to estimate the suitable number of patients at probabilities of 70%, 80%, and 90%. The applicability of our proposed method for estimating a suitable number of patients for SSDC implementation was confirmed based on the incidence rates or risk differences from actual clinical trial data for panitumumab. RESULTS: We demonstrated the performance of our proposed method in estimating a suitable number of patients to implement SSDC in several situations. Furthermore, according to the safety datasets of three phase III clinical trials, the number of suitable patients for implementing SSDC using incidence rates or risk differences of common AEs with panitumumab could confirm the applicability of our proposed method. CONCLUSION: A suitable number of patients estimated based on our proposed method may be one of the foundations for implementing SSDC, as additional data accrual may not impact the precision of the estimates of the frequency of common AEs.