Evaluation method of "syndrome differentiation" of TCM based on adaptive interventions and sequential multiple assignment randomized trial_Chinese Journal of Evidence-Based Medicine

Authors：

ZHOU Sha ¹ , SHUAI Yuxing ² , JI Mengmeng ³ , QIAN Zhenzhen ⁴ , JIANG Yanhua ⁴ , JIN Zhiwei ⁴ , LIU Chi ⁵ , LI Hongyi ⁵ , XUAN Guowei ⁵ ,  CHEN Xinlin ²

1. Second Affiliated Clinical School, Guangzhou University of Chinese Medicine, Guangzhou 510403, P. R. China;
2. Basic Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510006, P. R. China;
3. School of life sciences, Ningxia University, Yinchuan 750021, P. R. China;
4. Institute of Clinical Basic Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China;
5. Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou 510120, P. R. China;

Corresponding author：

CHEN Xinlin, Email: chenxlsums@126.com

Keywords：

Sequential multiple assignment randomized trial (SMART); Adaptive interventions (AI); Clinical trial design; Adaptive design; Interim analysis

DOI：

10.7507/1672-2531.202404079

Video：

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The modern clinical research evaluation system has been increasingly emphasizing the evaluation of individual patients' clinical characteristics, diagnosis and treatment plans, and complex intervention measures. Traditional randomized controlled trial evaluated fixed interventions and non-adaptive treatment plans, which cannot meet the needs of evaluating adaptive interventions. This made researchers more inclined to explore an individualized and adaptive clinical trial design, then sequential multiple assignment randomized trial (SMART) emerged as the time 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.

