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.
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.
Compared with traditional clinical trials, the real-world studies set higher requirements on the authenticity (reality), applicability, and timeliness of the evidence obtained. In this paper, we brought up a hypothesis that creating synergies between observational and experimental studies may meet these requirements. And then it was discussed in three aspects including providing evidence, research design and execution. In addition, data analysis facilitated generating efficient and robust evidence which was in support of decision making. Finally, some enlightenment may be offered for Traditional Chinese Medicine evaluation methods based on the synergies of both study types.
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.
Objectives To estimate the elasticity of demand price elasticity and demand income of urban and rural residents’ self-purchase drug use and expenditure, and to analyze the sensitivity of self-purchase drug use and expenditure to the price change of drug purchase, resident income and medical institutions. Methods The data were derived from the fifth health service survey in Heilongjiang province in 2013. The Probit model was used to obtain the partial regression coefficients of the control variables in the regression model, and the demand elasticity of the self-purchase drug use was further measured by the partial regression coefficients, and the demand elasticity of self-purchase expenditure was obtained by the logarithmic regression model. Results A total of 5 289 households (14 431 persons) were included. The demand for self-purchase drug use of Heilongjiang province was 0.374 (P=0.000), the cross-price elasticity of self-purchase drug utilization and service was –0.184 (P=0.000), and the income elasticity was 0.083 (P=0.172). Since the price elasticity of the self-purchase drug expenditure was 0.675 (P=0.000), the income elasticity was 0.144 (P=0.069). Conclusions The use of self-purchased drugs in Heilongjiang province lacks price elasticity and is a necessity. There is a complementary relationship between the use of self-purchase drugs and medical institutions.
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.
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.
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.
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.