A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.
ABSTRACT: The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves.We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation.We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software.Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based.
Project description:BACKGROUND: Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. FINDINGS: We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. CONCLUSIONS: It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software.
Project description:<h4>Background</h4>Decisions about the use of new technologies in health care are often based on complex economic models. Decision makers frequently make informal judgments about evidence, uncertainty, and the assumptions that underpin these models.<h4>Objectives</h4>Transparent interactive decision interrogator (TIDI) facilitates more formal critique of decision models by decision makers such as members of appraisal committees of the National Institute for Health and Clinical Excellence in the UK. By allowing them to run advanced statistical models under different scenarios in real time, TIDI can make the decision process more efficient and transparent, while avoiding limitations on pre-prepared analysis.<h4>Methods</h4>TIDI, programmed in Visual Basic for applications within Excel, provides an interface for controlling all components of a decision model developed in the appropriate software (e.g., meta-analysis in WinBUGS and the decision model in R) by linking software packages using RExcel and R2WinBUGS. TIDI's graphical controls allow the user to modify assumptions and to run the decision model, and results are returned to an Excel spreadsheet. A tool displaying tornado plots helps to evaluate the influence of individual parameters on the model outcomes, and an interactive meta-analysis module allows the user to select any combination of available studies, explore the impact of bias adjustment, and view results using forest plots. We demonstrate TIDI using an example of a decision model in antenatal care.<h4>Conclusion</h4>Use of TIDI during the NICE appraisal of tumor necrosis factor-alpha inhibitors (in psoriatic arthritis) successfully demonstrated its ability to facilitate critiques of the decision models by decision makers.
Project description:<h4>Background</h4>Meta-analysis is increasingly used as a key source of evidence synthesis to inform clinical practice. The theory and statistical foundations of meta-analysis continually evolve, providing solutions to many new and challenging problems. In practice, most meta-analyses are performed in general statistical packages or dedicated meta-analysis programs.<h4>Results</h4>Herein, we introduce Meta-Analyst, a novel, powerful, intuitive, and free meta-analysis program for the meta-analysis of a variety of problems. Meta-Analyst is implemented in C# atop of the Microsoft .NET framework, and features a graphical user interface. The software performs several meta-analysis and meta-regression models for binary and continuous outcomes, as well as analyses for diagnostic and prognostic test studies in the frequentist and Bayesian frameworks. Moreover, Meta-Analyst includes a flexible tool to edit and customize generated meta-analysis graphs (e.g., forest plots) and provides output in many formats (images, Adobe PDF, Microsoft Word-ready RTF). The software architecture employed allows for rapid changes to be made to either the Graphical User Interface (GUI) or to the analytic modules.We verified the numerical precision of Meta-Analyst by comparing its output with that from standard meta-analysis routines in Stata over a large database of 11,803 meta-analyses of binary outcome data, and 6,881 meta-analyses of continuous outcome data from the Cochrane Library of Systematic Reviews. Results from analyses of diagnostic and prognostic test studies have been verified in a limited number of meta-analyses versus MetaDisc and MetaTest. Bayesian statistical analyses use the OpenBUGS calculation engine (and are thus as accurate as the standalone OpenBUGS software).<h4>Conclusion</h4>We have developed and validated a new program for conducting meta-analyses that combines the advantages of existing software for this task.
Project description:SaSAT (Sampling and Sensitivity Analysis Tools) is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab, a numerical mathematical software package, and utilises algorithms contained in the Matlab Statistics Toolbox. However, Matlab is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated.
