Publication:
Performance of cytokine models in predicting SLE activity

dc.contributor.authorRuchakorn N.
dc.contributor.authorNgamjanyaporn P.
dc.contributor.authorSuangtamai T.
dc.contributor.authorKafaksom T.
dc.contributor.authorPolpanumas C.
dc.contributor.authorPetpisit V.
dc.contributor.authorPisitkun T.
dc.contributor.authorPisitkun P.
dc.date.accessioned2021-04-05T03:02:16Z
dc.date.available2021-04-05T03:02:16Z
dc.date.issued2019
dc.date.issuedBE2562
dc.description.abstractBackground: 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.format.mimetypeapplication/pdf
dc.identifier.citationArthritis Research and Therapy. Vol 21, No.1 (2019)
dc.identifier.doi10.1186/s13075-019-2029-1
dc.identifier.issn14786354
dc.identifier.other2-s2.0-85077084700
dc.identifier.urihttps://hdl.handle.net/20.500.14740/5023
dc.rights.holderScopus
dc.subject.otherAlpha interferon
dc.subject.otherComplement component C3
dc.subject.otherComplement component C4
dc.subject.otherCytokine
dc.subject.otherDouble stranded DNA antibody
dc.subject.otherGamma interferon
dc.subject.otherInterleukin 10
dc.subject.otherInterleukin 12
dc.subject.otherInterleukin 17
dc.subject.otherInterleukin 18
dc.subject.otherInterleukin 1beta
dc.subject.otherInterleukin 23
dc.subject.otherInterleukin 33
dc.subject.otherInterleukin 6
dc.subject.otherInterleukin 8
dc.subject.otherMonocyte chemotactic protein 1
dc.subject.otherTumor necrosis factor
dc.subject.otherAutacoid
dc.subject.otherBiological marker
dc.subject.otherCytokine
dc.subject.otherInterleukin 18
dc.subject.otherInterleukin 6
dc.subject.otherInterleukin 8
dc.subject.otherAdult
dc.subject.otherArticle
dc.subject.otherControlled study
dc.subject.otherCorrelation analysis
dc.subject.otherDisease activity
dc.subject.otherDisease exacerbation
dc.subject.otherFemale
dc.subject.otherFlow cytometry
dc.subject.otherFollow up
dc.subject.otherHuman
dc.subject.otherLogistic regression analysis
dc.subject.otherLupus erythematosus nephritis
dc.subject.otherMajor clinical study
dc.subject.otherMale
dc.subject.otherMultivariate logistic regression analysis
dc.subject.otherOdds ratio
dc.subject.otherPrediction
dc.subject.otherProspective study
dc.subject.otherProtein blood level
dc.subject.otherSensitivity and specificity
dc.subject.otherSLEDAI
dc.subject.otherSystemic lupus erythematosus
dc.subject.otherBlood
dc.subject.otherMiddle aged
dc.subject.otherPrognosis
dc.subject.otherSeverity of illness index
dc.subject.otherSystemic lupus erythematosus
dc.subject.otherYoung adult
dc.subject.otherAdult
dc.subject.otherBiomarkers
dc.subject.otherCytokines
dc.subject.otherFemale
dc.subject.otherHumans
dc.subject.otherInflammation Mediators
dc.subject.otherInterleukin-18
dc.subject.otherInterleukin-6
dc.subject.otherInterleukin-8
dc.subject.otherLupus Erythematosus, Systemic
dc.subject.otherMale
dc.subject.otherMiddle Aged
dc.subject.otherPrognosis
dc.subject.otherSensitivity and Specificity
dc.subject.otherSeverity of Illness Index
dc.subject.otherYoung Adult
dc.titlePerformance of cytokine models in predicting SLE activity
dc.typeArticle
dspace.entity.typePublication
swu.datasource.scopushttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85077084700&doi=10.1186%2fs13075-019-2029-1&partnerID=40&md5=276c68f597dc89d48c6bbbacb79a2a31

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