As a novel research model that can address multiple research questions within an overall trial structure, master protocol design shares similarities with the clinical research on syndrome-based traditional Chinese medicine in terms of study design. The sample size estimation in master protocol design is characterized by analyzing the subtrials separately and re-estimation at interim analyses. Specific methods include the combination of Simon’s two-stage design and Bayesian hierarchical design that facilitates information borrowing. By drawing on these methods to estimate dynamically and adjust the sample size for each subtrial in a targeted manner, it is expected to provide a feasible approach for the methodological development of sample size estimation in the field of clinical research on syndrome-based traditional Chinese medicine.
Sample size re-estimation (SSR) refers to the recalculation of the sample size using the existing trial data as original planned to ensure that the final statistical test achieved the pre-defined goals. SSR can enhance research efficiency, save trial costs, and accelerate the research process. Depending on whether the group assignment of the patients is known, SSR is divided into blinded sample size re-estimation and unblinded sample size re-estimation. Blinded sample size re-estimation can estimate the variance of the primary evaluation index through the EM algorithm or single sample variance re-estimation method, and then calculate the sample size. Unblinded sample size re-estimation can calculate the sample size by estimating the overall variance or therapeutic effect difference, but it needs to control the family wise type I error (FWER) rate. Cui-Hung-Wang method, conditional rejection probability method, P-value combination method, conditional error function, and promising zone are common methods used to control FWER. Currently, there are application examples of SSR methods. With the maturation of related theories and the popularization of methods, it is expected to be widely applied in clinical trials, especially in traditional Chinese medicine clinical trials in the future.
