Analysis of the use of GEBD in a group of patients with psoriasis (according to the data from the Moscow Scientific and Practical Center of Dermatovenereology and Cosmetology of the Moscow Healthcare Department)

Psoriasis and psoriatic arthritis are chronic immune-mediated diseases with a high risk of comorbid conditions, for which the use of genetically engineered biological drugs (GEBD) is the most effective modern approach. Choice of the optimal drug requires considering clinical and demographic factors, treatment line and presence of concomitant diseases. Material and methods. A retrospective analysis of data from 405 patients (268 men, 137 women; mean age 46.7 years) with psoriasis vulgaris (43%) and arthropathic psoriasis (57%) who were receiving GEBD was performed. The distribution by drugs, frequency of efficacy «escape», influence of therapy line and comorbid pathology was evaluated. Statistical processing included the calculation of relative values, medians, interquartile range and correlation analysis. Results. Netakimab was the most frequently prescribed agent (45.4%) with a minimum frequency of therapy «escape» effect equal 12.8%. Among the used classes of drugs, inhibitors of IL-23 (10.3%) and IL-17 (25.3%) had the most stable positive effect; at the same time, TNF-α inhibitors showed the highest frequency of loss of effect (54.9%). The first line of therapy had a median response of 93.0%, which decreased by 2—6 p.p. to the 3rd—4th lines. Metabolic syndrome (40.1%) and cardiovascular diseases (32.1%) were associated with lower response to therapy, especially in application of TNF inhibitors. The IL-17 and IL-23 inhibitors showed stable efficacy even in late administration and in patients with comorbid pathology. Discussion. The obtained results confirm the need for a personalized selection of GEBD considering the diagnosis, line of therapy and profile of comorbid pathology. Drug classes of IL-23 and IL-17 inhibitors are preferred in late lines and in patients with high cardiometabolic risk. Conclusion. The implementation of a stratified approach to the choice of GEBD and early selection of the most effective drug can reduce the risk of «escape» effect and improve long-term treatment results.

Authors

Institutions

Publication Details

Journal
Russian Journal of Clinical Dermatology and Venereology
Published
2026-03-16
DOI
https://doi.org/10.17116/klinderma20262501153
Primary Topic
Psoriasis: Treatment and Pathogenesis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of the use of GEBD in a group of patients with psoriasis (according to the data from the Moscow Scientific and Practical Center of Dermatovenereology and Cosmetology of the Moscow Healthcare Department)

I.A. Mikhaylova, O. Zhukova, N. Potekaev, S.I. Artemyeva et al.
Russian Journal of Clinical Dermatology and Venereology
Psoriasis: Treatment and Pathogenesis
article

Analysis of the use of GEBD in a group of patients with psoriasis (according to the data from the Moscow Scientific and Practical Center of Dermatovenereology and Cosmetology of the Moscow Healthcare Department)

I.A. Mikhaylova, O. Zhukova, N. Potekaev, S.I. Artemyeva, V. A. Volnukhin, O.V. Dolya, A.G. Gadzhigoroeva, O.L. Novozhilova
article en

Abstract

Psoriasis and psoriatic arthritis are chronic immune-mediated diseases with a high risk of comorbid conditions, for which the use of genetically engineered biological drugs (GEBD) is the most effective modern approach. Choice of the optimal drug requires considering clinical and demographic factors, treatment line and presence of concomitant diseases. Material and methods. A retrospective analysis of data from 405 patients (268 men, 137 women; mean age 46.7 years) with psoriasis vulgaris (43%) and arthropathic psoriasis (57%) who were receiving GEBD was performed. The distribution by drugs, frequency of efficacy «escape», influence of therapy line and comorbid pathology was evaluated. Statistical processing included the calculation of relative values, medians, interquartile range and correlation analysis. Results. Netakimab was the most frequently prescribed agent (45.4%) with a minimum frequency of therapy «escape» effect equal 12.8%. Among the used classes of drugs, inhibitors of IL-23 (10.3%) and IL-17 (25.3%) had the most stable positive effect; at the same time, TNF-α inhibitors showed the highest frequency of loss of effect (54.9%). The first line of therapy had a median response of 93.0%, which decreased by 2—6 p.p. to the 3rd—4th lines. Metabolic syndrome (40.1%) and cardiovascular diseases (32.1%) were associated with lower response to therapy, especially in application of TNF inhibitors. The IL-17 and IL-23 inhibitors showed stable efficacy even in late administration and in patients with comorbid pathology. Discussion. The obtained results confirm the need for a personalized selection of GEBD considering the diagnosis, line of therapy and profile of comorbid pathology. Drug classes of IL-23 and IL-17 inhibitors are preferred in late lines and in patients with high cardiometabolic risk. Conclusion. The implementation of a stratified approach to the choice of GEBD and early selection of the most effective drug can reduce the risk of «escape» effect and improve long-term treatment results.

Russian Journal of Clinical Dermatology and VenereologyVol. 25(1)
Peoples' Friendship University of Russia (RU), Pirogov Russian National Research Medical University (RU), State Research Center for Dermatovenereology and Cosmetology (RU)
Good health and well-being
Openalex Percentile: Top 19%
Psoriasis: Treatment and Pathogenesis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.