1.	于亚南, 荆志伟, 刘骏, 等. 适应性治疗临床试验设计与辨证论治疗效评价的思考. 中国中医基础医学杂志, 2012, 18(3): 316-318.
2.	Murphy SA, Lynch KG, Oslin D, et al. Developing adaptive treatment strategies in substance abuse research. Drug Alcohol Depend, 2007, 88(Suppl 2): S24-S30.
3.	Kidwell KM, Postow MA, Panageas KS. Sequential, multiple assignment, randomized trial designs in immuno-oncology research. Clin Cancer Res, 2018, 24(4): 730-736.
4.	Murphy SA. Optimal dynamic treatment regimes. J R Stat Soc, 2003, 65(2): 331-366.
5.	Almirall D, Compton SN, Rynn MA, et al. SMARTer discontinuation trial designs for developing an adaptive treatment strategy. J Child Adolesc Psychopharmacol, 2012, 22(5): 364-374.
6.	Dawson R, Lavori PW. Placebo-free designs for evaluating new mental health treatments: the use of adaptive treatment strategies. Stat Med, 2004, 23(21): 3249-3262.
7.	Murphy SA. An experimental design for the development of adaptive treatment strategies. Stat Med, 2005, 24(10): 1455-1481.
8.	Lavori PW, Dawson R. Dynamic treatment regimes: practical design considerations. Clin Trials, 2004, 1(1): 9-20.
9.	Lavori PW, Dawson R. A design for testing clinical strategies: biased adaptive within-subject randomization. J R Stat Soc, 2000, 163(1): 29-38.
10.	Collins LM, Murphy SA, Bierman KL. A conceptual framework for adaptive preventive interventions. Prev Sci, 2004, 5(3): 185-196.
11.	Artman WJ, Nahum-Shani I, Wu T, et al. Power analysis in a SMART design: sample size estimation for determining the best embedded dynamic treatment regime. Biostatistics, 2020, 21(3): 432-448.
12.	Scott AI, Levy JA, Murphy SA. Evaluation of sample size formulae for developing adaptive treatment strategies using a smart design. University Park, PA: the Pennsylvania State University, the Methodology Center. 2007: Technical Report No. 07-81.
13.	Scott AI, Levy JA, Murphy SA. Statistical methodology for a smart design in the development of adaptive treatment strategies. University Park, PA: the Pennsylvania State University, the Methodology Center. 2007: Technical Report No. 07-82.
14.	Hsu JC. Simultaneous confidence intervals for all distances from the "best". Ann Stat, 1981, 9(5): 1026-1034.
15.	Hsu JC. Constrained simultaneous confidence intervals for multiple comparisons with the best. Ann Stat, 1984, 12(4): 1136-1144.
16.	Hsu JC. Multiple comparisons. London: Springer US: 1996.
17.	Ertefaie A, Shortreed S, Chakraborty B. Q-learning residual analysis: application to the effectiveness of sequences of antipsychotic medications for patients with schizophrenia. Stat Med, 2016, 35(13): 2221-2234.
18.	Auyeung SF, Long Q, Royster EB, et al. Sequential multiple-assignment randomized trial design of neurobehavioral treatment for patients with metastatic malignant melanoma undergoing high-dose interferon-alpha therapy. Clin Trials, 2009, 6(5): 480-490.
19.	Collins LM, Nahum-Shani I, Almirall D. Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clin Trials, 2014, 11(4): 426-434.
20.	Rubin DB. Estimating causal effects of treatments in randomized and nonrandomized studies. Educ Psychol, 1974, 66(2): 688-701.
21.	Rubin DB. The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat Med, 2007, 26(1): 20-36.
22.	Almirall D, Compton SN, Gunlicks-Stoessel M, et al. Designing a pilot sequential multiple assignment randomized trial for developing an adaptive treatment strategy. Stat Med, 2012, 31(17): 1887-1902.
23.	Hampton LH, Chow JC. Deeply tailoring adaptive interventions: enhancing knowledge generation of SMARTs in special education. Remed Spe Educ, 2022, 43(3): 195-205.
24.	Kraemer HC, Mintz J, Noda A, et al. Caution regarding the use of pilot studies to guide power calculations for study proposals. Arch Gen Psychiatry, 2006, 63(5): 484-489.
25.	Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract, 2004, 10(2): 307-312.
26.	Chevret S. Bayesian adaptive clinical trials: a dream for statisticians only. Stat Med, 2012, 31(11-12): 1002-1013.
27.	Nahum-Shani I, Qian M, Almirall D, et al. Experimental design and primary data analysis methods for comparing adaptive interventions. Psychol Methods, 2012, 17(4): 457-477.
28.	Lu X, Nahum-Shani I, Kasari C, et al. Comparing dynamic treatment regimes using repeated-measures outcomes: modeling considerations in SMART studies. Stat Med, 2016, 35(10): 1595-1615.
29.	Dziak JJ, Yap JRT, Almirall D, et al. A data analysis method for using longitudinal binary outcome data from a SMART to compare adaptive interventions. Multivariate Behav Res, 2019, 54(5): 613-636.
30.	沈澍农. “证候”与“证”“候”的溯源与诠证. 南京中医药大学学报(社会科学版), 2022, 23(4): 211-225.
31.	刘颖, 徐力. 徐力基于“三段六辨”模式治疗肺结节经验. 山东中医杂志, 2023, 42(11): 1211-1214,1229.
32.	刘保延. 有关辨证论治临床评价若干问题的思考. 中医杂志, 2007, 48(1): 12-14.
33.	Flynn D, Eaton LH, Langford DJ, et al. A SMART design to determine the optimal treatment of chronic pain among military personnel. Contemp Clin Trials, 2018, 73: 68-74.
34.	曹卉娟, 刘建平. SMART设计在中医非药物疗法疗效评价中的应用探讨. 北京中医药, 2020, 39(1): 78-80.
35.	卜志军, 张雨欢, 孙源, 等. SMART设计样本量估算方法及应用. 现代中医临床, 2024(7): 1-6.
36.	孙源, 鞠传兰, 郑薇, 等. 中医药SMART设计分析思路及统计方法应用. 现代中医临床, 2024(7): 1-8.
37.	周莎. 金匮泽泻汤辨治痰湿型良性阵发性位置性眩晕的SMART设计探索研究. 北京: 中国中医科学院, 2022.

