RA is a chronic systemic autoimmune disorder characterized by persistent synovial inflammation, progressive joint destruction, and various extra-articular manifestations (30). Its complex pathogenesis involves disrupted bone remodeling due to an imbalance between osteoblast and osteoclast activity, synoviocyte hyperplasia, and immune dysregulation (31). At the cellular level, the aberrant activation of T cells, B cells, and macrophages drives chronic inflammation and tissue damage. This immune activation is accompanied by excessive secretion of pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-17 (IL-17) (24, 32, 33).

Emerging evidence suggests that impaired regulatory T cell function and the expansion of autoreactive T cells promote B cell hyperactivity and autoantibody production in RA (24, 34, 35). Dysfunctional immune homeostasis, marked by impaired T-cell regulation and excessive B-cell activity, plays a central role in perpetuating autoimmunity (36, 37). As RA progresses, systemic inflammation intensifies and can be quantitatively assessed using hematological indices. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have shown greater sensitivity in reflecting inflammatory burden than individual cell counts (37). More comprehensively, the SII, which incorporates lymphocyte, neutrophil, and platelet counts, serves as an applicable composite index of the immune-inflammatory status in RA.

The SII has emerged as a promising biomarker for systemic inflammation and immune cell dynamics. Thus in RA, the SII has shown value in assessing disease activity and inflammatory burden.

Satis et al. (38) reported that the SII levels were significantly higher in patients with RA compared to healthy controls (HCs), with a positive correlation between the SII values and disease activity. Active RA was associated with higher SII (702.25 ± 39.56) than remission (574.69 ± 34.72). Additional data showed mean SII levels of 666.42 ± 33.00 in patients with RA versus 596.71 ± 57.64 in HCs.

Supporting evidence from Choe et al. (39) demonstrated significant correlations between SII and composite disease activity scores, including the Disease Activity Score (DAS)28-ESR, DAS28-CRP, CDAI, and SDAI. SII values increased with disease severity, suggesting that it may be a sensitive cell-based index for tracking RA progression.

Population-based data support this association. A cross-sectional NHANES analysis (n = 37,604) (40) found that a higher SII was independently associated with an increased RA prevalence. Restricted cubic spline analysis revealed a non-linear dose–response relationship, with an inflection point at ln-SII = 6.36 (SII ≈ 578.25), beyond which RA risk increased sharply.

Although RA remains the primary focus, the SII has demonstrated utility in predicting treatment response. In a retrospective study of 154 patients with RA treated with TNF-α inhibitors, Bai et al. (41) found that pre-treatment SII levels were significantly lower in responders than in non-responders. Among the tested inflammatory markers, the SII and lymphocyte count exhibited the strongest predictive value for therapeutic efficacy, outperforming conventional biomarkers such as CRP and RF. These findings support SII’s potential in stratifying patients for biological therapy and predicting outcomes.

Recent findings suggest that the SII may reflect not only immune activation, but also molecular alterations associated with aging and immune dysregulation. A study of 982 patients with RA from the NHANES 2007–2016 identified a remarkable inverse association between the SII and serum levels of soluble Klotho protein (42), and a significant inverse correlation was observed between the SII and serum Klotho protein—an anti-aging, anti-inflammatory molecule secreted mainly by the kidneys and parathyroid glands (43, 44). Serum Klotho concentrations quantified using ELISA showed consistent inverse correlations with SII across regression models, independent of age, comorbidities, or metabolic status (42).

Mechanistically, Klotho modulates immune and oxidative stress pathways. Experimental studies indicate that Klotho attenuates reactive oxygen species, suppresses pro-inflammatory cytokines (e.g., IL-6, TNF-α), and inhibits NF-κB signaling (45). It also influences the neutrophil activity, lymphocyte function, and platelet activation (46–48). In RA, where macrophage-driven inflammation contributes to joint destruction (36, 49), reduced Klotho levels may indicate the failure of endogenous anti-inflammatory regulation. The observed inverse trend between SII and serum Klotho suggests that SII may reflect not only immune cell imbalance but also the underlying immunosenescence and molecular stress.

