In January 2020, the State Food and Drug Administration issued the guiding principles of real world evidence supporting drug research & development (R&D) and evaluation (Trial) to guide the development of real world study (RWS) for drug R&D and review decision-making in the future. This guideline has important reference value for developing RWS of health food. Based on the interpretation of the core content of the guiding principles, combined with the common points of RWS and health food interventions, this paper preliminarily discusses the application of RWS to support health food regulatory decision-making so as to provide references for further promoting the application of RWS in the field of health food.
Objectives To analyze the labeling of drug items for patients with renal insufficiency in our hospital so as to provide reference for rational use of drugs. Methods The drug instructions used in No.1 Hospital of Jilin University in 2017 were collected. According to the classification of pharmacology, the instructions of the top 9 drugs system were selected. The annotation of drug items for patients with renal insufficiency in these pharmaceutical instructions was analyzed. Results A total of 812 drug instructions were included, in which 72.17% did not mark drug instruction for renal insufficiency patients. According to the administration system, the highest unlabeled rate were digestive system drugs; according to the method of administration, the highest unlabeled rate was external preparation of drugs, accounting for 83.33%; according to production enterprises, the highest unlabeled rate were domestic drugs, accounting for 75.55%. There were only 23.40% of the tagging items having guidance of medication, and some with a certain degree of confusion in the annotation. Conclusion The unlabelling situation of drug instructions for renal insufficiency patients is very serious. It should arouse the attention of pharmaceutical manufacturers and the pharmaceutical supervisory department is suggested to strengthen the supervision of drug instructions and regulate the contents of drug labeling in drug instructions, so as to guide the rational use of drugs in clinical practice.
Structured template and reporting tool for real world evidence (STaRT-RWE) was developed by a team led by professor Shirley V Wang of Brigham and Women's Hospital, Harvard Medical School, which is to plan and report on the implementation of real world evidence (RWE) studies on the safety and efficacy of treatments. The template, published in the journal BMJ in January 2021, has been endorsed by the International Society of PharmacoEpidemiology and the Transparency Initiative promoted by the International Society of Pharmacoeconomics and Outcome Research. This article interprets its entries to promote the understanding and application of STaRT-RWE by domestic scholars engaged in real world study, and help to improve the transparency, repeatability, and accuracy of RWE research.
ObjectiveTo analyze the status of real world studies (RWS) through registration information of the Chinese Clinical Trials Registry (ChiCTR). MethodsThe website of ChiCTR was searched with the real world as the search term to collect relevant registered items in the real world from inception to May 4, 2022. Descriptive analysis method was used. ResultsA total of 642 registered items were included. The median sample size was 482 cases. RWS were mainly observational studies, and the number of intervention studies was increasing year by year. There were 267 studies (41.59%) at the stage of post-marketing drugs or phase Ⅳ clinical trials. Most of the main measures were endpoints (56.23%), and the most commonly used was overall survival (15.79%). 62.15% of the registered projects met the minimum requirements for registration. ConclusionThe number of RWS registered by ChiCTR shows an increasing trend. At present, the research purpose of RWSs is unclear, and the completeness of registered studies and the overall content compliance of the studies need to be improved.
Recently, real world studies (RWS) have received increasing attentions. Such studies typically involve patient information, and their results may have potentially significant impact on patient well-being and safety. When reviewing the protocol of real world studies, ethical issues should be carefully considered and assessed. This paper discussed three issues, including the overview of bioethics and its application to classic clinical trials, key features of RWS, and medical ethical considerations on RWS.
Assessment of Real World Observational Studies (ArRoWS) is a tool developed by the Leicester Real World Evidence (LRWE) Unit of the Diabetes Research Centre of the University of Leicester in the United Kingdom to assess the quality of real world evidence research, and has been reported to have good practicability. ArRoWS can be used to quickly and specifically assess the quality of real world evidence research that uses electronic health record information. The tool contains 16 items, nine of which are common items, and seven of which are related to specific research designs. The current study introduces the development background, development process, assessment items, assessment criteria, and application methods of ArRoWS and other related aspects, to provide references for real world researchers in China.
