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Performance of cytokine models in predicting SLE activity

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dc.contributor.author Ruchakorn N.
dc.contributor.author Ngamjanyaporn P.
dc.contributor.author Suangtamai T.
dc.contributor.author Kafaksom T.
dc.contributor.author Polpanumas C.
dc.contributor.author Petpisit V.
dc.contributor.author Pisitkun T.
dc.contributor.author Pisitkun P.
dc.date.accessioned 2021-04-05T03:02:16Z
dc.date.available 2021-04-05T03:02:16Z
dc.date.issued 2019
dc.identifier.issn 14786354
dc.identifier.other 2-s2.0-85077084700
dc.identifier.uri https://ir.swu.ac.th/jspui/handle/123456789/12216
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077084700&doi=10.1186%2fs13075-019-2029-1&partnerID=40&md5=276c68f597dc89d48c6bbbacb79a2a31
dc.description.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).
dc.subject alpha interferon
dc.subject complement component C3
dc.subject complement component C4
dc.subject cytokine
dc.subject double stranded DNA antibody
dc.subject gamma interferon
dc.subject interleukin 10
dc.subject interleukin 12
dc.subject interleukin 17
dc.subject interleukin 18
dc.subject interleukin 1beta
dc.subject interleukin 23
dc.subject interleukin 33
dc.subject interleukin 6
dc.subject interleukin 8
dc.subject monocyte chemotactic protein 1
dc.subject tumor necrosis factor
dc.subject autacoid
dc.subject biological marker
dc.subject cytokine
dc.subject interleukin 18
dc.subject interleukin 6
dc.subject interleukin 8
dc.subject adult
dc.subject Article
dc.subject controlled study
dc.subject correlation analysis
dc.subject disease activity
dc.subject disease exacerbation
dc.subject female
dc.subject flow cytometry
dc.subject follow up
dc.subject human
dc.subject logistic regression analysis
dc.subject lupus erythematosus nephritis
dc.subject major clinical study
dc.subject male
dc.subject multivariate logistic regression analysis
dc.subject odds ratio
dc.subject prediction
dc.subject prospective study
dc.subject protein blood level
dc.subject sensitivity and specificity
dc.subject SLEDAI
dc.subject systemic lupus erythematosus
dc.subject blood
dc.subject middle aged
dc.subject prognosis
dc.subject severity of illness index
dc.subject systemic lupus erythematosus
dc.subject young adult
dc.subject Adult
dc.subject Biomarkers
dc.subject Cytokines
dc.subject Female
dc.subject Humans
dc.subject Inflammation Mediators
dc.subject Interleukin-18
dc.subject Interleukin-6
dc.subject Interleukin-8
dc.subject Lupus Erythematosus, Systemic
dc.subject Male
dc.subject Middle Aged
dc.subject Prognosis
dc.subject Sensitivity and Specificity
dc.subject Severity of Illness Index
dc.subject Young Adult
dc.title Performance of cytokine models in predicting SLE activity
dc.type Article
dc.rights.holder Scopus
dc.identifier.bibliograpycitation Arthritis Research and Therapy. Vol 21, No.1 (2019)
dc.identifier.doi 10.1186/s13075-019-2029-1


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