Экономическая эффективность доклинической диагностики болезни Паркинсона: марковская модель

This article contains a pharmacoeconomic analysis of early (preclinical) diagnosis of Parkinson's disease in Russia. Previous works show that using a combination of socio-economic determinants and a panel of blood biomarkers one may distinguish a Parkinsonism-related “risk group” among the entire population. This group consists of people who are most vulnerable to parkinsonism or are already ill, but at the preclinical stage. Together with the approach traditionally used in the pharmacoeconomics of chronic and long-term diseases, based on the representation of the dynamics of the development of the disease using Markov chains - discrete random processes without memory - this makes it possible to analyze the economic effects of early detection of cases and conducting preventive preclinical therapy. The work investigates the Markov model of Parkinson's disease, consisting of nine states - five states corresponding to the stages HY1-HY5, two preclinical states ("risk group", "prodromal state"). We use as the initial data for the model the probability of transition between states and health-adjusted quality of life (HRQoL) estimates, published in a number of works of researchers affiliated with AbbVie Corporation, and calculate the cost of therapy based on open data on the cost of drugs and procedures in Russian market. Moreover, we show that due to the introduction of preclinical diagnostics and preventive treatment at preclinical stages, identified patients can significantly increase the average survival time (in quality-adjusted life-years) compared to standard therapy, and the average cost per patient until the end of life can be significantly reduced.