PSORIASIS: A COMPREHENSIVE REVIEW OF CURRENT KNOWLEDGE
DOI:
https://doi.org/10.31435/ijitss.2(50).2026.5378Keywords:
Psoriasis, IL-23/IL-17 Axis, Environmental Triggers, HLA-C*06:02, Biological Therapy, Personalized MedicineAbstract
Introduction and Purpose: Psoriasis is a chronic systemic inflammatory disease that impairs quality of life and psychological well being. Its multifactorial etiology results from genetic predisposition, environmental triggers, and immune dysregulation where the IL-23/IL-17 axis plays a notable role. This review synthesizes current scientific literature on psoriasis, focusing on risk factors, pathogenesis, and available treatment methods.
Materials and Methods: This review analyzes 47 articles from the PubMed database published between 2002 and 2026, with an emphasis on recent literature. The review integrates etiopathogenesis with clinical management, including conventional therapies, biologics, and small-molecule inhibitors.
Description of the State of Knowledge: Psoriasis diagnosis relies on clinical assessment supported by the Psoriasis Area and Severity Index (PASI), Body Surface Area (BSA), and Dermatology Life Quality Index (DLQI) scales. Pathogenesis involves genetic and environmental factors leading to the activation of the IL-23/IL-17 axis and chronic inflammation. Management includes lifestyle modification and individualized therapy through topical treatments, phototherapy, systemic drugs, and biologic therapies tailored to disease severity and quality of life.
Conclusion: The contemporary understanding of psoriasis pathogenesis focuses on the interleukin-23/interleukin-17 axis and the significant role of genetic factors, including the HLA-C06:02 variant. Therapeutic advances, particularly the introduction of biologic agents and novel targeted molecules, have substantially improved treatment efficacy. However, important limitations remain, including the lack of reliable serological markers and the insufficient ability to predict treatment response; therefore, further research into predictive biomarkers and artificial intelligence–based tools is essential.
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Copyright (c) 2026 Karol Zimnicki, Maksymilian Szklarski , Jędrzej Sztajura, Karol Józef Szkarłat, Szymon Targosz, Michał Stachel, Ewa Maraszewska, Weronika Szymacha, Aleksandra Płecka, Alicja Stępień

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