Meta-MUMS DTA: Implementation, validation, and application of diagnostic test accuracy software for meta-analysis in radiology

• Main Authors: Massoud Sokouti (Author), Ramin Sadeghi (Author), Saeid Pashazadeh (Author), Saeid Eslami (Author), Mohsen Sokouti (Author), Morteza Ghojazadeh (Author), Babak Sokouti (Author)
• Format: Book
• Published: Elsevier, 2021-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2213-3984; 10.1016/j.cegh.2020.10.004
• Keywords: Diagnostic meta-analysis; Meta-MUMS DTA; Software; Accuracy test; Radiology; Public aspects of medicine; RA1-1270
• Source: Clinical Epidemiology and Global Health, Vol 9, Iss , Pp 310-325 (2021)

Purpose: Generally, guiding clinical practice concentrates on the statistical techniques implemented for performing the diagnostic meta-analysis and test accuracy studies in a specific field of research. This study aims to implement a comprehensive diagnostic meta-analysis tool, which is user-friendly, free, and simple, and can be useful for diagnostic and bivariate model analysis purposes. Methods: The Meta-MUMS DTA tool for meta-analysis developed in Matlab R2013a for the Microsoft Windows operating systems (32-bit and 64-bit). Meta-DiSc, Open-MetaAnalyst, Stata (Deeks' test) were the tools used for comparison purposes. Results: The features include determination of heterogeneity and computations of chi-square (Q, df, and p-value), I2, Γ2, and Spearman correlation tests, subgroup analysis, meta-regression techniques to explore the relationships of study characteristics and accuracy estimates and performing statistical pooling of sensitivities, specificities, likelihood ratio, and diagnostic odds ratios on fixed- and random-effects models as well as providing figures for forest plots with high quality. The Egger's regression test (along with its smooth version SVE and SVT), Deeks' regression test with funnel plots, and trim and fill were the tools for detecting publication bias. Bivariate model analysis of sensitivity and specificity accuracy is also available in this software. Publication bias and bivariate model analysis are super-advantageous of the proposed software. Moreover, a worked example to evaluate the diagnostic accuracy of mammography and magnetic resonance imaging in breast cancer is proposed. Conclusion: The Meta-MUMS DTA tool shows its advantages for upcoming diagnostic meta-analysis studies, especially in radiology science and hopefully may become a platform for teaching purposes.