PAN Zhiyu 1 , ZHU Jian 1 , WU Hongli 1 , YU Yanan 1 , JIANG Yanhua 2 , ZHOU Sha 3 , WU Guang 1 , JING Zhiwei 1
  • 1. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China;
  • 2. Department of Oncology, Yantai Hospital of Traditional Chinese Medicine, Yantai 264001, P. R. China;
  • 3. The Second School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, P. R. China;
JING Zhiwei, Email: drjzw@163.com
Adaptive design; Dynamic treatment regime; Sequential multiple assignment randomized trial; Chronic diseases; Generalized estimating equations
10.7507/1672-2531.202509146
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Objective  This study aims to systematically review the current application status of sequential multiple assignment randomized trials (SMART) in the past decade. The goal is to clarify the research fields, research objectives, design elements, and data analysis methods of SMART clinical reports, and to provide evidence-based references for the subsequent standardized design and reporting of SMART. Methods  The PubMed, Embase, Web of Science, APA PsychInfo, Scopus, CNKI, WanFang Data, VIP databases were electronically searched to collect studies on SMART-related clinical studies published from 2015 to 2025. Descriptive statistics and inductive thematic analysis methods were used to summarize and analyse the extracted data. Results  A total of 153 articles were included. The results showed that the number of publications has been increasing year by year; the research was mainly concentrated in the United States (n=133), followed by China (n=11). The research fields were mainly in psychology and psychiatry (42%), endocrinology (12%), and cancer (11%). The research goals were diverse, with the comparison of dynamic treatment strategies (14%) being the most common. In terms of trial design, the initial grouping was mostly two groups, with a 1: 1 ratio between groups being the most common; two-stage multiple randomizations were mostly used, ultimately forming 4-8 subgroups; sample sizes were mostly between 100 and 500 cases (48%). Data analysis methods were diverse, depending on the research purpose, data characteristics, and design type. Longitudinal data analysis mainly used linear mixed-effects models (66 times) and generalized estimating equations (31 times), and Q-learning (16 times) was the mainstream method for constructing optimal decision rules. Additionally, the study found that the detail related to data processing was generally underreported. Conclusion  As a primary method for evaluating clinical dynamic treatment strategies, SMART has issues such as imbalanced geographical and disciplinary distribution, incomplete reporting of design elements, and insufficient standardization of data processing. In the future, it is necessary to promote the expansion of international reporting standards, strengthen methodological research, and encourage the validation of its extrapolation and clinical translation value in a wider range of disease fields and regions.

Citation： PAN Zhiyu, ZHU Jian, WU Hongli, YU Yanan, JIANG Yanhua, ZHOU Sha, WU Guang, JING Zhiwei. A study on the application status of sequential multiple assignment randomized trials. Chinese Journal of Evidence-Based Medicine, 2026, 26(4): 479-484. doi: 10.7507/1672-2531.202509146 Copy

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