Systematic review, a kind of higher-level evidence in evidence-based medicine, has a fully developed method system. However, it has some defects in the updating strategy. The living systematic review can effectively improve the timeliness of system reviews by periodically obtaining clinical evidences and updating the results of systematic reviews in a timely manner. This study briefly introduces the developing, characteristics, conditions, implementation and applications of living systematic reviews.
Evidence-based medicine database is a type of digital resource, which is based on principles of evidence-based medicine. It collects clinical evidence as a major content to serve clinical decision-making. This paper focused on various types of evidence-based databases, such as clinical practice guidelines, systematic reviews, and clinical trials. After collecting some representative databases, it analyzed and compared their contents, functions and characteristics, in attempt to enhance understanding of the current situation and trends of development of evidence-based medicine databases.
A metadata standard is a high level document that establishes a common way of structuring and understanding data, and includes principles and implementation issues for utilizing the standard. It helps to record their collections and processes and to structure this information, and can be used to validate data integrity and quality. Metadata standards improve the quality and interoperability of information across information technology platforms by increasing compatibility, improving the consistency and efficiency of information collection, and reducing redundancy. This article introduced the progress and features of metadata standards of clinical research, and aimed to promote the standardization of clinical research and scientific process of therapeutic evaluation.
Obtaining the best evidence is an important part of practicing evidence-based medicine. Evidence grading is an indispensable tool and process in helping decision makers obtain the best evidence. However, the current research evidence is numerous, the quality of evidence is uneven, the evidence classification system is diverse and the standards are different. By reviewing the development history and process of evidence grading and recommendation system, this paper analyzed representative grading recommendation systems with representative and international influence, and expounded the status quo, characteristics and development trend of evidence grading development, so as to provide a reference for the grading recommendation system exploration in contemporary medical field.
Objectives To analyze evidence-based medicine (EBM) related projects funded by National Natural Science Foundation of China (NSFC) from 2000 to 2019. Methods The online NSFC database, Internet-based Science Information System, Biomart.cn, and MedSci.com were searched to obtain all EBM grants funded by NSFC. The achievements, Chinese papers and SCI-indexed papers, were obtained by searching the database of CNKI, VIP, SinoMed, WanFang Data and Web of Science. All data screened and extracted manually, and then managed and analyzed with Microsoft Excel 2016 software. Results The NSFC has funded 94 projects regarding EBM, with a total amount of 44.763 million Yuan (RMB) since 2000. Beijing, Shanghai, Guangdong and Sichuan ranked highly in the number of projects and their undertaking institutions and total amount of fundings. General programs and youth scientist programs constituted the main parts of fundings. The funded projects mainly originated from three subjects of new technologies and methods of TCM, health management and policy, clinical basis of integrated Chinese and western medicine. General programs contributed the most articles, while the distinguished young scientist programs had the highest average outputs. Three papers from Chinese EBM Center were published on BMJ and were highly cited. Conclusions Support of NSFC on EBM has increased continuously for the last twenty years, but it is still below the average. The fundings are unbalanced in areas and institutions. The supported research fields change every year, and show a trend of subjects aggregation.
Systematic review is an important method to obtain clinical decision evidence. The traditional systematic review is primarily conducted manually, which cannot meet the needs of rapid decision-making due to its high time and labor force cost as well as low efficiency. However, the development of information technology has laid the foundation for computer-aided systematic review methods. Attempts have been made to replace or enhance manual operations by introducing computer technology in all aspects of systematic review, thereby improving efficiency. This paper integrates the methodological research and its application of computer-aided systematic review both domestically and abroad from perspectives of literature acquisition, data processing and evidence evaluation. The aim of this paper is to understand the status quo and future trend in this field, and to provide reference for further researches related to automated systematic review technology.
The scientific research on prevention and control of coronavirus disease 2019 (COVID-19) has been a major and urgent task, of which clinical trials occupy a pivotal position in the entire prevention and control system. 204 relative clinical trials of traditional Chinese medicine (TCM) have been registered on Chinese Clinical Trial Registry. Through the analysis of all online public protocols of registered trials, it is found that the clinical studies of TCM in China showed lack of research foundation, tight time and heavy tasks, difficult clinical implementation, and disturbance by changes of the epidemic status. Based on these characteristics, this paper put forward several thoughts and suggestions on the quality management and design improvement for clinical trials of TCM preventing and treating COVID-19, in order to improve the quality of clinical trials in China, provide effective supports for the public health decision-making on the epidemic, and also give a reference for the prevention and control of epidemics in the future.
Objective To define an objective evaluation model for metadata integrity of randomized controlled trials (RCTs) in traditional Chinese medicine (TCM), and to evaluate the data integrity of RCT reports published in TCM journals. Methods Retrieving Chinese medicine RCT literature and extracting data, using the metadata specification list and customized evaluation model defined in the project "Intelligent Construction and Application Demonstration of the Evidence System of Chinese Medicine Dominant Diseases" to analyze RCTs from the perspective of data integrity. Results A metadata interface specification and an objective evaluation model for RCT metadata integrity were proposed. A total of 37 361 articles of 10 diseases from 1986 to 2020 were evaluated. Among them, 6 743 reports failed to meet the basic requirements of metadata specifications. The proportion of reports with no missing required items was between 73% and 97%. "tcm_disease" and "num_drop_total" had a greater impact on completeness for the required items. The reporting rates of the items in the "age_sd" and "history_sd" in the "group" section, and "dosage", "dosage_form" and "dosage_freq" in the "interventions" section were low. The average score of RCT report was 71.39 points. Conclusions There is room for improvement in the integrity of RCT data in TCM, and data reporting is urgently required to be standardized. The metadata specification and completeness objective evaluation model proposed in this study can provide references for improving the data integrity of clinical trial reports of TCM.
At present, the network meta-analysis has been rapidly developed and widely used, and it has the characteristic of quantifying and comparing the relative advantages of two or more different interventions for a single health outcome. However, comparison of multiple interventions has increased the complexity of drawing conclusions from network meta-analysis, and ignorance of the certainty of evidence has also led to misleading conclusions. Recently, the GRADE (grading of recommendations assessment, development and evaluation) working group proposed two approaches for obtaining conclusions from a network meta-analysis of interventions, namely, the partially contextualised framework and the minimally contextualised framework. When using partially contextualised framework, authors should establish ranges of magnitudes of effect that represent a trivial to no effect, minimal but important effect, moderate effect, and large effect. The guiding principles of this framework are that interventions should be grouped in categories based on the magnitude of the effect and its benefit or harm; and that when classifying, consider the point estimates, the rankings, and the certainty of the evidence comprehensively to draw conclusions. This article employs a case to describe and explain the principles and four steps of partially contextualised framework to provide guidance for the application of this GRADE approach in the interpretation of results and conclusions drawing from a network meta-analysis.
The primary advantage of network meta-analysis is the capability to quantify and compare different interventions for the same diseases and rank their benefits or harms according to a certain health outcome. The inclusion of a variety of interventions has increased the complexity of the conclusions drawing from a network meta-analysis, and based on the ranking results alone may lead to misleading conclusions. At present, there are no accepted standards for the conclusion drawing from a network meta-analysis. In November 2020, based on the evidence certainty results of network meta-analysis, the GRADE (Grades of Recommendations Assessment, Development and Evaluation) working group proposed two approaches to draw conclusions from a network meta-analysis: the partially contextualised framework and the minimally contextualised framework. This paper aimed to introduce principles and procedures of the minimal contextualised framework through a specific example to provide guidance for the network meta-analysis authors in China to present and interpret the results using minimally contextualised framework.