WEON 2024 > Programme > Masterclasses

Masterclasses

Different masterclasses are organised on Thursday May 30th, 2024. As the masterclasses overlap in time, you are only able to attend one of them. Attending a masterclass is included in the registration fee.

 

TimeSpeakerAffiliationTitle
09:00 - 10:30Lotty Hooft & Anneke DamenCochrane Netherlands / UMC Utrecht, Julius CenterConducting systematic reviews of prognosis studies
09:00 - 10:30Maarten van SmedenUMC Utrecht, Julius CenterAI-based prediction models in healthcare: from development to implementation
09:00 - 10:30Mira ZuidgeestUMC Utrecht, Julius CenterInnovative Trial Methodology
09:00 - 10:30Oscar FrancoUMC Utrecht, Julius CenterCommunicating science and media interaction: from theory to experience

 

Conducting systematic reviews of prognosis studies

Lotty Hooft & Anneke Damen

Cochrane Netherlands / UMC Utrecht, Julius Center for Health Sciences and Primary Care

Prognosis is a description or quantification of the probable course of individuals with(in) a certain health condition over time, and is a crucial part of health care decision making. Like research on the effectiveness of interventions and the accuracy of diagnostic tests, summarizing evidence on prognosis requires systematic and transparent synthesis. Although basic systematic review principles are similar, there are several opportunities and challenges unique to reviews of prognostic studies.

In this masterclass, we will introduce participants to systematic reviews of prognosis studies. We will address various types of prognosis questions (including studies on overall prognosis, prognostic factors, and prognostic models). We then introduce the required approaches and methods for conducting systematic and meta-analysis of prognosis studies including:

1. Formulating the review question of a prognosis review using the PICOTS format
2. Searching and selection of prognosis articles
3. The CHARMS checklist for data extraction
4. Risk of bias assessment with QUIPS, for prognostic factor studies, and PROBAST, for prediction modelling studies
5. Statistical methods for meta-analysis of prognosis studies
6. GRADE, a tool used to assess the quality of evidence and strength of the recommendations that emerge from a systematic review of prognosis studies.

 

AI-based prediction models in healthcare: from development to implementation

Maarten van Smeden

UMC Utrecht, Julius Center for Health Sciences and Primary Care

 

Innovative Trial Methodology

Mira Zuidgeest

UMC Utrecht, Julius Center for Health Sciences and Primary Care

 

Communicating science and media interaction: from theory to experience

Oscar Franco

UMC Utrecht, Julius Center for Health Sciences and Primary Care