Individuals with LS have an increased risk to develop CRC due to a genetic mutation. To reduce this risk, they are currently recommended to undergo two-yearly colonoscopy surveillance. There is accumulating evidence that CRC risk depends on an individual's risk profile e.g. mutation type, age and sex. This suggests that surveillance can be optimized by switching from the current one-size-fits-all approach to risk-based surveillance strategies. As a PhD student, you will work on the Lynch project, led by Dr. Veerle Coupé, with the aim to optimize CRC surveillance in individuals with LS. To achieve this aim, you will compare a range of risk-based surveillance strategies by making model predictions of long-term benefits, harms and cost-effectiveness.
The first task in this project is to gain more insight in CRC risk in individuals with LS. To this end, you will estimate adenoma incidence and progression rates to CRC by applying a Bayesian three-state statistical model to data of individuals undergoing colonoscopy surveillance. In this dataset, there is information available on the timing and the yield of colonoscopy. Subsequently, you will develop a microsimulation model to simulate the natural history of CRC in LS individuals (task 2). This model will synthesize information from task 1, scientific literature and cost data. Using this model, you will assess how to optimize CRC surveillance by comparing a range of surveillance strategies in which the intensity of surveillance is based on an individual's risk (task 3). This project requires both mathematical-statistical skills to help with the model development (e.g. Markov and multi-state modelling), programming skills to implement ideas and conduct simulations, as well as interest in real-world applications.About your role
As a PhD student, your main tasks are:
- To apply a Bayesian three-state statistical model to surveillance data;
- To develop a microsimulation model that simulates CRC development in LS individuals, programmed in e.g. C++ or Python;
- To parametrize and validate the microsimulation model;
- To evaluate risk-based surveillance strategies with the microsimulation model in order to optimize CRC surveillance in LS individuals in terms of health outcomes, costs and cost-effectiveness;
- To publish your research findings in biomedical, health-economic, and/or epidemiological journals;
- To write a PhD thesis for defense at the Vrije Universiteit Amsterdam;
- To assist in teaching activities in biostatistics courses for medical students.