To explore clinical design methods that suit the characteristics of acupuncture science, this article mainly analyzes the design features of pragmatic randomized controlled trials and the advantages and current problems in clinical research on acupuncture. We discuss the differences between pragmatic randomized controlled trials and explanatory randomized controlled trials and the application status of clinical research about acupuncture. We consider that pragmatic randomized controlled trials suit the characteristics of in clinical research on acupuncture with complicated interventions. Exploring the application of pragmatic randomized controlled trials clinical research on acupuncture is beneficial to exploring appropriate clinical research methods that suit the specific characteristics of acupuncture subject, and to objectively and comprehensively assessing clinical efficacy and safety of acupuncture.
In order to improve the understanding of pragmatic randomized controlled trial (pRCT), to promote high-quality implementation of such trials, and to provide technical guidance for researchers to conduct such trials scientifically, the working group of China REal world data and studies ALliance (ChinaREAL) hereby develop a technical guidance. The guidance provides technical specifications of pRCT in terms of the concept and scope of application, planning and study design, conduct, data management and quality control, statistical analysis, and ethical issues. It emphasizes that the trial sites and settings, patient population, interventions, controls, outcomes, follow-ups and other factors should be considered when planning and designing. Meanwhile, the guidance recommends that estimation of sample sizes for different types of trial designs should be based on individual pRCTs, and it also provides suggestions for data management, quality control, principles of statistical analysis, analysis requirements for each type of trial designs, and ethical considerations.
In the study of real-world data, the pragmatic randomized controlled trial can provide the optimal evidence for clinical decisions. Although randomization protects against confounding, post-randomization confounding may still arise due to non-compliance. Traditional intention-to-treat analysis will drift apart from true estimation and lead to deviation of clinical decisions. Meanwhile, the alternative traditional methods would subject to bias and confounding. Thus, new methods are required for revolution, i.e., instrument variable method and modern per-protocol analysis. Our study reviews the defects of traditional methods in pragmatic randomized controlled trials, and then refers to two new methods with a detailed discussion of strengths and weaknesses. We aim to provide researches with insights on choosing the statistical methods for pragmatic trial.
Pragmatic randomized controlled trials can provide high-quality evidence. However, pragmatic trials need to frequently encounter the missing outcome data due to the challenges of quality assurance and control. The missing outcome could lead to bias which may misguide the conclusions. Thus, it is crucial to handle the missing outcome data appropriately. Our study initially summarized the bias structures and missingness mechanisms, and then reviewed important methods based on the assumption of missing at random. We referred to the multiple imputations and inverse probability of censoring weighting for dealing with missing outcomes. This paper aimed to provide insights on how to choose the statistical methods on missing outcome data.