ECEBM, a GESI member

We are pleased to announce that the Egyptian Center for Evidence Based Medicine (ECEBM), is now a member of the Global Evidence Synthesis Initiative (GESI) Network. Top-tier evidence-synthesis centers from LMIC form the GESI Network. The Network enhances the collaboration between these centers and forms a bridge to share knowledge and experience. The GESI Consortium … Continue reading ECEBM, a GESI member

Systematic Reviews and Meta-analysis, 17

This workshop takes a step-by-step approach to the practical tasks of conducting and reporting a new Systematic Review to answer a question about the effects of an intervention. This course will focus on the practicalities rather than the theory. Venue: Holiday Inn City stars, Cairo, Egypt. At Aswan Meeting Hall. We delivered the workshop on two dates Dates: 18 … Continue reading Systematic Reviews and Meta-analysis, 17

Multiple treatments comparisons

A special method of meta-analysis known as multiple treatments meta-analysis (MTM) is suited to the practical issues addressed by overviews of reviews. However, MTM (also known as ‘network meta-analysis’, or ‘multiple treatments comparisons’ (‘MTC’) meta-analysis) relies on a strong assumption that studies of different comparisons are similar in all ways other than the interventions being compared.

Evidence Synthesis, Dec 2015

Title: Evidence Synthesis: A Systematic Approach to Literature Review  Date: 3-4 December 2015 Venue: The Training & Education Enhancement Center, Ain Shams University Hospitals Topics include: Define the research question to inform the scope of the review Plan the methods Setting eligibility criteria for including studies in the review Selecting outcomes to be addressed for studies included in the review … Continue reading Evidence Synthesis, Dec 2015

Key Message: How to reduce the risk of selection bias in RCTs

Probably the simplest and most effective method to prevent selection bias in randomized trials is simple randomization. Simple randomization works by assigning each patient to one of the treatment groups with a 50% probability; this probability is the same for every patient, regardless of previous allocations. For example, consider a trial where 40 of the first … Continue reading Key Message: How to reduce the risk of selection bias in RCTs