ABSTRACT
Objective: evaluation of the clinical and economic efficiency of using Levilimab in the treatment of moderate and severe COVID-19 based on real world data (RWD). Material and methods. A single-center observational retrospective case-control study was performed. According to the matching algorithm, 834 pairs of patients with moderate and 347 pairs with severe infection were selected, similar in gender, age, vaccination status, severity of the disease and the level of C-reactive protein. Results. The clinical efficiency of Levilimab with respect to in-hospital mortality was demonstrated both for the moderate course (6% in the Levilimab group and 10% in the standard therapy group;odds ratio (OR) 1.71;95% confidence interval (CI) 1.19-2.47;p<0.01) and for the severe course of COVID-19 (63% and 82%, respectively;OR 2.70;95% CI 1.90-3.82;p<0.01). The costs per 1 treated patient were also higher in the Levilimab therapy groups: the difference in costs compared to the standard therapy group for patients with moderate disease was 54 665.30 rubles, with severe disease - 91 285.85 rubles. The estimated cost of the additional effectiveness of Levilimab for the moderate course of the disease was 13, 666.32 rubles, for the severe course - 4, 804.51 rubles. Conclusion. The use of Levilimab for the treatment of moderate and severe COVID-19 is feasible both from a clinical and economic points of view. Conducting RWD trials is an important tool to understand the effectiveness of medical technologies in real clinical practice.Copyright © 2023 IRBIS LLC. All Rights Reserved.
ABSTRACT
Objective. To evaluate safety of anti-interleukin drugs used as a pathogenetic therapy of COVID-19 as assessed by risks of infectious complications. Materials and methods. A systematic review of publications related to safety assessment of anti-interleukin drugs recommended as pathogenetic therapy in COVID-19 patients in terms of incidence of serious adverse events and adverse events of "Infections and Invasions" class and a meta-analysis of the data were performed. Results. The meta-analysis included 16 randomized and 3 non-randomized studies. The hazard ratio of serious adverse events between the comparison groups was 0.93 [95% CI 0.85;1.01] (p = 0.1), the hazard ratio of adverse event of "Infections and Invasions" class was 0.9 [95% CI 0.8;1.02] (p = 0.09), showing no differences in the incidence of those events. Conclusions. This meta-analysis did not demonstrate statistically significant differences in the relative risks of serious adverse events and adverse events of "Infections and Invasions" class for the use of anti-interleukin drugs in COVID-19 patients.Copyright © 2022, Interregional Association for Clinical Microbiology and Antimicrobial Chemotherapy. All rights reserved.
ABSTRACT
Objective. To evaluate safety of anti-interleukin drugs used as a pathogenetic therapy of COVID-19 as assessed by risks of infectious complications. Materials and methods. A systematic review of publications related to safety assessment of anti-interleukin drugs recommended as pathogenetic therapy in COVID-19 patients in terms of incidence of serious adverse events and adverse events of “Infections and Invasions” class and a meta-analysis of the data were performed. Results. The meta-analysis included 16 randomized and 3 non-randomized studies. The hazard ratio of serious adverse events between the comparison groups was 0.93 [95% CI 0.85;1.01] (p = 0.1), the hazard ratio of adverse event of “Infections and Invasions” class was 0.9 [95% CI 0.8;1.02] (p = 0.09), showing no differences in the incidence of those events. Conclusions. This meta-analysis did not demonstrate statistically significant differences in the relative risks of serious adverse events and adverse events of “Infections and Invasions” class for the use of anti-interleukin drugs in COVID-19 patients. © 2022, Interregional Association for Clinical Microbiology and Antimicrobial Chemotherapy. All rights reserved.
ABSTRACT
The case-based rate reasoning (CBRR) method is presented for predicting future values of the coronavirus epidemic's main parameters in Russia, which makes it possible to build short-term forecasts based on analogues of the percentage growth dynamics in other countries. A new heuristic method for estimating the duration of the transition process of the percentage increase between specified levels is described, taking into account information about the dynamics of epidemiological processes in countries of the spreading chain. The CBRR software module has been developed in the MATLAB environment, which implements the proposed approach and intelligent proprietary algorithms for constructing trajectories of predicted epidemic indicators.