RANDOM EFFECTS MODELS IN A META-ANALYSIS OF THE ACCURACY OF DIAGNOSTIC TESTS WITHIN A GOLD STANDARD IN THE PRESENCE OF MISSING DATA

In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian hierarchical model, both of which account for the heterogeneity across studies through study-specific random effects. The methods can be used to estimate the accuracy of two imperfect diagnostic tests in other meta-analyses when the prevalence of disease, the sensitivities and/or the specificities of diagnostic tests are heterogeneous among studies. Furthermore, simulation studies have demonstrated the importance of carefully selecting appropriate random effects on the estimation of diagnostic accuracy measurements in this scenario

Association Between Cellphone Use While Driving Legislation and Self-reported Behaviour Among Adult Drivers in USA: A Cross-sectional Study

Objectives Cellphone use behaviours can vary demographically in the USA. This study examined whether legislation restricting cellphone use while driving was associated with lower self-reported hand-held cellphone conversations or texting behaviours among adult drivers of different ages (19–24, 25–39, 40–59,≥60 years), sex, race/ethnicity (white non-Hispanic, black non-Hispanic, Hispanic, Other) or rurality (urban, rural). Design Cross-sectional study. Setting USA. Participants Individuals ≥19 years of age who indicated they were a current driver and participated in the 2011– 2014 Traffic Safety Culture Index Surveys (n=9706). Primary outcome The exposure was the presence of a hand-held calling or texting ban applicable to all drivers (ie, universal) at time of survey. Modified Poisson regression with robust SE was used to estimate the risk of engaging in these self-reported behaviours. Results In fully adjusted models, universal texting bans were not associated with lower texting behaviours (adjusted risk ratio [aRR]=0.92; 95% CI 0.84, 1.01). In stratified, fully adjusted models, men and those of other racial/ethnic origin were 13% and 33% less likely, respectively (aRR=0.87; 95%CI 0.77, 0.98; aRR=0.67; 95%CI 0.46, 0.97), to engage in texting behaviours if a universal texting ban was effective in their state. Conversely, universal hand-held calling bans were associated with lower self-reported hand-held cellphone conversations across every sub-group. In fully adjusted models, the presence of a hand-held calling ban was associated with 40% lower (aRR=0.60, 95%CI 0.54, 0.67) self-reported hand-held cellphone conversations while driving. Conclusions Universal hand-held calling bans were associated with lower self-reported cellphone conversations for adult drivers. More interventional work targeting adult drivers may be needed to reduce texting while driving

mmeta: An R Package for Multivariate Meta-Analysis

This paper describes the core features of the R package mmeta, which implements the exact posterior inference of odds ratio, relative risk, and risk difference given either a single 2 x 2 table or multiple 2 x 2 tables when the risks within the same study are independent or correlated

Knowledge mapping and global trends in the field of low-intensity pulsed ultrasound and endocrine and metabolic diseases: a bibliometric and visual analysis from 2012 to 2022

BackgroundLow-intensity pulsed ultrasound (LIPUS) is a highly promising therapeutic method that has been widely used in rehabilitation, orthopedics, dentistry, urology, gynecology, and other multidisciplinary disease diagnoses and treatments. It has attracted extensive attention worldwide. However, there is currently a lack of comprehensive and systematic research on the current status and future development direction of the LIPUS field. Therefore, this study comprehensively analyzed LIPUS-related reports from the past decade using bibliometrics methods, and further conducted research specifically focusing on its application in endocrine and metabolic diseases.MethodsWe downloaded LIPUS literature from 2012 to 2022 reported in the Web of Science Core Collection Science Citation Index-Expanded and Social Sciences Citation Index, and used bibliometric analysis software such as VOSviewer and CiteSpace to execute the analysis and visualize the results.ResultsWe searched for 655 English articles published on LIPUS from 2012 to 2022. China had the highest number of published articles and collaborations between China and the United States were the closest in this field. Chongqing Medical University was the institution with the highest output, and ULTRASOUND IN MEDICINE AND BIOLOGY was the journal with the most related publications. In recent years, research on the molecular mechanisms of LIPUS has continued to deepen, and its clinical applications have also continued to expand. The application of LIPUS in major diseases such as oxidative stress, regeneration mechanism, and cancer is considered to be a future research direction, especially in the field of endocrinology and metabolism, where it has broad application value.ConclusionGlobal research on LIPUS is expected to continue to increase, and future research will focus on its mechanisms of action and clinical applications. This study comprehensively summarizes the current development status and global trends in the field of LIPUS, and its research progress in the field of endocrine and metabolic diseases, providing valuable reference for future research in this field

A hybrid Bayesian hierarchical model combining cohort and case–control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented