Please use this identifier to cite or link to this item:
Title: Performance of cytokine models in predicting SLE activity
Authors: Ruchakorn N.
Ngamjanyaporn P.
Suangtamai T.
Kafaksom T.
Polpanumas C.
Petpisit V.
Pisitkun T.
Pisitkun P.
Keywords: alpha interferon
complement component C3
complement component C4
double stranded DNA antibody
gamma interferon
interleukin 10
interleukin 12
interleukin 17
interleukin 18
interleukin 1beta
interleukin 23
interleukin 33
interleukin 6
interleukin 8
monocyte chemotactic protein 1
tumor necrosis factor
biological marker
interleukin 18
interleukin 6
interleukin 8
controlled study
correlation analysis
disease activity
disease exacerbation
flow cytometry
follow up
logistic regression analysis
lupus erythematosus nephritis
major clinical study
multivariate logistic regression analysis
odds ratio
prospective study
protein blood level
sensitivity and specificity
systemic lupus erythematosus
middle aged
severity of illness index
systemic lupus erythematosus
young adult
Inflammation Mediators
Lupus Erythematosus, Systemic
Middle Aged
Sensitivity and Specificity
Severity of Illness Index
Young Adult
Issue Date: 2019
Abstract: Background: Identification of universal biomarkers to predict systemic lupus erythematosus (SLE) flares is challenging due to the heterogeneity of the disease. Several biomarkers have been reported. However, the data of validated biomarkers to use as a predictor for lupus flares show variation. This study aimed to identify the biomarkers that are sensitive and specific to predict lupus flares. Methods: One hundred and twenty-four SLE patients enrolled in this study and were prospectively followed up. The evaluation of disease activity achieved by the SLE disease activity index (SLEDAI-2K) and clinical SLEDAI (modified SLEDAI). Patients with active SLE were categorized into renal or non-renal flares. Serum cytokines were measured by multiplex bead-based flow cytometry. The correlation and logistic regression analysis were performed. Results: Levels of IFN-α, MCP-1, IL-6, IL-8, and IL-18 significantly increased in active SLE and correlated with clinical SLEDAI. Complement C3 showed a weakly negative relationship with IFN-α and IL-18. IL-18 showed the highest positive likelihood ratios for active SLE. Multiple logistic regression analysis showed that IL-6, IL-8, and IL-18 significantly increased odds ratio (OR) for active SLE at baseline while complement C3 and IL-18 increased OR for active SLE at 12 weeks. IL-18 and IL-6 yielded higher sensitivity and specificity than anti-dsDNA and C3 to predict active renal and active non-renal, respectively. Conclusion: The heterogeneity of SLE pathogenesis leads to different signaling mechanisms and mediates through several cytokines. The monitoring of cytokines increases the sensitivity and specificity to determine SLE disease activity. IL-18 predicts the risk of active renal SLE while IL-6 and IL-8 predict the risk of active non-renal. The sensitivity and specificity of these cytokines are higher than the anti-dsDNA or C3. We propose to use the serum level of IL-18, IL-6, and IL-8 to monitor SLE disease activity in clinical practice. © 2019 The Author(s).
ISSN: 14786354
Appears in Collections:Scopus 1983-2021

Files in This Item:
There are no files associated with this item.

Items in SWU repository are protected by copyright, with all rights reserved, unless otherwise indicated.