The modern clinical research evaluation systems have increasingly emphasized the evaluation of individual patients' clinical characteristics, diagnosis and treatment plans, and complex intervention measures. Traditional randomized controlled trials evaluate fixed interventions and non-adaptive treatment plans, which cannot meet the needs of evaluating adaptive interventions. This has made researchers more inclined to explore an individualized and adaptive clinical trial design, and sequential multiple assignment randomized trial (SMART) has emerged as needed. This article introduces the principles, key elements, and implementation points of SMART design, further explores the limitations of the mismatch between traditional Chinese medicine clinical trial design and syndrome differentiation treatment, and proposes that SMART design can meet the needs of traditional Chinese medicine clinical trials to inspire researchers in designing their plans.
In recent years, investment in new drug development in China has surged; however, challenges such as difficulties in efficacy validation, high failure rates, and lengthy, costly clinical trials have been faced. The traditional model is insufficient for addressing these issues, necessitating innovation. Adaptive design (AD), particularly sequential multiple assignment randomized trials (SMART), has 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 are highlighted in terms of its precision in evaluating treatment strategies, minimizing sample waste, 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, facilitating the efficient advancement of new drug development.
ObjectiveTo evaluate the quality of randomized controlled trials (RCTs) of Chinese medicine (TCM) formulated granules published in core journals in China. MethodsComputerized searches were conducted in CNKI, VIP, WanFang Data and CBM databases. The publicly published RCTs of TCM formulated granules were collected, with source from Peking University Core, CSSCI and EI. The following information was extracted: including title, the first author, the journals name, type of disease, year of publication, and source of drug. The included studies were evaluated using the CONSORT extension for CHM formulas (CONSORT-CHM formulas 2017), which included 25 items from title, abstract and keywords, introduction, research methods, steps, results, discussion, and other information. ResultsA total of 125 papers were included, which mainly included digestive system diseases (n=25), respiratory system diseases (n=17), and circulatory system diseases (n=17). The results showed that the overall reporting quality of RCTs of TCM formulated granules was poor. After the publication of the CONSORT–CHM formulas 2017, the reporting quality of RCTs of TCM formulated granules had no significant changes, while some items were still reported with poor quality. For example, 42.2% of RCTs did not adequately report how to generate allocation sequence, 93.3% of RCTs did not adequately report allocation concealment, and 62.2% of RCTs did not adequately report how to solve the missing data. ConclusionThe quality of RCTs reports on traditional Chinese medicine formula granules published in Chinese journals still needs to be improved. It is recommended that researchers, journals and reviewers attach importance to the application of CONSORT-CHM formula throughout the whole process of paper writing. In the future, more scientific and detailed requirements should be put forward for trial design and reporting standards in line with the characteristics of clinical trials of traditional Chinese medicine formula granules.
Response-adaptive randomization (RAR) dynamically adjusts the probability of assigning patients to different groups, optimizing treatment efficacy and participant welfare. It is particularly suitable for clinical studies involving multiple interventions or dose-finding and seamless phase II/III trials. This paper systematically introduces the concept, principles, and types of RAR, as well as its application in clinical trials (including traditional Chinese medicine research). It also provides R implementation code, offering researchers practical tools aimed at promoting the adoption of RAR in clinical practice.