Stepped wedge cluster randomized trials (SW-CRT) is a kind of cluster randomized controlled trial mainly applied in the field of public health policy that has emerged in recent years, which has gradually attracted the attention of workers in the field of health and wellness. At present, this trial method is not widely used at home and abroad, and there are various ways of sample size calculation and statistical analysis. This paper describes the principles, categories, and differences between SW-CRT and traditional randomized controlled trials, and outlines sample size calculation and statistical analysis methods. In general, SW-CRT is characterized by clustering, cross-design, and measurement of results at multiple time points. In terms of sample size calculation, it is necessary to distinguish between clusters with the same and different sizes, and commonly used sample size calculation procedures can be implemented in Stata, R, and SAS software, as well as in fixed online websites, including the "Steppedwedge" program, the "swCRTdesign" program, the "Swdpwr" program, the "CRTpowerdist" program, and the "Shiny CRT Calculator" tool and so on. Based on the design characteristics of SW-CRT, the researcher should also consider the confounding factors of time effects and repeated measurements of result. Therefore, the statistical analysis methods are often based on generalized linear mixed model (GLMM) and generalized estimating equations (GEE). However, most of the above models have been proposed based on cross-sectional studies, there is a lack of statistical methods for queue design and SW-CRT with transitional period now, and more comprehensive methodological exploration is still needed in the future.
In recent years, investment in new drug development in China has surged; however, it faces challenges such as difficulties in efficacy validation, high failure rates, and lengthy, costly clinical trials. The traditional model is insufficient to address these issues, necessitating innovation. Adaptive designs (AD), particularly sequential multiple assignment randomized trials (SMART), have emerged as a flexible and efficient new pathway for drug development. This study focused on the two-stage design of SMART, analyzed its principles, and contrasted it with randomized controlled trials, group sequential designs, and crossover designs. The advantages of SMART were highlighted in terms of its precision in evaluating treatment strategies, minimizing sample wastage, and enhancing the exploration of complex treatment pathways. Through case analyses, we demonstrated that SMART significantly improved clinical trial efficiency and the quality of treatment decisions, representing an innovative solution to the challenges of new drug development. This study aims to provide strategic references for clinical researchers and promote the adoption of adaptive designs in China, thereby facilitating the efficient advancement of new drug development.