Traditional randomized controlled trial and real-world study have different advantages in internal validity and external extensibility, respectively. With the development of evidence-based health decisions, randomized controlled trial was no longer the only golden standard of interventional study, the research evidence of the real world was gradually involved in health decisions. This study mainly analyzed the requirements of evidence and actual application of evidence in the evaluation of the effectiveness of NICE in the UK. It was found that NICE still used the results of randomized controlled trials as a primary basis. Although real-world research has developed rapidly in recent years, it was limited used in health decision because of its bias by design and other factors. However, in recent years, real-world evidence has played a significant role in the field of innovative drugs or diseases that lack therapeutic drugs. With the improvement of real-world research in experimental design and data analysis, it is expected that it will play a more important role in health decision-making.
Given the growing importance of real-world data (RWD) in drug development, efficacy evaluation, and regulatory decision-making, establishing a scientific and systematic data quality regulatory framework has become a strategic priority for global pharmaceutical regulatory authorities. This paper analyzed the EU's advanced practices in RWD quality regulation, compared the RWD quality regulatory systems of China and the EU, and aimed to derive implications for enhancing China's own framework. The EU has made significant progress by promoting the interconnection, intercommunication, and efficient utilization of data resources, implementing a collaborative responsibility mechanism spanning the entire data lifecycle, developing a standardized, tool-based quality assessment system, and facilitating international cooperation and alignment of rules. While China has established an initial regulatory system for RWD quality, it still confronts challenges such as unclear mechanisms for data acquisition and utilization, underdeveloped operational standards, and unclear responsibility delineation. In contrast, by adapting relevant EU experience, China can refine its regulatory framework, establish mechanisms for the interconnection, intercommunication, and efficient utilization of RWD, develop more practical quality assessment toolkits, improve the lifecycle responsibility-sharing mechanism, and promote the alignment of RWD quality regulation with international standards. These enhancements will advance the standardization and refinement of RWD quality regulation in China, ultimately strengthening the scientific rigor and reliability of regulatory decisions.
Observational studies based on real-world data are providing increasing amount of evidence for evaluating therapeutic outcomes, which is important for timely decision-making. Although time and costs for data collection could be saved using real-world data, it is significantly more complex to design real world researches with lower risk of bias. In order to enhance the validity of causal inference and to reduce potential risk of bias in real world studies, the Working Group of China Real world data and studies Alliance (China REAL) has formulated recommendations for designing observational studies to evaluate therapeutic outcomes based on real-world data. This guidance introduces design types commonly used in real world research; recommends key elements to consider in observational studies, including sample selection, specifying and allocating exposures, defining study entry and endpoints, and pre-designing statistical analysis protocols; and summarizes potential biases and corresponding control measures in real-world studies. These recommendations introduces key elements in designing observational studies using real-world data, for the purpose of improving the validity of causal inference. However, the application scope of these recommendations may be limited and warrant constant improvement.
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
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.
ObjectivesTo establish an appropriate data governance mode in according with the database status of clinical study.MethodsForty-six doctors of different seniority with clinical research experience from six hospitals in Beijing were selected by stratified purposeful sampling and semi-structured interview and were used to understand the status and shortcomings of data acquisition and storage in clinical research. The data resource of current clinical studies were summarized and the main target of data governance and the characteristics of clinical study data were explored to establish the domains of clinical study data governance to construct the framework of clinical research data governance.ResultsCurrently, the data sources of clinical studies were diverse, including real-world data from various medical and health records, data collected independently for clinical studies and numerous other sources. However, since collecting the data from electronic medical records was difficult for numerous reasons, a large number of researchers still collected research data by hand writing and stored it insecurely. In addition, the combination of electronic information from multiple sources was difficult. Building ALCOA+CCEA standard clinical research data management system based on clinical research data governance was urgent. Data governance includes data architecture, data model, data standards, data quality, master data, timeliness management, metadata and data security, while life cycle management and data insight were not essential parts.ConclusionsBased on the real-world data resources, domains of data governance in clinical study should include data architecture, data model, data standards, data quality, master data, timeliness management, metadata and data security.
ObjectiveTo evaluate the safety, efficacy, and cost-effectiveness of different uses of oxidized regenerated cellulose (ORC) in video-assisted thoracoscopic surgery (VATS) for lung cancer resection to provide a reference for the selection, clinical use, and rational utilization of absorbable hemostatic materials. MethodsA retrospective analysis of relevant data from inpatients who underwent VATS for lung cancer resection at a tertiary hospital from July 2019 to January 2020 and from July 2020 to December 2020 was conducted. Patients were divided into two groups based on the use of ORC: 1) combined use group (ORC and collagen sponge) and 2) sole-use group (ORC). Safety, efficacy, and economic outcome indicators were compared between the two groups. ResultsThe main analysis included a total of 904 patients, with 466 in the combined use group and 438 in the sole-use group. Compared to the combined use group, the sole-use group had a significantly longer hospital stay, used fewer hemostatic drugs, had a lower average cost of hemostatic materials, and a lower median total hospitalization cost (P<0.05). No statistically significant difference was found between the two groups in terms of intraoperative blood loss volume, massive blood loss rate, perioperative transfusion rate, reoperation rate, postoperative 48-hour drainage volume, bloody drainage fluid rate, or postoperative laboratory test indicators. ConclusionThere was no significant difference in the safety or efficacy of VATS for lung cancer resection between the sole use of ORC and the combined use of ORC, but the sole use of ORC was associated with a lower cost of hemostatic materials and a lower total hospitalization cost. The sole use of hemostatic gauze in VATS for lung cancer resection may be a more cost-effective choice.
In recent years, real-world evidence data (RWD) and real-world evidence (RWE) have gained substantial attentions from healthcare practitioners and health authorities worldwide. In particular, the needs from regulatory bodies have promoted the production and use of real-world evidence. In the context of drug and device evaluation and regulation decisions, the pattern for using real world evidence may differ. This article aimed to discuss the potential uses of RWE for pre-approval clinical evaluation, post-approval monitoring and evaluation, and associated regulatory decisions, which may ultimately improve the production and use of RWE for regulatory decisions.
With the increasing improvement of real-world evidence as a research system and guideline specification for pre-market registration and post-market regulatory decision support of clinically urgent drug and mechanical products, identifying an approach to ensure the high quality and standards of real-world data and establishing a basis for the generation of real-world evidence is receiving increasing attention and concern from regulatory authorities. Based on the experience of Boao hope city real-world data research pattern and ophthalmic data platform construction, this paper discussed the "source data-database-evidence chain" generation process, data management, and data governance in real-world study from the special features and necessity of multiple sources and heterogeneity of data, multiple research designs, and standardized regulatory requirements, and provided references for further construction of comprehensive research data platforms in the future.
The active comparator, new user (ACNU) design is an important design developed under the concept of the target simulation experimental framework. It aims to reduce indication confounding, immortal time bias, prevalence-incidence bias, and other unmeasured confounders by simulating head-to-head randomized controlled trials. It is widely applied in scenarios such as comparing the efficacy of newly marketed drugs with existing standard treatments, evaluating drug safety and adherence, exploring drug repurposing, and optimizing algorithms for processing medical big data. This article introduces the application and practice of the ACNU design in real-world data research from aspects such as concept, development, advantages and disadvantages, and implementation points, and also presents an outlook on its application in the field of traditional Chinese medicine. It is believed that with the progress in understanding the design of observational studies of real-world data, the ACNU design is expected to be more widely applied and provide new ideas for researchers' scientific research designs.