Every year we teach at the Epidemiology and Population Health Summer Institute at Columbia University the following Courses:

Introduction to systematic reviews

Systematic reviews and meta-analyses are increasingly used for evidence-based clinical and public health practice. Health-care professionals need to understand and critique this research design. This course will present an overview of the methodology specifically related to the conduct and interpretation of systematic reviews.

It will cover the strengths, potential bias and limitations of systematic review methods, and provide step-by-step guidance on how to actually perform and report a systematic review.

Specific details regarding appropriate methods to ensure that results of the systematic review are appropriate for future meta-analysis will also be addressed.

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Meta-analysis of observational data

Meta-analyses of data arising from systematic reviews are increasingly used for evidence-based clinical and public health practice. Health-care professionals need to understand and critique this research design.
This course will present a detailed description of the meta-analysis process, discuss the strengths, potential bias and limitations of this design, and provide step-by-step guidance on how to actually perform and report a meta-analysis.
We will focus on issues relevant to meta-analyses of observational studies although the overall methodology is highly applicable to meta-analyses of randomized trials as well. In particular, there will be discussion about issues such as adjustment for confounders, aggregating data from different observational designs, assessing small-study effects.

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Network meta-analysis

Traditional meta-analytical methods commonly used for synthesizing evidence from clinical trials are limited in comparing two interventions at a time. However, for any given condition there is usually a plethora of alternative treatment options. This situation has motivated the development of network meta-analysis which is an extension of conventional meta-analysis that allows the simultaneous synthesis of data from networks of trials. By combining direct and indirect information, network meta-analysis can inform every possible treatment comparison, even those for which no head-to-head trials exist.
This course will focus on the role of network meta-analyses in comparative effectiveness research. We will examine the statistical methods and methodological aspects involved, the assumptions underlying the method and the potential sources of bias that can invalidate the results. Finally, we will discuss methods for reporting and critically appraising the results from network meta-analyses.

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