The role biomarkers of systemic inflammation as Predictors of Response to anti-cytokine therapy in Psoriasis.
- Authors: Batkaeva N.V.1, Olisova O.Y.2
-
Affiliations:
- Peoples' Friendship University of Russia
- The First Sechenov Moscow State Medical University (Sechenov University)
- Section: DERMATOLOGY
- Submitted: 07.04.2025
- Accepted: 09.06.2025
- Published: 22.09.2025
- URL: https://rjsvd.com/1560-9588/article/view/678204
- DOI: https://doi.org/10.17816/dv678204
- ID: 678204
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Abstract
BACKGROUND:
Integrated hematological indices SIRI, MLR, NLR, SII, PLR and AISI represent an easily accessible, inexpensive and objective parameter for monitoring psoriatic inflammation both in everyday clinical practice and in scientific research. Currently, there is very little data on the significance and dynamics of integral hematological indices in patients with psoriasis and psoriatic arthritis during anti-cytokine therapy.
AIM To study the effect of anticytokine therapy with an IL-17A inhibitor on NLR, PLR, MLR, SII and SIRI parameters in patients with psoriasis of varying severity.
Materials and methods.
All patients included in the study had their systemic inflammation indices SIRI, MLR, NLR, SII, PLR and AISI calculated before treatment and after 6 months of treatment with the IL-17A inhibitor (netakimab). A standardized assessment method, PASI index, was used to assess the area and severity of psoriatic lesions of the skin process.
Results.
The main group consisted of 77 patients with psoriasis, including 33 women (42.9%) and 44 men (57.1%). The average age of patients was 41.3 (±13.4) years. The average PASI value was 10.8 (3.2; 15.3). There were 58 patients with only skin manifestations of psoriasis (75.4%), and 19 patients with psoriatic arthritis (24.6%). In accordance with the clinical guidelines of the Russian Ministry of Health for the treatment of patients with psoriasis and psoriatic arthritis, a subgroup of patients was identified that received treatment with the IL-17A inhibitor netakimab. The first subgroup included 20 patients with moderate to severe psoriasis (Ps), the second - 19 patients with psoriatic arthritis (PsA).The total observation period was 10 months. No adverse reactions or complications occurred in any of the subjects in the study group. Almost complete skin clearance (PASI75) was recorded in all subjects in the study group 6 months after the start of therapy. When analyzing the values of SIRI, MLR, NLR, SII, PLR and AISI in patients with Ps and PsA, their different diagnostic dynamics were revealed against the background of treatment with the IL-17A inhibitor nekimab. Thus, NLR (p=0.047) and MLR (p=0.038) turned out to be the most sensitive to the therapy in patients with Ps. In PsA patients, no statistically significant dynamic changes were found for the MLR, NLR, and PLR indices during treatment. SIRI showed statistically significant dynamics both in the Ps group and in the PsA group. Thus, in Ps patients, SIRI decreased by 1.9 times (p=0.021), and in PsA patients - by 1.34 times (p=0.047). AISI showed statistically significant dynamics in the group of patients with Ps (decreased by 2.3 times after 6 months of treatment; p=0.005). In patients with PsA, the average AISI value decreased by only 1.27 times after 6 months of treatment (p=0.087). The systemic inflammation index SII was less sensitive and showed dynamics only in patients with skin manifestations of psoriasis (p=0.030).
Conclusion.
Based on the results of our study, we can conclude that integral hematological indices of systemic inflammation are a promising tool for assessing the effectiveness of anti-cytokine therapy in patients with severe forms of psoriasis. NLR, MLR, SII and AISI can be used to assess the reduction of systemic inflammation in patients with only skin manifestations of psoriasis. SIRI is an effective tool for assessing treatment efficacy in both psoriasis and psoriatic arthritis patients.
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About the authors
Nadezhda V. Batkaeva
Peoples' Friendship University of Russia
Author for correspondence.
Email: nbatkaeva.derm@yandex.ru
ORCID iD: 0000-0002-8350-5842
SPIN-code: 5884-1750
ResearcherId: A-4704-2017
http://www.researcherid.com/rid/A-4704-2017
MD, Cand. Sci. (Medicine), Associate Professor
Russian Federation, MoscowOlga Y. Olisova
The First Sechenov Moscow State Medical University (Sechenov University)
Email: olisovaolga@mail.ru
ORCID iD: 0000-0003-2482-1754
SPIN-code: 2500-7989
MD, Dr. Sci. (Medicine), Professor, Corresponding Member of the Russian Academy of Sciences
Russian Federation, MoscowReferences
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