ObjectivesTo analyze the active areas of real world studies on traditional Chinese medicine in China.MethodsCBM, CNKI, WanFang Data, PubMed and EMbase databases were electronically searched to collect real world studies on traditional Chinese medicine in China from inception to 26th April, 2018. The main research contents (research direction, data sources, and research methods) by Excel were extracted, together with the primary information by BICOMS-2 software and production of the network figures by NetDraw 2.084 software.ResultsEventually, 373 real world studies in traditional Chinese medicine were included, in which the initial one was punished in 2008. The top three ranking of authors involved in real world studies on traditional Chinese were Xie Yanming, Zhuang Yan, Yang Wei, and the top three ranking of institutions were Institute of Basic Research in Clinical Medicine of China Academy of Chinese Medical Sciences, School of Statistics of Renmin University of China, and the PLA Navy General Hospital. The amount of related studies in Beijing accounted for 74.26%. It was found that the active areas involve real world, hospital information system, real world study, drug combination, and propensity score method. In terms of the main studied contents on the use of traditional Chinese medicine in the real world, in which the top three were Fufang Kushen injection, Dengzhanxixin injection, and Shuxuetong injection. Digestive system disease, nervous system disease and cardiovascular disease received the highest attention rate, specifically stroke, coronary heart disease, virus hepatitis and hypertension. 58.18% studies were retrospective studies, 49.60% of the information were from the hospital information system, and 56.30% studies used data mining to carry out statistical analysis.ConclusionsMost real world studies on traditional Chinese medicine are based on HIS, and use data mining to study Chinese medicine preparations. The research attention on Chinese medicine is higher than that of the method of diagnosis and treatment, similarly the Chinese medicine preparations is higher than traditional Chinese medicine. In future, attention should be paid to traditional Chinese medicine, prescription and traditional methods of diagnosis and treatment, such as moxibustion and scraping.
Mixed methods research (MMR) is the third research paradigm that combines quantitative and qualitative research. MMR can overcome limitations of qualitative and quantitative methods by integrating the advantages of these two. The environment of real world research is complicated. When using real world data to assess the health status of patients, process of treatment, outcomes of prevention and treatment, prognosis and prediction, and support for medical policy development, MMR can be applied to tackle research questions more comprehensively for the quality of research.
There is huge clinical value in real world data from traditional Chinese medicine (TCM), but the real world study of TCM faces many challenges, because of its diverse data types, different standards, and serious data island phenomenon. Data governance is the key to transforming real world data into real world evidence. As the last step of data governance, data transformation has not been standardized. The key technologies and methods of data transformation, including data classification, natural language processing, standardization, data system construction, and derivative variables, will be discussed in this article based on the characteristics of real world data of TCM and the current development status of data transformation technology. At the same time, the suggestions of safety control and quality control of data transformation are put forward, and the data transformation system of real world study of TCM is preliminarily constructed, combined with the characteristics of TCM data. It is hoped that this paper can provide references for future real world studies of TCM.
ObjectiveTo construct a strategy for classification of clinical research data security for real-world research, based on the features of clinical research data.MethodsBased on the laws, regulations, and data security classification method in relevant fields, the clinical research data was classified into five security levels. Then, the method was gradually perfected through three times of revisions, which followed the advice from experts who were experienced in many relative areas, such as clinical medicine, clinical research methodology, clinical research management, ethics, genetics and public health data application and management.ResultsExperts’ opinions gradually converged through several times of consultation. The clinical research data was finally classified into five security levels with explicit definition and security policy for each security level. Thirty-three data categories, which covered demographic information, clinical examination, diagnosis, treatment information, genetic information, health economics information, medical data and information on research processes that have been published, were included in the five security levels.ConclusionsSince there is an increasing trend of data scale and the data security classification and management are necessary to ensure the data security and appropriately utilization of data. The method of clinical research data classification proposed in this paper can provide beneficial references for the further improvement of data security in the future.