OncohematologyOncohematologyОнкогематология1818-83462413-4023Publishing House ABV Press11910.17650/1818-8346-2014-9-3-16-24HEMATOLOGIC MALIGNANCIES: DIAGNOSIS, TREATMENT, SUPPORTIVE CAREГЕМОБЛАСТОЗЫ: ДИАГНОСТИКА, ЛЕЧЕНИЕ, СОПРОВОДИТЕЛЬНАЯ ТЕРАПИЯPharmacoeconomic modeling of target therapy of chronic myeloid leukemia in remissionФармакоэкономическое моделирование таргетной терапии у больных хроническим миелолейкозом в ремиссииShuvaevV. A.ШуваевВ. А.
Russian Federation
shuvaev77@mail.ruAbdulkadyrovK. M.АбдулкадыровК. М.
Russian Federation
MartynkevichI. S.МартынкевичИ. С.
Russian Federation
FominykhM. S.ФоминыхМ. С.
Russian Federation
Russian Research Institution of Hematology and Transfusiology, Federal Medical and Biological Agency, St.-PetersburgФГБУ «Российский научно-исследовательский институт гематологии и трансфузиологии» ФМБА России, Санкт-Петербург3010201493162430012015300120152014https://oncohematology.abvpress.ru/ongm/article/view/119

The article presents example of modeling for pharmacoeconomical-founded choice of chronic myelogenous leukemia treatment strategy related to therapeutic efficacy and economical rationality. The economic model of chronic myelogenous leukemia diagnosis and treatment with Markov chain approach was constructed, based on modern national and international clinical guidelines. Pharmacoeconomical comparison of chronic myelogenous leukemia target therapy using first and second-generation tyrosine kinase inhibitors was performed. The average direct cost for one patient and total budget impact in twenty years were calculated. Analysis was made based on costs of original imatinib and generics. We used the imatinib generics’ substitution experience as a scenario for the second generation TKIs. Under these conditions, more frequent therapy cessation with second generation TKIs resulted in nilotinib first line is cost saving over imatinib. We should note that theresults of our analysis were strongly dependent on the input parameters values. The Pharmacoeconomic modelling can forecast the budget burden and its future dynamics on the individual and national level. The results of such modelling could be of value in decision-making in national guidelines development and discussion with healthcare authorities.

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