The SMART Safety: An empirical dataset for evidence synthesis of adverse events.

Evidence synthesis serves an important role to promote informed decision-making in healthcare practice. A key issue of evidence synthesis is the approach to deal with rare adverse events and the methods to address bias of harm effects. Empirical data is essential to help methodologists and statisticians to solve the issues in evidence synthesis of adverse events.

Measuring the impact of zero-cases studies in evidence synthesis practice using the harms index and benefits index (Hi-Bi).

Objectives: In evidence synthesis practice, dealing with studies with no cases in both arms has been a tough problem, for which there is no consensus in the research community. In this study, we propose a method to measure the potential impact of studies with no cases for meta-analysis results which we define as harms index (Hi) and benefits index (Bi) as an alternative solution for deciding how to deal with such studies.

Methods: Hi and Bi are defined by the minimal number of cases added to the treatment arm (Hi) or control arm (Bi) of studies with no cases in a meta-analysis that lead to a change of the direction of the estimates or its statistical significance.

Prevalence and Incidence of Dry Eye and Meibomian Gland Dysfunction in the United States: A Systematic Review and Meta-analysis.

Importance: Dry eye is a common clinical manifestation, a leading cause of eye clinic visits, and a significant societal and personal economic burden in the United States. Meibomian gland dysfunction (MGD) is a major cause of evaporative dry eye.

Objective: To conduct a systematic review and meta-analysis to obtain updated estimates of the prevalence and incidence of dry eye and MGD in the United States.

Network meta-analysis of rare events using penalized likelihood regression.

Network meta-analysis (NMA) of rare events has attracted little attention in the literature. Until recently, networks of interventions with rare events were analyzed using the inverse-variance NMA approach. However, when events are rare the normal approximations made by this model can be poor and effect estimates are potentially biased.

Comparing efficacy and safety in catheter ablation strategies for atrial fibrillation: protocol of a network meta-analysis of randomised controlled trials.

Introduction: Atrial fibrillation (AF) is the most common sustained arrhythmia. Catheter ablation (CA) of AF is an increasingly offered therapeutic approach, primary to relieve AF-related symptoms. Despite the development of new ablation approaches, there is no consensus regarding the most efficient ablation strategy.

A Markov chain approach for ranking treatments in network meta-analysis.

When interpreting the relative effects from a network meta-analysis (NMA), researchers are usually aware of the potential limitations that may render the results for some comparisons less useful or meaningless. In the presence of sufficient and appropriate data, some of these limitations (eg, risk of bias, small-study effects, publication bias) can be taken into account in the statistical analysis. Very often, though, the necessary data for applying these methods are missing and data limitations cannot be formally integrated into ranking.