Design and Challenges of Real World Data as Control Group in A Randomized Controlled Trial of Chinese Medicine
10.13422/j.cnki.syfjx.20230194
- VernacularTitle:中医药随机对照试验中采用真实世界数据作为对照组的研究设计及挑战
- Author:
Jing HU
1
;
Bo LI
1
;
Huina ZHANG
1
;
Shuo FENG
1
;
Xing LIAO
2
Author Information
1. Beijing Hospital of Traditional Chinese Medicine， Capital Medical University，Beijing Institute of Chinese Medicine，Beijing 100010，China
2. Center for Evidence-based Chinese Medicine， Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences，Beijing 100700，China
- Publication Type:Journal Article
- Keywords:
randomized controlled trial;
real-world data;
traditional Chinese medicine;
propensity score method;
efficacy evaluation
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2023;29(1):181-187
- CountryChina
- Language:Chinese
-
Abstract:
In the design of randomized controlled trials （RCT）， difficulties in patient recruitment and enrollment of control group would limit the overall implementation of the trials. In recent years， as a data source， real-world data （RWD） plays an increasingly important role in the medical field. In RCT of Chinese medicine， RWD could be designed as control group. This design can effectively solve the problem of inclusion difficulty for the patients in the western medicine control group of traditional Chinese medicine（TCM） RCT， it also can provide high quality evidence to evaluate the efficacy of TCM. In recent years， propensity score method has been widely used to deal with confounding factors in real world study. In this paper， four common research designs based on propensity score method were introduced with examples， including propensity score matching and data augmentation， two-stage design of propensity score stratification method， propensity score-integrated composite likelihood approach， and combination of different propensity score methods. However， there are some methodological challenges in this type of design， including the RWD data sources must be of high quality and the key information needs to be collected in a standardized method， the baseline characteristics of RCT and RWD patients should be comparable， and all known covariates related to the intervention and outcome need to be included for analysis. When adopting this design in the field of TCM， there are still some problems such as the lack of TCM syndrome information and TCM outcomes in RWD. When using RWD， it is necessary to decide how to analyze according to the data condition. This paper discussed the design types and methodological challenges of using RWD as control group in RCT， hoping to provide methodological ideas for researchers to use this type of design in the future.