1. 于亚南, 荆志伟, 刘骏, 等. 适应性治疗临床试验设计与辨证论治疗效评价的思考. 中国中医基础医学杂志, 2012, 18(3): 316-318.
2. Murphy SA, Lynch KG, Oslin D, et al. Developing adaptive treatment strategies in substance abuse research. Drug Alcohol Depend, 2007, 88(Suppl 2): S24-S30.
3. Kidwell KM, Postow MA, Panageas KS. Sequential, multiple assignment, randomized trial designs in immuno-oncology research. Clin Cancer Res, 2018, 24(4): 730-736.
4. Murphy SA. Optimal dynamic treatment regimes. J R Stat Soc, 2003, 65(2): 331-366.
5. Almirall D, Compton SN, Rynn MA, et al. SMARTer discontinuation trial designs for developing an adaptive treatment strategy. J Child Adolesc Psychopharmacol, 2012, 22(5): 364-374.
6. Dawson R, Lavori PW. Placebo-free designs for evaluating new mental health treatments: the use of adaptive treatment strategies. Stat Med, 2004, 23(21): 3249-3262.
7. Murphy SA. An experimental design for the development of adaptive treatment strategies. Stat Med, 2005, 24(10): 1455-1481.
8. Lavori PW, Dawson R. Dynamic treatment regimes: practical design considerations. Clin Trials, 2004, 1(1): 9-20.
9. Lavori PW, Dawson R. A design for testing clinical strategies: biased adaptive within-subject randomization. J R Stat Soc, 2000, 163(1): 29-38.
10. Collins LM, Murphy SA, Bierman KL. A conceptual framework for adaptive preventive interventions. Prev Sci, 2004, 5(3): 185-196.
11. Artman WJ, Nahum-Shani I, Wu T, et al. Power analysis in a SMART design: sample size estimation for determining the best embedded dynamic treatment regime. Biostatistics, 2020, 21(3): 432-448.
12. Scott AI, Levy JA, Murphy SA. Evaluation of sample size formulae for developing adaptive treatment strategies using a smart design. University Park, PA: the Pennsylvania State University, the Methodology Center. 2007: Technical Report No. 07-81.
13. Scott AI, Levy JA, Murphy SA. Statistical methodology for a smart design in the development of adaptive treatment strategies. University Park, PA: the Pennsylvania State University, the Methodology Center. 2007: Technical Report No. 07-82.
14. Hsu JC. Simultaneous confidence intervals for all distances from the "best". Ann Stat, 1981, 9(5): 1026-1034.
15. Hsu JC. Constrained simultaneous confidence intervals for multiple comparisons with the best. Ann Stat, 1984, 12(4): 1136-1144.
16. Hsu JC. Multiple comparisons. London: Springer US: 1996.
17. Ertefaie A, Shortreed S, Chakraborty B. Q-learning residual analysis: application to the effectiveness of sequences of antipsychotic medications for patients with schizophrenia. Stat Med, 2016, 35(13): 2221-2234.
18. Auyeung SF, Long Q, Royster EB, et al. Sequential multiple-assignment randomized trial design of neurobehavioral treatment for patients with metastatic malignant melanoma undergoing high-dose interferon-alpha therapy. Clin Trials, 2009, 6(5): 480-490.
19. Collins LM, Nahum-Shani I, Almirall D. Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clin Trials, 2014, 11(4): 426-434.
20. Rubin DB. Estimating causal effects of treatments in randomized and nonrandomized studies. Educ Psychol, 1974, 66(2): 688-701.
21. Rubin DB. The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat Med, 2007, 26(1): 20-36.
22. Almirall D, Compton SN, Gunlicks-Stoessel M, et al. Designing a pilot sequential multiple assignment randomized trial for developing an adaptive treatment strategy. Stat Med, 2012, 31(17): 1887-1902.
23. Hampton LH, Chow JC. Deeply tailoring adaptive interventions: enhancing knowledge generation of SMARTs in special education. Remed Spe Educ, 2022, 43(3): 195-205.
24. Kraemer HC, Mintz J, Noda A, et al. Caution regarding the use of pilot studies to guide power calculations for study proposals. Arch Gen Psychiatry, 2006, 63(5): 484-489.
25. Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract, 2004, 10(2): 307-312.
26. Chevret S. Bayesian adaptive clinical trials: a dream for statisticians only. Stat Med, 2012, 31(11-12): 1002-1013.
27. Nahum-Shani I, Qian M, Almirall D, et al. Experimental design and primary data analysis methods for comparing adaptive interventions. Psychol Methods, 2012, 17(4): 457-477.
28. Lu X, Nahum-Shani I, Kasari C, et al. Comparing dynamic treatment regimes using repeated-measures outcomes: modeling considerations in SMART studies. Stat Med, 2016, 35(10): 1595-1615.
29. Dziak JJ, Yap JRT, Almirall D, et al. A data analysis method for using longitudinal binary outcome data from a SMART to compare adaptive interventions. Multivariate Behav Res, 2019, 54(5): 613-636.
30. 沈澍农. “证候”与“证”“候”的溯源与诠证. 南京中医药大学学报(社会科学版), 2022, 23(4): 211-225.
31. 刘颖, 徐力. 徐力基于“三段六辨”模式治疗肺结节经验. 山东中医杂志, 2023, 42(11): 1211-1214,1229.
32. 刘保延. 有关辨证论治临床评价若干问题的思考. 中医杂志, 2007, 48(1): 12-14.
33. Flynn D, Eaton LH, Langford DJ, et al. A SMART design to determine the optimal treatment of chronic pain among military personnel. Contemp Clin Trials, 2018, 73: 68-74.
34. 曹卉娟, 刘建平. SMART设计在中医非药物疗法疗效评价中的应用探讨. 北京中医药, 2020, 39(1): 78-80.
35. 卜志军, 张雨欢, 孙源, 等. SMART设计样本量估算方法及应用. 现代中医临床, 2024(7): 1-6.
36. 孙源, 鞠传兰, 郑薇, 等. 中医药SMART设计分析思路及统计方法应用. 现代中医临床, 2024(7): 1-8.
37. 周莎. 金匮泽泻汤辨治痰湿型良性阵发性位置性眩晕的SMART设计探索研究. 北京: 中国中医科学院, 2022.

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