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.
| Time | Speaker | Affiliation | Title |
|---|---|---|---|
| 09:00 - 10:30 | Lotty Hooft & Anneke Damen | Cochrane Netherlands / UMC Utrecht, Julius Center | Conducting systematic reviews of prognosis studies |
| 09:00 - 10:30 | Maarten van Smeden, Anne de Hond, Wouter van Amsterdam & Ilse Kant | UMC Utrecht, Julius Center | AI-based prediction models in healthcare: from development to implementation |
| 09:00 - 10:30 | Mira Zuidgeest & Joost van Rosmalen | UMC Utrecht, Julius Center | Innovation in Clinical trials - Why should we innovate and how? |
| 09:00 - 10:30 | Renée Verdiesen & Oscar Franco | Thoughtful Stories & UMC Utrecht, Julius Center | Science communication within and beyond academia |
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.
Maarten van Smeden, Anne de Hond, Wouter van Amsterdam & Ilse Kant
UMC Utrecht, Julius Center for Health Sciences and Primary Care
Artificial intelligence (AI) holds great promise for the healthcare sector. It could assist us with early disease detection, personalized treatment recommendations, and efficient resource allocation. Despite its potential, AI-based prediction faces several challenges. Data quality and ethical dilemmas pose significant hurdles, and concerns have been raised about our limited understanding of how this technology affects clinical decision making. In this masterclass, we discuss the intricacies of AI prediction models, their potential, and the critical considerations for succesful implementaiton. We explore successful case studies, highlighting the promises and complexities of developing AI for real-world application. Specifically, the masterclass dives into four key topics:
• The promises of AI for healthcare;
• The prerequisites: validation, explainability and fairness;
• The pitfalls: self-fulfilling prophecy;
• The impact: valuable AI implementation and adoption in healthcare
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.
Renée Verdiesen & Oscar Franco
Thoughtful Stories & UMC Utrecht, Julius Center for Health Sciences and Primary Care
Most – if not all – epidemiologists strive to make the world a better place; be it through enhanced disease prevention, improving diagnosis or prognosis, or new and better treatments. In order to actually move from research to implementation, it is essential to convey your findings successfully to many different people (e.g. fellow researchers, clinicians, patients, policy officers and the general public). In this masterclass, we will provide you with guidance in how to get your (research) message across in different settings within and beyond academia. Specifically, we will discuss how to shape your story in a way that fits you and your audience, the use of social media and media interaction.