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Systematic Reviews in Intervention Research

Content partner
Utrecht University
Course coordinator
Drs. P. Heus
Description

 

Course
Systematic Reviews in Intervention Research
Date
 3 - 7 February 2025
Course co-ordinator
Pauline Heus
Course description
Meta-Analysis is the statistical approach to synthesis of the results from a series of studies. During this course we will present and discuss the rational and use of meta-analysis. We will discuss the strengths and limitations, and provide step-by-step guidance on how to perform a meta-analysis based on examples that either has provoked discussion on their logic and methods, or that have challenged conventional beliefs in medicine and biomedical sciences.
Logic and developments on particular approaches (e.g. model selection, individual patient data meta-analyses), and controversies in meta-analysis will be discussed during interactive tutorials (e.g. dealing with heterogeneity and when to refrain from meta-analysis).
Participants will learn how to conduct a meta-analysis. They will get hands-on experience on different aspects of the design and conduct of meta-analysis, including computer practicals using Excel, Comprehensive Meta-Analysis (CMA), STATA and MIX. By the end of the course, participants should be able to conduct a meta-analysis.
Participants gain access to the online materials the week before the course. Participants are encouraged to bring their laptop.
Course objectives

Systematic reviews in general
Explain the rationale for performing a systematic review
List the key steps of a systematic review
Critically appraise systematic reviews

 Defining a study question and selection criteria
Formulate a well-defined review question addressing a therapeutic dilemma
Develop eligibility criteria for selecting studies

 Identifying studies
Understand the design of a comprehensive and efficient search strategy to identify relevant studies of interventions in electronic bibliographic databases and from other sources.

 Risk of Bias
Describe various shortcomings in design, conduct and analysis which may bias the results of randomised trials and non-randomised studies of interventions
Assess risk of bias in randomised controlled trials and report the results of the assessment
Understand how risk-of-bias assessment of non-randomised studies of interventions differs in comparison to that of randomised trial.
Understand how risk-of-bias assessments can be incorporated into a systematic review.

Data-extraction
Define what descriptive and numerical data should be extracted to inform the end-users of the review

 Meta-analysis
Understand the steps of conducting a meta-analysis
Recognise the elements of a forest plot and interpret the results
Select and calculate measures of treatment effect for dichotomous (risk difference, risk ratio, odds ratio) and continuous outcomes (mean difference and standardised mean difference)
Express effect measures for ordinal data, counts and rates, and time to event data
Select appropriate statistical methods for meta-analysis of dichotomous and continuous data
Explain the difference between fixed effect and random effects approach and their assumptions
Use statistical software to set up a meta-analysis and create forest plotApply the Generic Inverse Variance (GIV) method for meta-analysis

 Heterogeneity
Understand the meaning of heterogeneity
Identify differences between clinical, methodological and statistical heterogeneit
Interpret the different measures of heterogeneity
Describe the strategies for handling heterogeneity
Describe the pitfalls of subgroup analyses and meta-regressioN
Interpret the results of a meta-regression model

 Summarising and interpreting results
Interpret the findings of a meta-analysis (including direction of effect, effect size, and precision, both for fixed effect & random-effects approach)
List and explain the different types of reporting bias
Assess the certainty of a body of evidence (using the GRADE approach) and construct Summary of Findings Tables
Re-express relative effects in more clinically meaningful ways
Make judgements surrounding clinical and statistical significance

Prerequisite knowledge

Obligatory
Introduction to Epidemiology
Introduction to Statistics

Preffered:
Clinical Epidemiology

Course days
This is a 1 week course: 5 morning sessions and 4 afternoon sessions + one exam (in the afternoon). Teaching contact during plenaries and in groups will typically take from 10 am to 5 pm.
Course format
This course includes plenary lectures, interactive tutorials, small group assignments, computer practicals, discussion on the assignment, (group) presentations and self study
Assessment
80% attendance and (Open book) Exam.
During the course, home work will be assigned. These home work assignments take approximately 2 hours each day.
Number of participants
60
Course fee
€ 1010,00
Prerequisite for participation is sufficiënt capacity in terms of teachers and locations.

This course can also be followed online. Look at the website http://elevatehealth.eu/courses for more information and costs.


 


Maximum participants
40
Fee (€)
980.00

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