392,037 papers found

Multiple genetic strategies are available to help improve understanding of diabetic nephropathy. This chapter provides detailed methodology for a single-nucleotide polymorphism association study and meta-analysis, using a protocol suitable for targeted SNP or genome-wide association studies, to identify genetic risk fa…

I discuss the lack of precision in the term 'clinical reasoning' and its relationship to evidence-based medicine and critical thinking. I examine critical thinking skills, their underemphasis in medical education and successful attempts to remediate them. Evidence-based medicine (and evidence-based psychiatry) offer mu…

It is shown that fixed-effect meta-analyses of naïve treatment estimates from sequentially run trials with the possibility of stopping for efficacy based on a single interim look are unbiassed (or at the very least consistent, depending on the point of view) provided that the trials are weighted by information pro…

OBJECTIVES: The validity of network meta-analysis (NMA) relies on 3 assumptions, namely, homogeneity, consistency, and transitivity. A recent article argued that all 3 assumptions can be reduced to the exchangeability assumption. However, it is not entirely clear what is exchangeable in NMA and how the exchangeability…

Genome-wide association studies (GWAS) have significantly enhanced our understanding of the genetic basis of complex diseases. Despite the technological advancements, gaps in our understanding remain, partly due to small effect sizes and inadequate coverage of genetic variation. Multiancestry GWAS meta-analysis (MAGMA)…

In Woldeamanuel and Oliveira (2022)'s article about the efficacy of exercise in the treatment of migraine, the ranking of the efficacy of strength training (mean difference, - 3.55), aerobic exercise (mean difference, - 2.18 to - 3.13), topiramate (mean difference, - 0.98), and amitriptyline…

In 2020, 6 meta-analyses comparing arthroscopic hip surgery to physical therapy were published. All included the same 3 randomized controlled trials, and none used methods suitable for the analysis of fewer than 5 studies. When there are fewer than 5 studies and heterogeneity, a random-effects model with the Hartung-Kn…

OBJECTIVE: Dose-response meta-analysis (DRMA) is widely applied to investigate the dose-specific relationship between independent and dependent variables. Such methods have been in use for over 30 years and are increasingly employed in healthcare and clinical decision-making. In this article, we give an overview of the…

In conventional frequentist power analysis, one often uses an effect size estimate, treats it as if it were the true value, and ignores uncertainty in the effect size estimate for the analysis. The resulting sample sizes can vary dramatically depending on the chosen effect size value. To resolve the problem, we propose…

A widely used method in classic random-effects meta-analysis is the DerSimonian-Laird method. An alternative meta-analytical approach is the Hartung-Knapp method. This article reports results of an empirical comparison and a simulation study of these two methods and presents corresponding analytical results. For t…

Recently, multiple imputation has been proposed as a tool for individual patient data meta-analysis with sporadically missing observations, and it has been suggested that within-study imputation is usually preferable. However, such within study imputation cannot handle variables that are completely missing within studi…

Many meta-analyses report using 'Cochran's Q test' to assess heterogeneity of effect-size estimates from the individual studies. Some authors cite work by W. G. Cochran, without realizing that Cochran deliberately did not use Q itself to test for heterogeneity. Further, when heterogeneity is absent, the actual null dis…

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them i…

To investigate intervention effects on rare events, meta-analysis techniques are commonly applied in order to assess the accumulated evidence. When it comes to adverse effects in clinical trials, these are often most adequately handled using survival methods. A common-effect model that is able to process data in common…

Prognostic models provide an avenue to predict the risk of individual patients and support shared-decision making. Many prognostic models are published annually, and systematic reviews provide an avenue to collate the existing evidence behind prognostic models to determine whether a model demonstrates adequate predicti…

Recent years have witnessed calls for increased rigour and credibility in the cognitive and behavioural sciences, including psychophysiology. Many procedures exist to increase rigour, and among the most important is the need to increase statistical power. Achieving sufficient statistical power, however, is a considerab…

A Cochrane review of universal late-pregnancy ultrasound has been highly influential in guiding UK practice, concluding that it does not improve outcome. However, the meta-analysis combines trials that used diverse definitions of screen positive, were designed in the absence of high-quality data on diagnostic effective…

In this manuscript we use realistic data to conduct a network meta-analysis using a Bayesian approach to analysis. The purpose of this manuscript is to explain, in lay terms, how to interpret the output of such an analysis. Many readers are familiar with the forest plot as an approach to presenting the results of a pai…

Meta-analysis is a leading methodology used in systematic secondary researches. Review Manager software is the main tool used by leading world expert groups for meta-analysis. The authors analyzed the features of meta-analyzes evaluating the results of surgeries. It is shown that the majority of baseline clinical param…

Standard methods for fixed effects meta-analysis assume that standard errors for study-specific estimates are known, not estimated. While the impact of this simplifying assumption has been shown in a few special cases, its general impact is not well understood, nor are general-purpose tools available for inference unde…