Several studies have evaluated the diagnostic utility of the SII and have proposed clinically relevant cutoff values. Satis et al. (38), reported an AUC of 0.643 for SII in distinguishing active RA, with sensitivity of 56.3% and specificity of 45.5% at a threshold of 574.20. In contrast, a study of female RA patients proposed a lower cutoff of 305.6, yielding 85% sensitivity and 42% specificity for distinguishing patients from healthy controls (39). These findings suggest that the SII may serve as an accessible and cost-effective adjunct for screening and disease monitoring, particularly when conventional biomarkers are inaccurate.

Another study comparing the SII and pan-immune-inflammation value (PIV) found that both indices were elevated in patients with active RA compared to those in remission or HCs. PIV outperformed the SII in distinguishing remission from health, suggesting that PIV may offer superior sensitivity in detecting low-grade inflammation (50, 51). Another ROC-based study confirmed the acceptable diagnostic performance of the SII in active disease but noted limited utility for remission detection (39).

Collectively, the current evidence highlights the clinical relevance of the SII in RA. It shows consistent correlation with composite disease activity indices (e.g., DAS28 and CDAI) (38, 39), enables stratification by inflammatory burden and treatment response (41), and reflects broader immunometabolic dysregulation, including Klotho deficiency (42). Proposed cutoffs—305.6 (sensitivity, 85%; specificity, 42%) (39) may assist in disease monitoring and risk classification. Satis et al. (38) reported an AUC of 0.643 for SII in distinguishing active RA, with sensitivity of 56.3% and specificity of 45.5% at a cutoff of 574.20. These findings collectively suggest that SII thresholds require careful optimization to maximize diagnostic utility.

However, this study has a few limitations. The SII’s discriminatory power diminishes in low-inflammatory or near-remission states. In these cases, novel indices, such as PIV, may provide better sensitivity. In support of this, ROC analyses showed that, while the SII retained fair accuracy in active RA, it was less effective for remission monitoring (39).

Future studies should validate the current cutoffs longitudinally and define SII dynamics across treatment courses. Integrating the SII with conventional markers (e.g., CRP and ESR) may enhance diagnostic precision, while a combination with emerging indices such as the systemic inflammation response index (SIRI) may expand its value in predicting RA-related complications, including interstitial lung disease and malignancy (52).

AS and PsA are the two major subtypes of SpA that primarily affect the axial skeleton and peripheral joints (53). These diseases are frequently accompanied with systemic manifestations and comorbidities. Immunologically, both AS and PsA are driven by dysregulated immune responses and sustained inflammation, contributing to progressive joint damage, reduced mobility, and functional disability (54–56).

Recent studies have evaluated the utility of SII in assessing disease activity in patients with AS and PsA. In a cross-sectional study involving 100 patients with SpA (including both AS and PsA), the median SII exceeded 600, indicating active systemic inflammation. Patients with high disease activity demonstrated significantly elevated SII levels, which were positively correlated with conventional inflammatory markers, such as ESR and CRP, supporting the potential of SII as an objective indicator of inflammatory burden in SpA (57).

Additional evidence was obtained from a retrospective study involving 136 patients with AS and 63 HCs, which identified the SII as the most effective single biomarker for differentiating active diseases. Using a cut-off value of 513.2, the SII achieved 86.84% sensitivity and 83.33% specificity for detecting active AS, outperforming conventional laboratory indices (58).

Furthermore, in a study assessing patients with combined axial and peripheral SpA, an increased SII was significantly associated with active disease, as defined by BASDAI > 4 and DAPSA > 14. Notably, SII strongly correlates with ultrasonography-detected synovitis in peripheral SpA, suggesting its value as a marker of both systemic and local inflammation (57).

Psoriasis, especially when accompanied by PsA, is increasingly being recognized as a systemic inflammatory condition that extends beyond cutaneous involvement (59). Biological therapies with anti-inflammatory mechanisms have demonstrated efficacy in managing skin and joint symptoms, systemic inflammation, and associated comorbidities (60).

