ABSTRACT

Objective:

Our objective was to assess the relationship between disease activity and the systemic immune-inflammation index [SII; (platelet count × neutrophil count / lymphocyte count)] in individuals with ankylosing spondylitis (AS).

Materials and Methods:

A total of 201 participants (130 AS patients and 71 healthy volunteers) aged 18-65 years were included in this single center cross-sectional study. Based on their ratings on the Bath Ankylosing Spondylitis Disease Activity index (BASDAI), patients with AS were split into two groups: remission (n=90, those with BASDAI <4) and active disease (n=40, those with BASDAI >4). The study employed Spearman correlation analysis to assess the relationship between SII and C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), BASDAI, Ankylosing Spondylitis Disease Activity score-ESR (ASDAS-ESR), and ASDAS-CRP. The effectiveness of SII and other measures in evaluating the disease activity in the active AS and remission AS groups was ascertained using receiver operating characteristic curve analysis.

Results:

SII values were significantly higher in the AS group than healthy controls, as well as in the active AS group than AS patients in remission (p<0.001 for each). SII values were positively correlated with CRP [Spearman correlation coefficient (rs): 0.384, p<0.001], ESR (rs: 0.243, p=0.005), BASDAI (rs: 0.668, p<0.001), ASDAS-ESR (rs: 0.619, p<0.001) and ASDAS-CRP (rs: 0.700, p<0.001) values. The optimal cut-off value for the determination of AS disease activity was found to be 530.22x109/L (area under the curve: 0.902, 95% confidence interval: 0.838-0.947, sensitivity: 72.50% and specificity: 92.22%).

Conclusion:

When assessing the activity of AS disease, SII appears to be a useful biomarker.

Keywords: Ankylosing spondylitis, C-reactive protein, neutrophil to lymphocyte ratio, systemic immune-inflammation index

Introduction

Ankylosing spondylitis (AS), a chronic inflammatory rheumatic disease, is characterized by inflammatory low back pain resulting from spondylitis and sacroiliitis. The condition typically peaks in the second and third decades of life (1). Apart from spinal involvement, other musculoskeletal findings (i.e., arthritis, enthesitis and dactylitis) and findings related to extra-articular involvement (i.e., anterior uveitis, psoriasis and inflammatory bowel disease) may also accompany the clinical picture (2). In the advanced stages of the disease, kyphosis and limited spine mobility may appear with the development and progression of syndesmophytes in the vertebrae (3). These conditions likely to occur in the course of the disease may limit physical functions and impair quality of life in AS patients (4). When monitoring AS patients, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) are commonly used to gauge the level of inflammation (5). Besides the conventional acute phase reactants, other markers calculated from complete blood count parameters such as neutrophil-to-lymphocyte ratio (NLR) and platelet (PLT)-to-lymphocyte ratio (PLR) have also been investigated in many studies (6-11).

The Ankylosing Spondylitis Disease Activity score-CRP (ASDAS-CRP), the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and the ASDAS-ESR are the current measures used to evaluate AS disease activity.

Systemic immune-inflammation index (SII), calculated from complete blood count parameters using a formula of “PLT x neutrophil count / lymphocyte count”, was firstly defined as a useful index in hepatocellular cancer patients (12). Later on, its potential utility has also been considered for other malignancies, ulcerative colitis, uveitis, Bell’s palsy, irritable bowel syndrome, hidradenitis suppurativa, psoriasis and obstructive sleep apnea syndrome (13-24). In the setting of rheumatic diseases, SII is suggested to be used as a novel index in assessment of disease activity in rheumatoid arthritis, Behçet’s disease, adult-onset Still’s disease and anti-neutrophil cytoplasmic antibody-associated vasculitis (25-28). Already there are 2 studies evaluating the SII in relation to disease activity in AS patients (29,30). In one of these studies, only 50 AS patients were evaluated (30). In the other study, correlation of SII with CRP, ESR and BASDAI was evaluated, correlation assessment was not performed with ASDAS (29).

Therefore, the purpose of our study was to assess the relationship in a larger group of AS patients between ASDAS and SII values in addition to ESR, CRP, and BASDAI.

Materials and Methods

This single center cross-sectional study included 130 patients (aged 18-65) who were being followed at rheumatology outpatient clinics of Bursa Uludağ University Faculty of Medicine, Department of Physical Medicine and Rehabilitation and who had been diagnosed with AS based on Modified New York criteria (31).

Patients with comorbid diseases such as hypertension, diabetes mellitus, coronary artery disease, metabolic syndrome, malignancy, infection, anemia, parathyroid diseases, thyroid dysfunction, chronic obstructive respiratory disease, obstructive sleep apnea syndrome, allergic rhinitis, asthma, active smoking and other inflammatory rheumatic diseases were excluded from the study. A total of 71 healthy volunteers with no pathological findings on physical examination and laboratory tests on their admission to outpatient clinics served as the control group. The study protocol was approved by the Bursa Uludağ University Faculty of Medicine Clinical Research Ethics Committee (approval date: February 23, 2022, decision no: 2022-4/25). Informed consent was obtained from all subjects in accordance with the Declaration of Helsinki. Data on patient demographics (age, gender), educational status, occupational status, disease duration, medical treatments, CRP and ESR levels, neutrophil, lymphocyte and PLT counts were recorded. SII, NLR and PLR values were calculated.

Disease activity was assessed with BASDAI, ASDAS-ESR and ASDAS-CRP scores. Based on exhaustion, spinal pain, joint pain/swelling, areas of localized soreness, morning stiffness length, and morning stiffness intensity, the 6-item BASDAI index is used to assess disease activity. Higher total scores indicate increased disease activity. The score ranges from 0 to 10 (32). BASDAI scores ≥4 denotes the active disease. Patients classified as being in remission were those with a BASDAI <4, and patients classified as having active disease were those with a BASDAI >4.

Statistical Analysis

The conformity of continuous variables to the normal distribution was examined using the Shapiro-Wilk test. Continuous variables were expressed using mean ± standard deviation or median (minimum:maximum) values; categorical variables were expressed as n (%). The Mann-Whitney U test and the independent samples t-test were used to compare the groups based on the findings of the normality test. Categorical variables were analyzed using the chi-square test. The correlation of SII values with CRP, ESR, BASDAI, ASDAS-ESR and ASDAS-CRP values were examined with Spearman correlation analysis. SPSS (Version 26.0. Armonk, NY: IBM Corp.) program was used for statistical analysis. Power analysis is calculated to be 99% and the effect size was 0.66. Type I error was accepted as 5% and p<0.05 was considered to be statistically significant.

Results

In total, 201 people were included in our study: 130 patients with AS diagnoses and 71 healthy controls. Age and gender differences between the AS group and the healthy control group were not statistically significant (p>0.05). When comparing the AS group to the healthy control group, the values of SII, neutrophil, PLT, and NLR were considerably greater (p<0.05). Regarding PLR and lymphocyte levels, there was no discernible difference between the two groups (p>0.05).

Demographic and clinical characteristics and laboratory results of all participants are summarized in Table 1.

Table 1

When AS patients were evaluated with respect to BASDAI score, 90 patients with a score <4 were considered in the remission group, and 40 patients with a score ≥4 were in the active group. There was no statistically significant difference between active AS and remission AS groups in terms of age, gender, disease duration, education level and occupational status (p>0.05). SII, neutrophil, lymphocyte, PLT, CRP, ESR, NLR, PLR, BASDAI, ASDAS-ESR and ASDAS-CRP values were significantly higher in the active AS group than in the AS in remission (p<0.05). The clinical and demographic characteristics and laboratory results of the active AS and the remission AS groups are summarized in Table 2.

Table 2

SII values were found to be positively correlated with CRP [Figure 1a: Spearman correlation coefficient (rs): 0.384, p<0.001], ESR (Figure 1b: rs: 0.243, p=0.005), BASDAI (Figure 1c: rs: 0.668, p<0.001), ASDAS-ESR (Figure 1d: rs: 0.619, p<0.001) and ASDAS-CRP (Figure 1e: rs: 0.700, p<0.001) values. Data on correlation analysis of SII values with ESR, CRP, BASDAI, ASDAS-ESR and ASDAS-CRP values are shown in Table 3 and Figure 1.

