The paper gives an overview of the four fundamental elements that should be considered when constructing a Markov model of cancers, including outcome measures, health state transition, transitional probabilities, and model calibration. The construction of any model of this kind should begin by establishing transition to the death state. The probability of this transition can be estimated using overall survival data from clinical studies. Possible health states over a cycle are defined according to the natural history of diseases and treatment pathways. Validity of the constructed model is tested against real patient data and the parameters are adjusted until the survival results are consistent.

Keywords: Health state, Markov model, Solid tumor, Survival, Transitional probability