## Order courses: Course detail

## Systematic Reviews in Intervention Research

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 |
List the key steps of a systematic review Critically appraise systematic reviews Develop eligibility criteria for selecting studies 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.
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 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 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 Preffered: |

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 | € 980,- |

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. |