In 2019, the national government issued the document "Implementation Plan for Supporting the Construction of the Boao Lecheng International Medical Tourism Pilot Area", which allowed the use of innovative drugs and medical devices in medical institution of Boao Lecheng. These medical products had been designed to meet urgent clinical requirements and had been approved by regulatory authorities overseas. Through the use of these medical products, real-world data were generated in the routine clinical practice, based on which real-world evidence might be produced for regulatory decision-making by using scientific and rigorous methods. In March 2020, the first medical device product using domestic real-world data was approved, suggesting that the real-world data initiative in Boao Lecheng achieved initial success. This work also provided important experience for promoting the practice of medical device regulatory decision-making based on real-world evidence in China. Here, we shared the preliminary experiences from the study on the first approved medical device product and discussed the issues on developing a real-world data research framework in Boao Lecheng in attempt to offer insights for future studies.
With the acceleration of global innovative drug development, selecting safe, effective, and cost-effective products from numerous drugs has posed new challenges for the decision-making process of medical insurance drug access and dynamic updating of insurance directory. Real-world data (RWD) provides a new perspective for evaluation of clinical and economic value of drugs, but there are still uncertainties regarding the scope, quality standards, and evidence categories of RWD that can be used. Based on the current status of domestic and international RWD supporting the assessment of the clinical and economic value of drugs, this paper, in collaboration with national RWD and healthcare experts, has developed the key considerations for using real-world data to evaluate the clinical and economic value of drugs. This paper first clarifies the scope of RWD that can be used to evaluate the clinical and economic value of drugs evaluate; secondly, provides specific requirements and guidance on data attribution, data governance, and quality standards for RWD; finally, summarizes the evidence categories of RWD supporting evaluate the clinical and economic value of drugs evaluate.
Earthquake emergency medical rescue evidence-based decision-making is a typical case of real-world evidence deriving from real-world data, conducting real-world research, and producing real-world evidence for solving real-world problems. This article focuses on the use of evidence-based science in the real-world through a problem-oriented, evidence-based decision making way, as well as transferring of results to practice and continuing outcome evaluation.
ObjectiveTo systematically review the difference in 30-day readmission rates among acute heart failure patients between real-world studies vs. randomized controlled trials (RCTs). MethodsPubMed, EMbase, The Cochrane Library, CNKI, CBM, VIP and WanFang Data databases were electronically searched to collect clinical studies on 30-day readmission rates in patients with acute heart failure from inception to April 12th, 2021. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Meta-analysis was then performed using Stata 16.0 software. ResultsA total of 33 real-world studies and 11 RCTs involving 106 722 subjects were included. The results of meta-analysis showed that the 30-day heart failure-related readmission rates in the real-world studies and RCTs were 10.8% (95%CI 9.3% to 12.3%) and 6.9% (95%CI 5.3% to 8.4%), respectively. The 30-day all-cause readmission rates in real-world studies and randomized controlled studies were 18.6% (95%CI 15.7% to 21.4%) and 14.2% (95%CI 12.0% to 16.3%), respectively. There were statistically significant differences between two kinds of studies (P<0.05). ConclusionsCurrent evidence suggests that the 30-day heart failure-related and all-cause readmission rates in patients of acute heart failure in real-world studies are significantly higher than those in patients of RCTs. Due to the limited quality and quantity of included studies, more high-quality studies are required to verify the above conclusions.
Real-world evidence represents critical evidence to support post-marketing drug monitoring, assessment and policy decisions, and has received extensive attentions. However, an explicit over-arching design and conceptual framework for this specific area is lacking. Divergent opinions on the production of real world evidence are often present among researchers; and understanding about their implications also differ among policy makers and evidence users. In this article, we have proposed, from the regulatory and clinical perspectives, a conceptual framework on the use of real world data for post-marketing drug studies, assessment and policy decisions.
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.
Real-world data (RWD) in clinical research on specific categories of medical devices can generate sufficient quality evidence which will be used in decision making. This paper discusses the limitations of traditional randomized controlled trials in clinical research of medical devices, summarizes and analyses the applicable conditions of real-world evidence (RWE) for medical devices, interprets the new FDA guidance document on the characteristics of RWD for medical devices, in order to provide evidence for the use of RWE in medical devices in our country.
Evidence-based medicine is the methodology of modern clinical research and plays an important role in guiding clinical practice. It has become an integral part of medical education. In the digital age, evidence-based medicine has evolved to incorporate innovative research models that utilize multimodal clinical big data and artificial intelligence methods. These advancements aim to address the challenges posed by diverse research questions, data methods, and evidence sources. However, the current teaching content in medical schools often fails to keep pace with the rapidly evolving disciplines, impeding students' comprehensive understanding of the discipline's knowledge system, cutting-edge theories, and development directions. In this regard, this article takes the opportunity of graduate curriculum reform to incorporate real-world data research, artificial intelligence, and bioinformatics into the existing evidence-based medicine curriculum, and explores the reform of evidence-based medicine teaching in the information age. The aim is to enable students to truly understand the role and value of evidence-based medicine in the development of medicine, while possessing a solid theoretical foundation, a broad international perspective, and a keen research sense, in order to cultivate talents for the development of the evidence-based medicine discipline.
Real-world studies (RWSs) data are based on real medical scenes and reflect clinical facts. Besides, RWSs adapts to the characteristics of therapeutic principles of traditional Chinese medicine and the medical reality of the combination of Western and traditional Chinese medicine, which makes the safety assessment of herb-drug interaction more efficient and economical. During RWSs, more attention should be paid on the validity and reliability of data, especially the standardization of the data collection process and its contents. The safety assessment of herb-drug interaction will combine the methods of active surveillance study, big data analysis, and be based on precision medicine in the future
In recent years, the Data Monitoring Committee (DMC) has played a crucial role in clinical trials, especially in protecting the safety of subjects and ensuring the integrity and credibility of trial results. With the rise of real-world study, the application of DMC in real-world settings has also gradually attracted attention. In this paper, the application of DMC in real-world study is discussed, the functions of DMC in safety monitoring, efficacy monitoring, research operation quality monitoring, and recommendations for modifications of research designs are analyzed, and the differences in DMC's functions between real-world study and randomized controlled trials are compared. Through case analysis, this paper summarizes the best practices of DMC in real-world study, so as to provide references for future related research.
