scholarly journals Diagnostic test accuracy: application and practice using R software

2019 ◽  
Vol 41 ◽  
pp. e2019007 ◽  
Author(s):  
Sung Ryul Shim ◽  
Seong-Jang Kim ◽  
Jonghoo Lee
Keyword(s):  
Diagnostic Test ◽  
Roc Curve ◽  
Univariate Analysis ◽  
Diagnostic Test Accuracy ◽  
Effect Sizes ◽  
Bivariate Analysis ◽  
Forest Plot ◽  
Test Accuracy ◽  
R Software ◽  
Moderator Effect

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

scholarly journals Metadta: A Stata Command for Meta-analysis and Meta-regression of Diagnostic Test Accuracy Data – A Tutorial.

2021 ◽  
Author(s):  
Victoria Nyawira Nyaga ◽  
Marc Arbyn
Keyword(s):  
Bladder Cancer ◽  
Diagnostic Test ◽  
Sensitivity And Specificity ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Diagnostic Test Accuracy ◽  
Forest Plot ◽  
Test Accuracy ◽  
Statistical Procedures ◽  
Meta Regression

Abstract BackgroundAlthough statistical procedures for pooling of several epidemiological metrics are generally available in statistical packages, those for meta-analysis of diagnostic test accuracy studies including options for multivariate regression are lacking. Fitting regression models and the processing of the estimates often entails lengthy and tedious calculations. Therefore, packaging appropriate statistical procedures in a robust and user-friendly program is of great interest to the scientific community. Methodsmetadta is a statistical program for pooling of diagnostic accuracy test data in Stata. It implements both the bivariate random-effects and fixed-effects model, allows for meta-regression, and presents the results in tables, a forest plot and/or summary receiver operating characteristic (SROC) plot. For a model without covariates, it also quantifies heterogeneity using an I2 statistic that accounts for the mean-variance relationship, and correlation between sensitivity and specificity, a typical characteristic of diagnostic data. To demonstrate metadta, we applied the program on two published meta-analyses on: 1) the sensitivity and specificity of cytology and other markers including telomerase for primary diagnosis of bladder cancer; and 2) the accuracy of human papillomavirus testing on self-collected versus clinician-collected samples to detect cervical precancer.ResultsWithout requiring a continuity correction, metadta generated a pooled sensitivity and specificity of 0.77 [95% CI: 0.70, 0.82] and 0.91 [95% CI: 0.75, 0.97] respectively of telomerase for the diagnosis of primary bladder cancer. metadta allowed to assess the relative accuracy of human Papilloma virus (HPV) testing on self- versus clinician-taken specimens in matched studies taking into account two covariates. Under the condition of using assays based on target-amplification, HPV tests were similarly sensitive to detect cervical pre-cancer, irrespective of clinical setting. ConclusionThe metadta program implements state of art statistical procedures in an attempt to close the gap between methodological statisticians and systematic reviewers. With metadta, we hope to popularize even further, the use of appropriate statistical methods for diagnostic meta-analysis.

scholarly journals Intervention meta-analysis: application and practice using R software

2019 ◽  
Vol 41 ◽  
pp. e2019008 ◽  
Author(s):  
Sung Ryul Shim ◽  
Seong-Jang Kim
Keyword(s):  
Publication Bias ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Forest Plot ◽  
R Software ◽  
Data Synthesis ◽  
Moderator Effect ◽  
Theoretical Concepts ◽  
Analysis Application ◽  
Meta Regression Analysis

The objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.

scholarly journals Aeroallergen sensitisation for detecting asthma in primary care: a diagnostic test accuracy study

2021 ◽  
Author(s):  
Janwillem W.H. Kocks ◽  
Heinze J.H. Andringa ◽  
Ellen van Heijst ◽  
Renaud Louis ◽  
Inigo Ojanguren Arranz ◽  
...  
Keyword(s):  
Primary Care ◽  
Diagnostic Test ◽  
Diagnostic Test Accuracy ◽  
Test Accuracy ◽  
Accuracy Study
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