Figure 1

Table 3

Receiver operating characteristic (ROC) curve was used to evaluate disease activity in AS patients. Area under the ROC curve was found to be 0.902 for SII [95% confidence interval (CI): 0.838-0.947], 0.837 for NLR (95% CI: 0.762-0.896), 0.812 for PLR (95% CI: 0.734-0.875), 0.728 for ESR (95% CI: 0.643-0.802) and 0.732 for CRP (95% CI: 0.647-0.806). The optimal cut-off point for SII in evaluation of disease activity was found to be 530.22×10⁹/L (sensitivity: 72.50%, specificity: 92.22%). ROC curve analyses are shown in Table 4 and Figure 2.

Table 4

Figure 2

Discussion

In AS, similar to the other inflammatory rheumatic diseases, indicators are needed to determine and monitor disease activity. ESR, CRP, BASDAI, ASDAS-ESR and ASDAS-CRP are routinely used for this purpose in AS patients. In order to evaluate AS disease activity, studies have been conducted on new indicators that can be calculated from complete blood count parameters (6-11,29,30). In order to offer a new indicator, we studied SII and found that it is positively correlated with inflammation and disease activity in AS patients.

In the presence of inflammation, an increase in neutrophil and PLT counts and a decrease in lymphocyte counts are expected (33). The increase in neutrophil count in AS patients is suggested to be associated with an increase in the differentiation and maturation of hematopoietic progenitor cell through many cytokines, such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1, IL-6, IL-8 and granulocyte macrophage colony stimulating factor (6). Decrease in lymphocyte counts in AS patients is considered to occur as a result of apoptosis; and although the exact mechanism is not clear, the increase in PLT counts has been suggested to be mediated by factors such as thrombin, histamine, TNF-α and IL-12 (29). Given the association of inflammation with increase in neutrophil and PLT counts and decrease in lymphocyte counts, the NLR, PLR and SII values as calculated from neutrophil, lymphocyte and PLT values can also be expected to be high, in relation to inflammation, in AS patients.

While neutrophil and PLT values were found to be greater in AS patients compared to the healthy control group (p<0.001 for each), no significant difference was identified in lymphocyte values (p=0.336) in a study by Liang et al. (11). Regarding the values of lymphocytes, PLT, and neutrophils, our findings are consistent with this research. Liang et al. (11) also reported significantly higher PLR and NLR values in the AS group compared to the healthy control group (p values: p<0.001, p=0.006, respectively). In our results, NLR values were significantly higher (p=0.007) in the AS group compared to the healthy control group in line with the study by Liang et al. (11), however, no significant difference was found in terms of our PLR values (p=0.143). Also, while Liang et al. (11) reported that PLR values (p=0.045) but not NLR values (p=0.086) were significantly higher in patients with BASDAI ≥4 compared to those with BASDAI <4, our findings revealed that both PLR and NLR values (p<0.001 for each) were significantly higher in active AS group than in the remission AS group.

Hence, we obtained similar results with the study of Liang et al. (11) in terms of PLR but different results in terms of NLR.

In a study conducted in AS patients by Coşkun et al. (6), neutrophil, PLT and NLR values were reported to be significantly higher (p<0.001 for each) in the AS vs. control group, and our results are in line with this study. In terms of lymphocyte values, while Coşkun et al. (6) reported significantly lower lymphocyte counts in the AS group (p=0.012), our findings revealed no significant difference in terms of lymphocyte values.

Similar to our results, Gökmen et al. (10) reported significantly higher neutrophil and NLR values in AS patients vs. control group (p<0.001 for each), along with no significant difference between groups in terms of lymphocyte values (p=0.23).

In a study by Zeb et al. (7), on NLR and PLR values in AS patients and control subjects, NLR and PLR values were reported to be significantly higher in AS patients than in healthy controls, as well as in the active AS (BASDAI ≥4) vs. remission AS (BASDAI <4) group (p<0.01 for each). Our results support this study in terms of NLR values. When PLR values are taken into account, our investigation indicated that, in contrary to Zeb et al.’s (7) work, there was no significant difference (p=0.143) between the AS group and the control group. However, PLR values were considerably greater (p<0.001) in the active AS group compared to the remission AS group.

Seng et al.’s (8) investigation on axial spondyloarthritis patients revealed no discernible difference in NLR and PLR values (p=0.60 and p=0.40, respectively) between the groups with active and inactive illness. The neutrophil, lymphocyte, PLT, NLR and PLR values seem to vary across different studies, including the present study. Instead of using NLR and PLR values calculated from lymphocyte with neutrophil or PLT counts only, usage of SII value, obtained by a calculation including all of these parameters (neutrophil, lymphocyte and PLT), seems to be more valuable tool in determining the disease activity.

Two previous studies to date have investigated the SII, as a novel marker, in AS patients (29,30). One of them evaluated the indexes calculated from complete blood count parameters in inflammatory rheumatic diseases. The authors reported significantly higher SII levels in AS patients compared to healthy controls (p<0.001), and also in active AS patients compared to inactive AS patients (p=0.013). It was also noted that SII values were correlated with ESR (p=0.003), CRP (p=0.001) and ASDAS (p=0.013) values. In ROC curve analysis, the cut-off value for SII was reported to be 697.66 [area under the curve (AUC): 0.674, 95% CI: 0.504-0.845, sensitivity: 71.4%, specificity: 53.3%] (30). Our findings also revealed significantly higher SII values in AS patients vs. healthy controls, and in active AS group vs. remission AS group (p<0.001 for each), in addition to correlation of SII values with ESR (p=0.005), CRP (p<0.001), ASDAS-ESR (p<0.001) and ASDAS-CRP (p<0.001) values. We also found a correlation of SII with BASDAI (p<0.001), which was not evaluated in the above-mentioned study. In the ROC curve analysis, we determined the cut-off value for SII as 530.22×10⁹/L (AUC: 0.902, 95% CI: 0.838-0.947, sensitivity: 72.50%, specificity: 92.22%).

SII values were shown to be considerably higher in AS patients compared to the healthy control group and in the active AS group compared to the AS group in remission in Wu et al.’s (29) other AS study (p<0.001 for both). The data also showed a positive correlation between SII levels and CRP (rs=0.483, p<0.001), ESR (rs=0.374, p<0.001), and BASDAI (rs=0.667, p<0.001) values, as reported by the authors. The best indicator for assessing disease activity was found to be SII, with a reported cut-off value of 513.2 in ROC curve analysis (AUC: 0.877, 95% CI: 0.813-0.941, sensitivity: 86.84%, specificity: 83.33%). Our findings also revealed correlations between SII and ESR, CRP, BASDAI. We have also found correlation of SII with ASDAS-ESR and ASDAS-CRP, which was not assessed in the study by Wu et al. (29).

The single-center design and the relatively small sample sizes for the AS and healthy control groups are the two main limitations of our investigation. Owing to the cross-sectional design of our investigation, it was not possible to assess how patient-taken drugs affected SII levels. To ascertain whether SII is a useful tool for evaluating AS disease activity, more extensive prospective multi-center trials are required.

Conclusion

Our findings revealed that SII, which can easily be calculated from readily available complete blood count parameters routinely ordered in the follow up of AS patients, is a simple useful and efficient index in assessment of disease activity in AS patients, without causing any additional cost.

Ethics

Ethics Committee Approval: The study protocol was approved by the Bursa Uludağ University Faculty of Medicine Clinical Research Ethics Committee (approval date: February 23, 2022, decision no: 2022-4/25).

Informed Consent: Informed consent was obtained from all subjects in accordance with the Declaration of Helsinki.

Authorship Contributions

Surgical and Medical Practices: S.M., L.A., Concept: S.M., A.A., L.A., B.B.Y., Design: S.M., A.A., L.A., B.B.Y., Data Collection or Processing: S.M., A.A., L.A., B.B.Y., Analysis or Interpretation: S.M., A.A., L.A., B.B.Y., Literature Search: S.M., A.A., L.A., B.B.Y., Writing: S.M., L.A.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study received no financial support.

References

van den Berg R, Baraliakos X, Braun J, van der Heijde D. First update of the current evidence for the management of ankylosing spondylitis with non-pharmacological treatment and non-biologic drugs: a systematic literature review for the ASAS/EULAR management recommendations in ankylosing spondylitis. Rheumatology (Oxford) 2012;51:1388-96.

