Multilevel models are applicable to both the quantitative data and categorical variables. We used the methods, including the multilevel models, analysis of covariance and CMH chi-square test, to analyse different types of data, to explore the application of multilevel models in the analysis of the multicenter clinical trial center effect. The results showed that the analysis of covariance is more sensitive to find the center effect for quantitative data, while multilevel models are more sensitive to categorical variables. It can be seen that results with different analytical methods for center effect are not the same, and the most appropriate method should be selected in accordance with the characteristics of data, the objective of research, and the applicable conditions of the various methods in practical use.
BugsXLA is a Microsoft Excel add-in that facilitates Bayesian analysis of GLMMs and other complex model types by providing an easy to use interface for the BUGS package. BugsXLA macro is of good compatibility, ease to operation, smoothly running, low memory cost, and ease for data entry, extraction, and storage compared with other software which can calling BUGS to perform network meta-analysis currently. BugsXLA macro also integrates data storage and calculation. However, its function of plot drawing is very simple and only draws the density plot nowadays; Moreover, the function for calling WinBUGS is mature while is premature for calling OpenBUGS.
This article introduces two methods used to calculate effect indicators and their standard errors with non-comparative binary data. Then we give an example, the effect indicators and standard errors are calculated using both methods, and meta-analysis with the outcomes is conducted using RevMan software. At last the calculated results are compared with the results of meta-analysis conducted using Stata software with original data based on cases. The results of meta-analysis performed in RevMan software and Stata software are consistent in calculating non-comparative binary data.
Mini health technology assessment (mini-HTA) is a decision support tool based on the principle and method of evidence-based medicine and traditional HTAs. It systematically reviews healthy technologies and provides references for decision makers at the hospital level in terms of introducing relevant health technologies. In order to provide a new insight to the decision makers, this paper briefly introduces the features of mini-HTA.
ObjectiveTo analyze the status of systematic reviews/meta-analyses on tuberculosis. MethodsThe Web of Science was searched for systematic reviews/meta-analyses on tuberculosis up to February 4th, 2015. According to the inclusion and exclusion criteria, two reviewers screened literature and extracted data. Then SPSS 11.0 software was used to analysis data including publication year, country, institution, journal and citation situation. ResultsA total of 461 systematic reviews/meta-analyses were included. The publication numbers was increasing from 1 in 1997 to 82 in 2014. Among them, China ranked the top country (113 studies), followed by the USA and Canada. The area with the most number of countries where studies were published was Europe, followed by Asia and Africa. In terms of institution, McGill University in Canada ranked the top, followed by University of London in England and Sichuan University in China. As for the number of papers in journals, the International Journal of Tuberculosis and Lung Disease ranked the top, followed by PLOS One and European Respiratory Journal. In the terms of citation, the citation ranged from 0 to 591, and the median citation frequency was 8. ConclusionThe systematic reviews/meta-analyses on tuberculosis is gradually increasing; the developed countries are still important output areas; and China is playing more and more important role in this research field.
The pcnetmeta package in R is a special package for performing network meta-analysis based on Bayesian theory, which combines the strength computing function of JAGS software and the special data integration and powerful graph drawing function of R software. This package conducts calculation by calling JAGS, provides 3 different models for users, and each model can yield results of 3 effect-sizes (RR, OR and RD). At the same time, this package can draw many kinds of plots, which greatly meets actual needs of users to deal with complicated network meta-analysis. In this article, we introduce how to use pcnetmeta package to perform network meta-analysis based on an example.
This article discussed the development and current situation about both national and international diagnostic practice guidelines, as well as the role of evidence based medicine and systematic reviews in the development of such guidelines. Authors also analyzed the opportunities and challenges developers faced, and the methods and processes of development. Finally, authors proposed several strategic suggestions about how to improve the quality of diagnostic practice guideline in China.
Traditional Chinese Medicine (TCM) standardization is an important carrier for TCM inheriting and innovating. As an important content of TCM standardization system, TCM clinical practice guidelines' designation and revision play an important role for medical staff to regulate medical behavior, and improve the quality of health services. This paper expounds the significance and function of the TCM guidelines, analyzes the present situation, opportunities and challenges, and puts forward the strategies and suggestions to promote the development of evidence-based TCM guidelines.
The approaches of rating the quality of evidence of systematic reviews of diagnostic accuracy tests are different from systematic reviews of interventional studies. This article systematically introduces the application of GRADE in systematic reviews of diagnostic accuracy tests by a case interpretation and analysis. In this article we present rating workflow in systematic reviews of diagnostic accuracy tests and introduce how to use the GDT website to display the rating results, and interpret the conclusion of systematic reviews based on GRADE results.
Depending on different designs of original studies, systematic reviews of diagnostic studies could be categorized into two kinds:one is based on diagnostic randomized controlled trials, of which the GRADE rating approach is similar to that of interventional systematic reviews; and the other is based on diagnostic accuracy tests, of which the GRADE rating approach is introduced in this article. This article explains the application of GRADE in systematic reviews of diagnostic accuracy tests mainly from the angle of theoretical analysis, including rationales, methods, and challenges.