Finding cost-effective colorectal cancer screening strategies using multi-objective evolutionary algorithms and the MISCAN-Colon microsimulation model
Costs and effectiveness of screening strategies for colorectal cancer can be predicted using microsimulation models, such as MISCAN-Colon. Cost-effectiveness analyses use these outcomes to recommend efficient strategies. These studies usually consider a small number of strategies, mostly using only a single screening test and fixed intervals between interventions. By considering more strategies, efficiency can possibly be improved. However, the number of possible strategies is high and the microsimulation models are computationally expensive. Thus, an efficient algorithm is needed to identify efficient strategies. This thesis compares the performance of four multi-objective evolutionary algorithms (NSGA-11, SPEA2, PESA-II and IBEA) on an enumerated test case. First, each algorithm was tuned to perform well on this test case. Performance was then assessed using three unary (c-Performance, Inverted Generational Distance and Hypervolume) and two binary (Binary Hypervolume and Coverage) multi-objective performance measures. Statistical analysis showed that all measures indicate that NSGA-11 performs best on this problem. SPEA2 performed slightly worse, followed by IBEA and finally PESA-II. Inverted Generational Distance and Hypervolume were the most powerful measures, as they were able to find significant differences between each pair of algorithms. Finally, NSGA-11 was used to identify efficient strategies for a real case based on the United States scenario. Effectiveness could be improved by 2-22%, depending on the budget. Costs could be reduced by 8-201%, depending on the desired effectiveness. However, the identified strategies are probably too complex to be implemented in practice.
|Keywords||: colorectal cancer, screening, cost-effectiveness, microsimulation, multi-objective optimization, multi-objective evolutionary algorithms|
|Thesis Advisor||Birbil, S.I.|
Dunnewind, N. (2020, February 14). Finding cost-effective colorectal cancer screening strategies using multi-objective evolutionary algorithms and the MISCAN-Colon microsimulation model. Econometrie. Retrieved from http://hdl.handle.net/2105/51692