Project description:BACKGROUND: Single nucleotide polymorphism (SNP) genotyping is a major activity in biomedical research. Scientists prefer to have a facile access to the results which may require conversions between data formats. First hand SNP data is often entered in or saved in the MS-Excel format, but this software lacks genetic and epidemiological related functions. A general tool to do basic genetic and epidemiological analysis and data conversion for MS-Excel is needed. FINDINGS: The SNP_tools package is prepared as an add-in for MS-Excel. The code is written in Visual Basic for Application, embedded in the Microsoft Office package. This add-in is an easy to use tool for users with basic computer knowledge (and requirements for basic statistical analysis). CONCLUSION: Our implementation for Microsoft Excel 2000-2007 in Microsoft Windows 2000, XP, Vista and Windows 7 beta can handle files in different formats and converts them into other formats. It is a free software.
Project description:INTRODUCTION:Catheter-related bloodstream infection (CRBSI) is a major complication after central venous catheter insertion, which is associated with significant morbidity, mortality and additional medical costs. Many lock solutions for CRBSI have been evaluated. However, using traditional pairwise meta-analyses to summarise the evidence does not allow the inclusion of data from treatments that have not been compared head to head, which could impact the precision of pooled estimates in a meta-analysis. Therefore, we evaluated the efficacy and safety of the different lock solutions for CRBSI through a network meta-analysis. METHODS AND ANALYSIS:The primary outcome of this network meta-analysis is the CRBSI. The secondary outcomes are exit-site infection and catheter-related thrombosis. We will search the PubMed, Embase, Web of Science and the Cochrane Library databases for recent relevant meta-analysis and their reference lists to include randomised controlled trials (RCTs) that compared lock solutions for CRBSI prevention. Two individuals will independently extract data from each included RCT according to a predesigned Excel spreadsheet and will assess the methodological quality using the Cochrane risk of bias tool. We will analyse the data using WinBUGS (V.1.4.3) and Stata (V.15.0). We will also estimate the pooled direct and indirect effects for all lock solutions using the network meta-analysis. ETHICS AND DISSEMINATION:As the present meta-analysis is performed based on previous published studies, no ethical approval and patient safety considerations are required. This study commenced on 18 January 2019, and its expected completion date is 1 December 2019. We will disseminate the results of our network meta-analysis through an international peer-reviewed journal. PROSPERO REGISTRATION NUMBER:CRD42019121089.
Project description:Although there are many commercially available statistical software packages, only a few implement a competing risk analysis or a proportional hazards regression model with time-dependent covariates, which are necessary in studies on hematopoietic SCT. In addition, most packages are not clinician friendly, as they require that commands be written based on statistical languages. This report describes the statistical software 'EZR' (Easy R), which is based on R and R commander. EZR enables the application of statistical functions that are frequently used in clinical studies, such as survival analyses, including competing risk analyses and the use of time-dependent covariates, receiver operating characteristics analyses, meta-analyses, sample size calculation and so on, by point-and-click access. EZR is freely available on our website (http://www.jichi.ac.jp/saitama-sct/SaitamaHP.files/statmed.html) and runs on both Windows (Microsoft Corporation, USA) and Mac OS X (Apple, USA). This report provides instructions for the installation and operation of EZR.
Project description:BACKGROUND:Liver cirrhosis is characterized by fibrosis and nodule formation in the liver, due to a chronic injury, and subsequent alteration of the normal architecture of the liver. Even though there is a huge effort to elucidate the possible etiologic factors of liver cirrhosis, a significant number of cases are cryptogenic, especially in Sub Saharan Africa, where there is a high burden of aflatoxin exposure. Aflatoxins are known to cause hepatocellular carcinoma, which share similar etiologic factors with liver cirrhosis. This study aimed to assess the association between aflatoxin exposure and the risk of liver cirrhosis. METHODS:Relevant studies were identified through systematic searches conducted in Ovid MEDLINE, PubMed and Google Scholar. Also, by searching the references of retrieved articles. The abstracts and full text were screened for eligibility and the risk of bias was assessed for each study using Joanna Briggs Institute (JBI) critical appraisal checklist for observational studies. The extracted data from included studies using Microsoft Excel were exported to Stata software version 15.0 for analyses. The overall pooled estimation of outcomes was calculated using a random-effects model of DerSimonian-Laird method at a 95% confidence level. The heterogeneity of studies was determined using I2 statistics. The presence of publication bias between studies was evaluated using the Begg's and Egger's tests and funnel plot. The protocol of this systematic review and meta-analysis was registered in the Prospero database with reference number ID: CRD42019148481. RESULTS:A total of 5 studies published between the years 2005 and 2018 that met the pre-defined inclusion and exclusion criteria were included. The meta-analysis showed that a significant increase in the risk of liver cirrhosis is associated with aflatoxin exposure (unadjusted pooled odds ratio (OR)?=?3.35, 95% CI: 2.74-4.10, p?= 0.000; I2 =?88.3%, p?= 0.000; adjusted OR?=?2.5, 95% CI: 1.84-3.39, p?= 0.000; I2?=?0%, p?= 0.429). CONCLUSIONS:The present meta-analysis suggests that aflatoxin exposure is associated with a higher risk of liver cirrhosis.
