382,895 papers found

INTRODUCTION: Gliomas, the most commonly diagnosed primary brain tumours, are associated with varied survivals based, in part, on their histological subtype. Therefore, accurate pretreatment tumour grading is essential for patient care and clinical trial design. METHODS AND ANALYSIS: We will perform an individual-leve…

Network meta-analysis (NMA) is gaining popularity for comparing multiple treatments in a single analysis. Generalized linear mixed models provide a unifying framework for NMA, allow us to analyze datasets with dichotomous, continuous or count endpoints, and take into account multiarm trials, potential heterogeneity bet…

Network meta-analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time-to-event outcomes. Such outcomes are usually analysed using Cox proporti…

BACKGROUND: Many reviews aim to compare numerous treatments and report results stratified by subgroups (eg, by disease severity). In such cases, a network meta-analysis model including treatment by covariate interactions can estimate the relative effects of all treatment pairings for each subgroup of patients. Two key…

BACKGROUND: In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatme…

DNA aneuploidy is an imbalance of chromosomal DNA content that has been highlighted as a predictor of biological behavior and risk of malignant transformation. To date, DNA aneuploidy in oral potentially malignant diseases (OPMD) has been shown to correlate strongly with severe dysplasia and high-risk lesions that appe…

INTRODUCTION: There are many proven treatments (psychotherapy, pharmacotherapy or their combination) for the treatment of depression. Although there is growing evidence for the effectiveness of combination treatment (psychotherapy + pharmacotherapy) over pharmacotherapy alone, psychotherapy alone or psychotherapy plus…

Network meta-analysis enables comprehensive synthesis of evidence concerning multiple treatments and their simultaneous comparisons based on both direct and indirect evidence. A fundamental pre-requisite of network meta-analysis is the consistency of evidence that is obtained from different sources, particularly whethe…

Meta-analysis using individual participant data (IPD) obtains and synthesises the raw, participant-level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta-analysis, especially as it avoids reliance on published results and…

OBJECTIVES: There is no consensus on whether studies with no observed events in the treatment and control arms, the so-called both-armed zero-event studies, should be included in a meta-analysis of randomised controlled trials (RCTs). Current analytic approaches handled them differently depending on the choice of effec…

Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association between the number of true positives and true negatives, because studies that adopt less stringent criterion for declaring a test positive invo…

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. Consequen…

A variable is 'systematically missing' if it is missing for all individuals within particular studies in an individual participant data meta-analysis. When a systematically missing variable is a potential confounder in observational epidemiology, standard methods either fail to adjust the exposure-disease association f…

INTRODUCTION: Media and digital technologies shape adolescent development across interconnected online and offline contexts, offering opportunities for learning and connection while also exposing young people to risks that can affect wellbeing. Wellbeing-focused media literacy interventions aim to support young people…

Food-safety occurrence databases are increasingly important for surveillance, evidence appraisal, and quantitative risk assessment, yet their routine analytical use remains constrained by the need for database literacy and statistical programming. Building on the curated and harmonized Pathogens-in-Foods (PIF) database…

The I-squared index was proposed in 2002 as a measure to help understand the consistency of study results in a meta-analysis. It was developed to overcome some of the limitations of existing measures, principally the chi-squared test for heterogeneity and the between-study variance as estimated in a random-effects meta…

Publication bias is a major threat to the validity of a meta-analysis, resulting in overestimated effect sizes. We propose a generalization and improvement of the publication bias method p-uniform called p-uniform*. P-uniform* improves upon p-uniform in three ways, as it (i) entails a more efficient estimator, (ii) eli…

Graphical displays are often utilised for high-quality reporting of meta-analyses. Previous work has presented augmentations to funnel plots that assess the impact that an additional trial would have on an existing meta-analysis. However, decision-makers, such as the National Institute for Health and Care Excellence in…

The feasibility of network meta-analysis depends on several factors, one of which is the validity of the transitivity assumption that posits no systematic differences in the distribution of effect modifiers across treatment comparisons within a connected network. However, evaluating transitivity is complex for relying…

BACKGROUND: Traditional statistical methods assume normally distributed continuous variables, making them unsuitable for analysis of prevalence proportions. To address this problem, two commonly utilized variance-stabilizing transformations (logit and Freeman-Tukey) are empirically evaluated in this study to provide cl…