• 1. Hainan Institute of Real World Data, Qionghai 571400, P. R. China;
  • 2. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
  • 3. Sichuan Center of Technology Innovation for Real World Data, Chengdu 610041, P. R. China;
  • 4. MSD R & D (China) Co. Ltd, Beijing 100012, P. R. China;
  • 5. Merck & Co., Inc., Rahway, New Jersey 07065, USA;
  • 6. Weill Cornell Medical College, New York 10021, USA;
  • 7. Hainan Service Center for Drug and Medical Device Evaluation, Haikou 570216, P. R. China;
LARRY Z. Liu, Email: liu.larry@merck.com; LIN Kai, Email: 439856605@qq.com; SUN Xin, Email: sunxin@wchscu.cn
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Randomised controlled trials are often difficult to conduct for rare diseases, the treatment of life-threatening and serious diseases with no effective treatment options, and single-arm clinical trials are one of the most common choices. However, single-arm clinical trials lack a control group, making it difficult to determine whether the observed treatment effects stem from the drug itself or are influenced by natural disease progression, placebo effects, or selection bias. In recent years, with the continuous accumulation of real-world data, it is possible to use real-world data to construct an external control for single-arm clinical trials. However, it is necessary to carefully consider how to select appropriate external control data to enhance the credibility of the results. Based on the existing studies and relevant laws and regulations in China and abroad, this study expounds the key considerations of using real-world data to construct the external control of single-arm clinical trials on the source data from the perspective of external control setting model, reference intervention selection, data source, and so on. This study could provide references for relevant researchers to conduct similar studies.

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