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.
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.
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 boom of information technology and data science, real-world evidence (RWE) which is produced using diverse real-world data (RWD) has become an important source for healthcare practice and policy decisions, such as regulatory and coverage decisions, guideline development, and disease management. The production of high-quality RWE requires not only complete, accurate and usable data, but also scientific and sound study designs and data analyses to enable the questions of interest to be reliably answered. In order to improve the quality of production and use of RWE, China REal world data and studies ALliance (ChinaREAL) has developed the first series of technical guidance for developing real-world data and subsequent studies. The efforts are ongoing which would ultimately inform better healthcare practice and policy decisions.
Real-world data is been increasingly valued nowadays. This paper combined with related requirements of clinical evaluation of medical devices in China, studied the role of real-world evidence in pre-marketing clinical evaluation of medical devices in terms of technical evaluation, in aim of providing reference for the future application of China's real-world evidence in pre-marketing clinical evaluation.
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.
With the real-world study (RWS) becoming a hotspot for clinical research, health data collected from routine clinical practice have gained increasing attention worldwide, particularly the data related to the off-label use of drugs, which have been at the forefront of clinical research in recent years. The guidance from the National Medical Products Administration has proposed that real-world evidence (RWE) can be an important consideration in supporting label expansions where randomized controlled trials are unfeasible. Nevertheless, how to use the RWE to support the approval of new or expanded indications remains unclear. This study aims to explore the structured process for the use of RWE in supporting label expansions of approved drugs, and to discuss the key considerations in such process by reviewing the documents from relevant regulatory agencies and publications from public databases, which can inform future directions for studies in this area.
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.
To enhance the quality and transparency of oncology real-world evidence studies, the European Society for Medical Oncology (ESMO) has developed the first specific reporting guidelines for oncology RWE studies in peer-reviewed journals ‘the ESMO Guidance for Reporting Oncology Real-World Evidence (GROW)’. To facilitate readers understanding and application of these reporting standards, this article introduces and interprets the development process and main content of the ESMO-GROW checklist.
ObjectiveWe constructed a real-world evidence evaluation system to provide reference for obtaining high-quality evidence in evidence-based medicine.MethodsThrough the investigation and analysis of the key factors influencing the real-world research evidence, combined with domestic and foreign literature and evaluation tools, we preliminarily constructed the indicators of the real-world evidence evaluation system, then consulted experts in related fields by the Delphi method, modified and determined the final evaluation indicators. ResultsThe indicators of the final real-world evidence evaluation system included 40 items. The recovery efficiencies of the two rounds of expert consultation were 88.2% and 100%; The expert coordination coefficients were 0.174 (P<0.001) and 0.189 (P<0.001). After the second round of consultation, the mean of Likert scale in the range of 3.73~4.93, and the coefficient of variation varied in the range of 0.05~0.21. ConclusionThe real-world evidence evaluation system constructed in this study has certain reliability and scientificity, which can provide a basis and help for the transformation of real-world research into high-quality evidence.