Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12216
Full metadata record
DC FieldValueLanguage
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.identifier.issn14786354
dc.identifier.other2-s2.0-85077084700
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12216-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85077084700&doi=10.1186%2fs13075-019-2029-1&partnerID=40&md5=276c68f597dc89d48c6bbbacb79a2a31
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.subjectalpha interferon
dc.subjectcomplement component C3
dc.subjectcomplement component C4
dc.subjectcytokine
dc.subjectdouble stranded DNA antibody
dc.subjectgamma interferon
dc.subjectinterleukin 10
dc.subjectinterleukin 12
dc.subjectinterleukin 17
dc.subjectinterleukin 18
dc.subjectinterleukin 1beta
dc.subjectinterleukin 23
dc.subjectinterleukin 33
dc.subjectinterleukin 6
dc.subjectinterleukin 8
dc.subjectmonocyte chemotactic protein 1
dc.subjecttumor necrosis factor
dc.subjectautacoid
dc.subjectbiological marker
dc.subjectcytokine
dc.subjectinterleukin 18
dc.subjectinterleukin 6
dc.subjectinterleukin 8
dc.subjectadult
dc.subjectArticle
dc.subjectcontrolled study
dc.subjectcorrelation analysis
dc.subjectdisease activity
dc.subjectdisease exacerbation
dc.subjectfemale
dc.subjectflow cytometry
dc.subjectfollow up
dc.subjecthuman
dc.subjectlogistic regression analysis
dc.subjectlupus erythematosus nephritis
dc.subjectmajor clinical study
dc.subjectmale
dc.subjectmultivariate logistic regression analysis
dc.subjectodds ratio
dc.subjectprediction
dc.subjectprospective study
dc.subjectprotein blood level
dc.subjectsensitivity and specificity
dc.subjectSLEDAI
dc.subjectsystemic lupus erythematosus
dc.subjectblood
dc.subjectmiddle aged
dc.subjectprognosis
dc.subjectseverity of illness index
dc.subjectsystemic lupus erythematosus
dc.subjectyoung adult
dc.subjectAdult
dc.subjectBiomarkers
dc.subjectCytokines
dc.subjectFemale
dc.subjectHumans
dc.subjectInflammation Mediators
dc.subjectInterleukin-18
dc.subjectInterleukin-6
dc.subjectInterleukin-8
dc.subjectLupus Erythematosus, Systemic
dc.subjectMale
dc.subjectMiddle Aged
dc.subjectPrognosis
dc.subjectSensitivity and Specificity
dc.subjectSeverity of Illness Index
dc.subjectYoung Adult
dc.titlePerformance of cytokine models in predicting SLE activity
dc.typeArticle
dc.rights.holderScopus
dc.identifier.bibliograpycitationArthritis Research and Therapy. Vol 21, No.1 (2019)
dc.identifier.doi10.1186/s13075-019-2029-1
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.