Project description:BACKGROUND: Systematic reviews and meta-analyses of test accuracy studies are increasingly being recognised as central in guiding clinical practice. However, there is currently no dedicated and comprehensive software for meta-analysis of diagnostic data. In this article, we present Meta-DiSc, a Windows-based, user-friendly, freely available (for academic use) software that we have developed, piloted, and validated to perform diagnostic meta-analysis. RESULTS: Meta-DiSc a) allows exploration of heterogeneity, with a variety of statistics including chi-square, I-squared and Spearman correlation tests, b) implements meta-regression techniques to explore the relationships between study characteristics and accuracy estimates, c) performs statistical pooling of sensitivities, specificities, likelihood ratios and diagnostic odds ratios using fixed and random effects models, both overall and in subgroups and d) produces high quality figures, including forest plots and summary receiver operating characteristic curves that can be exported for use in manuscripts for publication. All computational algorithms have been validated through comparison with different statistical tools and published meta-analyses. Meta-DiSc has a Graphical User Interface with roll-down menus, dialog boxes, and online help facilities. CONCLUSION: Meta-DiSc is a comprehensive and dedicated test accuracy meta-analysis software. It has already been used and cited in several meta-analyses published in high-ranking journals. The software is publicly available at http://www.hrc.es/investigacion/metadisc_en.htm.
Project description:BACKGROUND AND AIMS:Infectious diseases (IDs) are major causes of morbidity and mortality and their surveillance is critical. In 2002, we implemented a simple and versatile homemade tool, named EPIMIC, for the real-time systematic automated surveillance of IDs at Marseille university hospitals, based on the data from our clinical microbiology laboratory, including clinical samples, tests and diagnoses. METHODS:This tool was specifically designed to detect abnormal events as IDs are rarely predicted and modeled. EPIMIC operates using Microsoft Excel software and requires no particular computer skills or resources. An abnormal event corresponds to an increase above, or a decrease below threshold values calculated based on the mean of historical data plus or minus 2 standard deviations, respectively. RESULTS:Between November 2002 and October 2013 (11 years), 293 items were surveyed weekly, including 38 clinical samples, 86 pathogens, 79 diagnosis tests, and 39 antibacterial resistance patterns. The mean duration of surveillance was 7.6 years (range, 1 month-10.9 years). A total of 108,427 Microsoft Excel file cells were filled with counts of clinical samples, and 110,017 cells were filled with counts of diagnoses. A total of 1,390,689 samples were analyzed. Among them, 172,180 were found to be positive for a pathogen. EPIMIC generated a mean number of 0.5 alert/week on abnormal events. CONCLUSIONS:EPIMIC proved to be efficient for real-time automated laboratory-based surveillance and alerting at our university hospital clinical microbiology laboratory-scale. It is freely downloadable from the following URL: http://www.mediterranee-infection.com/article.php?larub=157&titre=bulletin-epidemiologique (last accessed: 20/11/2015).