Background/Aims: In the case of metastatic colorectal cancer (mCRC) there is sufficient evidence to show that significantly more effective and expensive anti-Epidermal Growth Factor Receptor (anti-EGFR) monoclonal antibodies like Cetuximab and Panitumumab are effective only if the patient does not have Kras and Braf genetic mutations. Using genetic screening, it is possible to detect these mutations, and avoid unnecessary treatment costs in patients where the use of anti-EGFR antibodies would be ineffective. Current work is based on a decision analysis model which includes anti-EGFR antibodies, anti-VEGF antibodies and chemotherapies as possible lines of treatment. The objective is to complete a cost-effectiveness analysis of screening for Kras and Braf genetic mutations in order to evaluate current and future guidelines on mutation testing.
Methods: A Monte Carlo Markov model for mCRC is built using eight basic states: surveillance, death, palliative, colon resection, anti-EGFR therapy, anti-VEGF therapy, Oxaliplatin-based therapy and Irinotecan-based therapy. We setup the model with patients having Kras and Braf genetic mutations and synchronous or asynchronous tumors, which can be resectable with variation in progression and response to lines of treatments with a probability equal to the prevalence rates. The model tracks patients on a weekly basis.
Results: We generated a comprehensive decision analysis model that simulates disease progression, treatment and screening of patients with mCRC. We will present the cost-effectiveness analysis of screening for Kras and Braf in various real world settings based upon results that will be available in March.
Conclusions: Our decision analysis model’s structure and functionality provides an intuitive understanding of the use of screening in the context of mCRC. It provides an objective tool for assessing guidelines regarding the use of genetic screening for mutations in mCRC tumors.