Hybrid automated assessment of the clinical and economic effectiveness of melanoma antitumor drug therapy, taking into account the tumor’s molecular genetic characteristics and the patient’s functional status

Konstantinova Yulia S., Kanevsky Maxim A.

The cost of treating cancer patients is a serious problem in the Russian Federation, where funding decisions are based on health technology assessment - a systematic, explicit, multidisciplinary comparison of various treatments from a clinical, economic, ethical, and social point of view. While conventional methods of pharmacoeconomic analysis focus on the effectiveness of anticancer drug therapy from a health care system perspective, these data are often insufficient to improve treatment strategies in a particular health care setting. In our opinion, it is necessary to use a hybrid approach, namely: automation of the calculation of primary data with subsequent optimization of the revealed results by clinicians and oncologists. To analyze the volume of expenditures at the expense of the healthcare system and compulsory medical insurance funds, we used routine data on the functional status and molecular genetic features of tumors that affect the prognosis of the disease in patients. Data processing was performed in the PharmBudget software, which uses algorithms for calculations based on the theory of optimal resource allocation. This made it possible to identify opportunities for optimizing costs without reducing the survival rate. Subsequently, this information was used by expert oncologists to calculate the distribution of identified funds for more expensive manual therapy and, as a result, an increase in patient survival. The introduction of a hybrid automated assessment of the clinical and economic efficiency of antitumor drug therapy for cancer, taking into account the molecular genetic characteristics of the tumor and the functional status of the patient, greatly simplifies the process of studying treatment strategies and economic costs, frees up resources for those drugs that will be most in demand at a particular stage of activity in depending on the structure of the incidence to increase survival in the maximum number of patients. As a result, the healthcare organizations can establish a continuous process of improving the balance of clinical and economic outcomes in cancer patients.

Keywords:melanoma; Incremental Cost-Effectiveness Ratio (ICER); artificial intelligence; machine learning.