PhD defence C.J. (Celine) van de Laar

Below is a brief summary of the dissertation: 

This dissertation investigates the cost-effectiveness of treatments for rheumatic diseases, such as rheumatoid arthritis (RA) and gout, using data from daily clinical practice (Real-World Data). The introductions of effective yet costly medications necessitate robust economic evaluations to support decisions at both clinical and policy levels.
Using health economic models built with data from Dutch registries (e.g., DREAM), the long-term consequences of various treatment strategies were simulated. These studies incorporated quality of life alongside all relevant cost categories. The model-based analyses demonstrate that in early RA, in a treat-to-target (T2T) setting initiating treatment with combination therapy is more cost-effective than a step-up approach. JAK-inhibitors were shown to be cost-effective over using TNF-inhibitors in treating RA patients after failing to reach the target of remission in first-line treatment. Furthermore, for gout, the mathematical models showed that urate-lowering therapy is cost-effective.
Additionally, a pragmatic, randomized trial (PERFECTRA) demonstrates that a treatment strategy with a JAK inhibitor (baricitinib) is superior to a strategy with a TNF inhibitor following the failure of first-line treatment.
Another significant finding is that commonly used quality of life (QoL) questionnaires display limited sensitivity in detecting a deterioration in health status. This has important implications for health technology assessment and (dis)investment decisions.
This research underscores the value of combining Real-World Data with economic models to generate evidence that contributes to the quality and efficiency of healthcare.