Abstract
Background: Systemic inflammation is one of the underlying mechanisms of ankylosing spondylitis (AS) and rheumatoid arthritis (RA). More precise and effective diagnostic techniques can be developed by having an improved comprehension of the function of inflammatory indices in autoimmune disorders. Determining trustworthy biomarkers may help identify these illnesses early. Early diagnosis is imperative in ascertaining that patients receive their therapy as early as possible before any damage can occur, however there are certain conditions in which earlier diagnosis remains elusive.
Aims: Systemic immune-inflammation index (SII) has emerged as a promising biomarker. literature of SII on this matter is scarce and the one available reveals some inconsistencies. Therefore, the present meta-analysis is aimed to evaluate the diagnostic and prognostic ability of SII and association between high SII and AS and RA.Method: In this systematic review and meta-analysis, electronic databases, including PubMed, Ovid®, the Cochrane database, Scopus, and Web of Science, and the grey literature were searched from inception to June 28, 2024, using subject headings and text word terms related to “ankylosing spondylitis”, “axial spondyloarthritis”, “rheumatoid arthritis”, “RA”, “AS”, “systemic inflammation-index”, and “SII”. Quality of included literature was assessed using the Newcastle-Ottawa Scale (NOS) assessment scale, The Begg’s test, Egger test, and funnel plot/ the “trim-and-fill” method was used to evaluate the publication bias. The pooled standard mean difference (SMD) with 95% confidence interval (CI) of SII was calculated using random-effect model. Subgroup analysis and meta-regression were used to investigate the potential source of heterogeneity. Two-by-two tables from every study, the values for true positive (TP), false positive (FP), false negative (FN), and true negative (TN) were calculated. SROC was calculated using reitsma function in and DOR using metabin function in R.
Results: In 9 eligible study investigations, consisting of 1,194 patients with AS and RA (mean age: 56, 59.4% females) had a substantially elevated SII as opposed to 773 controls (mean age:58, 59% females) (SMD = 0.99, 95% CI 0.50 to 1.49, P<0.01; I2 = 94%, P<0.01). The pooled SMD values were stable ranging from 0.85 to 1.098. The Begg’s and Eggers both revealed no presence of bias. In subgroup analysis there was no significant difference (P = 0.78) in pooled SMD across countries, the subgroup analysis further showed that pooled SMD was significantly increased in AS studies as well as RA studies (SMD = 0.64, 95% CI 0.14 – 1.13, P < 0.01; I2 = 94%, P < 0.01), (SMD = 1.36, 95% CI 0.78 – 1.94, P <0.01; I2 = 94%, P < 0.01) respectively. Furthermore, the SII was substantially elevated in AS and RA patients with active disease as opposed to those in remission (SMD = 0.91, 95% CI: 1.78 to 0.04, P < 0.01; I2 = 94%, P < 0.01). The pooled AUC, sensitivity and specificity values of the Summary receiver operating characteristic (SROC) were 0.725, 68.6% (95% CI: 0.545 – 0.799), 33.5% (95% CI: 0.199 – 0.506) respectively. We found DOR to be 4.6, P = 0.0158 for the identification of active disease.
Conclusion: Our study investigation illustrates that SII can effectively detect active disease and differentiate between active and remission. However supplementary investigations especially the ones investigating SII diagnostic performance for identification of AS or RA are warranted.
Funding: This work was supported by grants from the National Natural Science Foundation of China (82073655, 82373672).
Declaration of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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