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Экономическая эффективность доклинической диагностики болезни Паркинсона: марковская модель

Vartanov, Sergey and Bogatova, Irina and Denisova, Irina and Kucheryanu, Valerian and Tourdyeva, Natalia and Chubarova, Tatyana and Shakleina, Marina and Polterovich, Victor (2020): Экономическая эффективность доклинической диагностики болезни Паркинсона: марковская модель. Forthcoming in: The bulletin of the Far Eastern Federal University. Economics and Management

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Abstract

This work is devoted to the pharmacoeconomic analysis of the results of the introduction of early (preclinical) diagnosis of Parkinson's disease in Russia. On the basis of a combination of socio-economic determinants and a panel of blood biomarkers, it may be possible to identify among the entire population a “risk group” - people most likely to develop parkinsonism or are already sick with it 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 investigated 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"). Using 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 calculating the cost of therapy based on open data on the cost of drugs and procedures in Russian market (eapteka, apteka.ru, piluli.ru, website of the Ministry of Health of the Russian Federation), the work shows 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 of life-adjusted years) compared to standard therapy, and the average cost per patient until the end of life can be significantly reduced.

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