Predicting the Relative Risk of Pharmacotherapy Based on a Mathematical Model of Age-Related Decline in Homeostasis in Elderly and Senile Patients

INTRODUCTION. The natural morpho-functional involution of the ageing body is accompanied by an age-related decline in homeostasis, which leads to changes in the pharmacodynamics, pharmacokinetics, and toxicity of medicines. Mathematical prediction models (MPMs) are a promising tool for predicting age-associated pharmacotherapy risks in elderly and senile patients. AIM. This study aimed to develop a simple linear mathematical model for predicting age-related changes in the relative risk of pharmacotherapy. MATERIALS AND METHODS. A basic statistical hypothesis for the MPM was formulated using generally accepted approaches and methods adapted to the original physiological concept of age-related decline in homeostasis. The prediction hypothesis has theoretical and clinical prerequisites. Statistically, the proposed MPM is a single-factor linear regression model. The main parameters and key criteria of the model include age (predictor), life expectancy, and the rates of population and physiological age-related decline in homeostasis. RESULTS. The algorithm developed for predicting the relative risk of pharmacotherapy based on the concept of age-related decline in homeostasis includes the following steps: 1) establishing the rate of population-based decline relative to the linear trend of hypothetical physiological decline; 2) determining the probability limits for critical age-related decline in homeostasis; 3) extrapolating the relative risk (RR) and the odds ratio (OR) of age-related decline in homeostasis to the corresponding pharmacotherapy parameters; and 4) using the available data on the risk of pharmacotherapy in young and middle-aged patients to convert predictions into quantitative characteristics of adverse drug reactions. The predictions based on the data obtained are in good agreement with clinical observations that indicate a 2–7-fold increase in the risk of developing adverse drug reactions during pharmacotherapy in elderly and senile patients. The physiological homeostatic decline rate in centenarians within the linear model corresponds to the age-related decline in human pharmacokinetic clearance parameters. The physiological homeostatic decline parameters allow researchers to assess the impact of population risk factors on age-related decline in homeostasis. CONCLUSIONS. The MPM developed in this study provides a means to predict the relative risk of pharmacotherapy in elderly and senile patients based on the concept of age-related decline in homeostasis. The results support further evaluation of the predictive effectiveness of the model.