In this therapeutic context, the SII has shown potential as a marker of treatment response. In a study of 220 patients with psoriasis, SII values significantly decreased after three months of biologic therapy (P< 0.001) (61). Subgroup analyses revealed significant reductions across several classes of biologic agents, including TNF-α inhibitors, IL-17 inhibitors, and IL-12/23 inhibitors, as well as with individual agents such as adalimumab, infliximab, ixekizumab, secukinumab etc. This suggests that the SII may serve as a reliable marker for monitoring therapeutic efficacy and predicting remission in patients with psoriasis and PsA.

Another study reported significantly higher SII in patients with PsA than in those with psoriasis. SII values were positively correlated with PASI scores and the presence of arthritis, further supporting its potential role as a prognostic marker for psoriatic disease (62). Moreover, the SII was significantly elevated in patients with moderate-to-severe PsA disease activity, as defined by the DAPSA scores. A proposed diagnostic cutoff of 800 yields high sensitivity and specificity for disease activity identification (63).

Collectively, the current evidence supports the clinical utility of the SII in assessing disease activity in AS and monitoring treatment responses in psoriasis and PsA. Its strong correlation with clinical indices and imaging findings, along with its association with PsA severity and progression, highlight its prognostic value. However, this study had several limitations. Disease-specific cutoffs have not yet been standardized, and their applicability across different SpA subtypes and disease stages requires further clarification. Future studies should prioritize longitudinal validation, integration of conventional markers and emerging immune signatures, and evaluation using multiparametric clinical algorithms (57).

SLE is a chronic multisystem autoimmune disorder characterized by alternating flares, remission, and dysregulation of the innate and adaptive immunity (64, 65). Clinically, SLE presents with heterogeneous manifestations involving the skin, joints, kidneys, central nervous system, and hematopoietic system (66, 67). The cellular components of SII are pathophysiologically relevant to SLE.

Neutrophils form NETs and exacerbate inflammation and tissue injury (68). Lymphopenia, a hallmark of active SLE, reflects T cell exhaustion and immune dysregulation, and lymphocyte counts and ratios serve as markers of immune disturbances and autoantibody-driven inflammation (69). Platelet activation contributes to the endothelial damage and inflammation. Elevated platelet counts or activity indicates heightened inflammation and may be correlated with disease activity and organ damage (70). Thus, SII may act as a composite indicator of disease burden and immune imbalance, especially during flares.

In multiple cohorts, the SII was consistently correlated with global disease activity indices in SLE, particularly the SLE Disease Activity Index (SLEDAI or SLEDAI-2K). Akdogan et al. (71) reported a strong correlation between the SII and SLEDAI (r = 0.698, p = 0.01), with high discriminatory power for moderate-to-severe activity (AUC = 0.930, sensitivity 77%, specificity 76%). Predescu et al. (72) similarly identified the SII as a robust flare marker, with an AUC of 0.963 for severe flares. Baykal et al. (73) observed an elevated SII in pediatric patients with high disease activity, especially in ANA-positive cases.

SII may reflect organ involvement, particularly in renal disease. Ergun et al. (74) showed a higher SII in patients with lupus nephritis than in those without proteinuria (p = 0.012), with correlations between both proteinuria and SLEDAI. Yang et al. confirmed that the SII independently predicted lupus nephritis (AUC = 0.6775) and correlated with SLEDAI-2K (r = 0.24, p< 0.05) (75). However, Özdemir et al. found no significant difference in the SII between patients with and without nephritis (76).

Sahin et al. demonstrated that an elevated first-trimester SII in pregnant patients with SLE was associated with adverse outcomes, including preterm birth and fetal loss. The optimal threshold (1612.6) yielded a sensitivity of 73.3% and specificity of 71.4% (77).

Longitudinal data on treatment-related SII changes are limited but promising. Gambichler et al. (78) observed that clinical and serological improvements were accompanied by a decline in the SII and rising lymphocyte counts, suggesting their potential utility in therapy monitoring. However, these findings are exploratory and require further validation.

The SII offers a rapid, noninvasive measure of systemic inflammation and has demonstrated utility in autoimmune conditions. However, its nonspecific nature is a limitation of this study. Taha et al. (79) reported elevated SII levels in patients with SLE, RA, and AS. Moreover, its components may vary with physiological changes or treatments, which complicates its interpretation.

Predescu et al. (72) reported a strong discriminative capacity of the SII for severe SLE flares (AUC=0.963), which aligned with the findings of Akdogan et al. (AUC=0.930) (71). However, the implausible SII cutoff (877,002.19)—reflects likely computational/unit errors given the incongruence with hematologic parameters (mean platelets: 246.413 ± 118.145×10³/µL, neutrophils: 3.818 ± 1.381×10³/µL, lymphocytes 1.591 ± 0.707×10³/µL). Consequently, while the AUC validates the SII’s diagnostic potential, the cutoff was excluded from the synthesis to prevent misinterpretation. This underscores the importance of a rigorous methodology for threshold derivation for the clinical translation of biomarkers.

Despite these challenges, the SII may complement conventional markers, such as anti-dsDNA and complement levels, particularly where access to immunologic assays is limited. Future work should define disease-specific cutoffs, track longitudinal changes, and assess the role of the SII in multiparametric models integrating clinical, serological, and imaging data.

Systemic vasculitides, including antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), Behçet’s syndrome (BS), and Kawasaki disease (KD), are complex inflammatory conditions characterized by vascular inflammation and multisystem involvement (80–82). Accurate biomarkers are essential for evaluating disease activity, organ involvement, and treatment responses. In vasculitis, where disease activity and vascular injury are often difficult to assess, the SII may offer additional diagnostic and prognostic value.

A retrospective study of 190 Chinese patients with myeloperoxidase (MPO)-AAV found that the baseline SII was positively correlated with CRP and ESR, but not with the Birmingham Vasculitis Activity Score (BVAS). Interestingly, patients with higher SII values (≥2136.45) had a significantly lower risk of progression to end-stage renal disease (ESRD), suggesting a possible protective association (83).

Several studies have linked the SII to disease activity in BS. In a retrospective analysis, Tanacan et al. (84) reported a significantly higher SII in active-BS than in inactive-BS, with a proposed cutoff value of 552 × 10⁹. Similarly, Menteseoglu and Atakan (85) found that an elevated SII correlated with CRP level, ESR, NLR, and PLR, and was an independent predictor of active disease in regression analysis.

A large cohort study by Ulusoy et al. (86) showed a significantly higher SII in patients with BS and vascular involvement than in those with mucocutaneous or other phenotypes. The SII demonstrated a strong discriminatory capacity for vascular involvement (AUC = 0.87).

In KD, multiple studies have evaluated the role of the SII in predicting coronary artery lesions (CALs), with mixed results. Huang et al. (87) found a significant linear association between the SII and CALs at admission, with an AUC of 0.789.

In contrast, Yalcinkaya et al. (88) observed a lower SII in patients with KD and CALs and identified male sex, low prognostic nutritional index (PNI), and reduced SII as independent risk factors. Liu et al. (89) found that post-intravenous immunoglobulin (IVIG) SII levels were significantly higher in IVIG-resistant patients, although the baseline SII did not differ according to resistance status.

In addition to its role in disease activity, SII may help assess treatment response and prognosis. For MPO-AAV, Chen et al. (83) found that a higher baseline SII correlated with CRP level and ESR, but not BVAS, and was associated with improved renal survival and reduced ESRD risk (83).

In KD, an elevated baseline SII is associated with IVIG resistance. Yi et al. (90) reported an optimal cutoff of 2209.66 (AUC of 0.626) and identified the SII, SIRI, and PIV as independent predictors of non-responsiveness. Similarly, Liu et al. (89) observed a significantly higher post-treatment SII in IVIG-resistant patients (AUC = 0.706), indicating that the failure of the SII to decline may signal persistent inflammation and predict resistance.

Emerging data support the use of the SII across vasculitis subtypes. In AAV, elevated SII is correlated with inflammatory markers and predicts renal outcomes (83). In the BS, the SII distinguishes active from inactive disease (84, 85), correlates with inflammatory indices, and differentiates vascular from mucocutaneous forms with high accuracy (AUC of up to 0.87) (86). In KD, SII predicts CALs and IVIG resistance, reflecting disease severity and treatment response (87, 90).

Overall, the SII is a simple, accessible, and cost-effective index for evaluating inflammation and vascular involvement in vasculitis. However, disease-specific cutoffs and prospective validations are needed to refine their clinical utility alongside established biomarkers.