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 Smeden, Anne de Hond & Wouter van AmsterdamUMC Utrecht, Julius CenterAI-based prediction models in healthcare: from development to implementation
09:00 - 10:30Mira Zuidgeest & Joost van RosmalenUMC Utrecht, Julius CenterInnovation in Clinical trials - Why should we innovate and how?
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, Anne de Hond & Wouter van Amsterdam

UMC Utrecht, Julius Center for Health Sciences and Primary Care

 

Innovation in Clinical trials – Why should we innovate and how?

Mira Zuidgeest & Joost van Rosmalen

UMC Utrecht, Julius Center for Health Sciences and Primary Care

Clinical trials are essential in demonstrating the benefits and risks of new medicines, medical devices, and nonpharmacological interventions. However, many challenges impact the conduct of traditional clinical trials and their ability to generate the evidence required to improve clinical practice, such as the substantial cost and effort required to perform a clinical trial. To overcome these challenges, several trial innovations have been developed and are being tested and implemented, such as pragmatic and decentralised clinical trial approaches, platform approaches with adaptive designs, and statistical methods that leverage information from external controls. Such innovations can make trials more efficient, more inclusive and possibly decrease participation burden. In this masterclass we will present an overview of these trial innovations and their possible benefits and challenges.

Communicating science and media interaction: from theory to experience

Oscar Franco

UMC Utrecht, Julius Center for Health Sciences and Primary Care