Inflammation-based biomarkers for the prediction of nephritis in systemic lupus erythematosus

Abstract

Background/Aim: Inflammation is a crucial component in the pathophysiology of systemic lupus erythematosus (SLE) nephritis. Immune-based scores, such as the neutrophil-lymphocyte and the platelet-lymphocyte ratios (NLR and PLR, respectively) have been suggested as predictors of inflammation and prognosis in SLE. This study aimed to investigate the value of the systemic immune-inflammation index (SII), inflammatory prognostic index (IPI), and systemic inflammatory response index (SIRI) in SLE and lupus nephritis (LN). Methods: This case-control study consisted of 108 newly diagnosed SLE patients (separated into two subgroups, which included 34 patients with biopsy-proven LN and 74 without nephritis) and 108 age- and gender-matched healthy controls who presented to our outpatient clinic between October 2015 and June 2020. Patients with malignancy, lymphoproliferative and hematologic disorders, active infection, and autoimmune diseases other than SLE were excluded. Inflammation-based biomarkers were calculated at the first presentation of the disease and before any medication was administered. SII was calculated as Neutrophil/Lymphocyte x Platelet, SIRI as Neutrophil x Monocyte/Lymphocyte, and IPI as CRP x NLR/serum albumin. The Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) was used to measure disease activity. The capability of SII, SIRI, NLR, PLR, and IPI to distinguish between SLE patients with or without nephritis was assessed using receiver operating characteristic (ROC) curves. Correlations of inflammation-based scores (SII, SIRI, IPI, NLR) with disease activity and laboratory data of SLE patients were analyzed. Results: SII, SIRI, and IPI were significantly higher in SLE patients than in healthy controls (P=0.003, P=0.019, and P<0.001, respectively) and also significantly higher in patients with nephritis than in those without (P<0.001, P=0.009, and P=0.007, respectively). The area under the curve (AUC) for SII, SIRI, and IPI in terms of differentiating SLE patients with or without nephritis was 0.748, 0.690, and 0.663, respectively. The cut-off value of SII, SIRI, and IPI to predict LN was 552.25 (sensitivity: 64.7%; specificity: 64.9%; P<0.001), 1.08 (sensitivity: 61.8%; specificity: 62.2%; P=0.002), and 4.48 (sensitivity: 61.8%; specificity, 62.2%; P=0.007), respectively. Conclusion: SII, SIRI, and IPI may be valuable and promising inflammation-based biomarkers in SLE and for the presence of nephritis in SLE patients. SII was found to be the most reliable predictor of SLE among the inflammation-based biomarkers in our study.