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Background: Psoriasis is an autoinflammatory disease that affects not only skin but multiple organs thus being associated with many comorbidities. Oxidative stress and inflammation play the major role in the pathogenesis of this disease. Studies that examined by-products of oxidative stress in psoriasis show discrepant results. Hence, we aimed to examine the oxidative stress, inflammation and metabolic markers and to explore their potential relationship with disease severity in patients with psoriasis. Methods: This case-control study comprised of 35 patients with psoriasis and 35 age, sex and body mass index-matched healthy controls. Metabolic and oxidative stress biomarkers [i.e., malondialdehyde (MDA), advanced oxidation protein products (AOPP), and catalase (CAT)] were measured. The principal component analysis (PCA) was employed to reduce the number of measured variables into smaller number of factors. PCA factors were subsequently used in logistic regression analysis for severe psoriasis prediction. Results: Higher AOPP levels (p<0.01) and CAT activity (p<0.001), but no difference in MDA levels in psoriasis patients vs. healthy controls were shown. Multivariate binary logistic regression analysis showed that a combination of metabolic related factor (i.e., glucose and triglycerides) and renal function related factor (i.e., creatinine and urea) was the best model for Psoriasis Area and Severity Index (PASI) >10 prediction, while oxidative stress-hepatic related factor (i.e., MDA, alanine aminotransferase) was selected as the best predictor for Dermatology Life Quality Index (DLQI) >20. Conclusion: Multi marker approach showed that metabolic and renal function related factor and oxidative stress-hepatic related factor were better predictors of psoriasis severity than each single examined biomarker. [ABSTRACT FROM AUTHOR]