Stolwijk C, van Tubergen A, Castillo-Ortiz JD, Boonen A. Prevalence of extra-articular manifestations in patients with ankylosing spondylitis: a systematic review and meta-analysis. Ann Rheum Dis 2015;74:65-73.

van der Heijde D, Ramiro S, Landewé R, Baraliakos X, Van den Bosch F, Sepriano A, et al. 2016 update of the ASAS-EULAR management recommendations for axial spondyloarthritis. Ann Rheum Dis 2017;76:978-91.

van der Heijde D, Braun J, Deodhar A, Baraliakos X, Landewé R, Richards HB, et al. Modified stoke ankylosing spondylitis spinal score as an outcome measure to assess the impact of treatment on structural progression in ankylosing spondylitis. Rheumatology (Oxford) 2019;58:388-400.

Romero-Sánchez C, Robinson WH, Tomooka BH, Londoño J, Valle-Oñate R, Huang F, et al. Identification of acute phase reactants and cytokines useful for monitoring infliximab therapy in ankylosing spondylitis. Clin Rheumatol 2008;27:1429-35.

Coşkun BN, Öksüz MF, Ermurat S, Tufan AN, Oruçoğlu N, Doğan A, et al. Neutrophil lymphocyte ratio can be a valuable marker in defining disease activity in patients who have started anti-tumor necrosis factor (TNF) drugs for ankylosing spondylitis. Eur J Rheumatol 2014;1:101-5.

Zeb A, Khurshid S, Bano S, Rasheed U, Zammurrad S, Khan MS, et al. The role of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as markers of disease activity in ankylosing spondylitis. Cureus 2019;11:e6025.

Seng JJB, Kwan YH, Low LL, Thumboo J, Fong WSW. Role of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and mean platelet volume (MPV) in assessing disease control in Asian patients with axial spondyloarthritis. Biomarkers 2018;23:335-8.

Boyraz I, Koç B, Boyacı A, Tutoğlu A, Sarman H, Ozkan H. Ratio of neutrophil/lymphocyte and platelet/lymphocyte in patient with ankylosing spondylitis that are treating with anti-TNF. Int J Clin Exp Med 2014;7:2912-5.

Gökmen F, Akbal A, Reşorlu H, Gökmen E, Güven M, Aras AB, et al. Neutrophil-lymphocyte ratio connected to treatment options and inflammation markers of ankylosing spondylitis. J Clin Lab Anal 2015;29:294-8.

Liang T, Chen J, Xu G, Zhang Z, Xue J, Zeng H, et al. Platelet-to-lymphocyte ratio as an independent factor was associated with the severity of ankylosing spondylitis. Front Immunol 2021;12:760214.

Hu B, Yang XR, Xu Y, Sun YF, Sun C, Guo W, et al. Systemic immune-inflammation index predicts prognosis of patients after curative resection for hepatocellular carcinoma. Clin Cancer Res 2014;20:6212-22.

Liu J, Li S, Zhang S, Liu Y, Ma L, Zhu J, et al. Systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio can predict clinical outcomes in patients with metastatic non-small-cell lung cancer treated with nivolumab. J Clin Lab Anal 2019;33:e22964.

Jomrich G, Gruber ES, Winkler D, Hollenstein M, Gnant M, Sahora K, et al. Systemic immune-inflammation index (sii) predicts poor survival in pancreatic cancer patients undergoing resection. J Gastrointest Surg 2020;24:610-8.

Zhu M, Chen L, Kong X, Wang X, Fang Y, Li X, et al. The systemic inflammation response index as an independent predictor of survival in breast cancer patients: a retrospective study. Front Mol Biosci 2022;9:856064.

He K, Si L, Pan X, Sun L, Wang Y, Lu J, et al. Preoperative systemic immune-inflammation index (SII) as a superior predictor of long-term survival outcome in patients with stage I-II gastric cancer after radical surgery. Front Oncol 2022;12:829689.

Ramón-Rodríguez J, De-Armas-Conde N, Jaén-Torrejimeno I, Prada-Villaverde A, Rojas-Holguín A, López-Guerra D, et al. Prognostic value of pre-operative systemic immune-inflammation index and platelet to lymphocyte ratio in peritoneal carcinomatosis of ovarian origin. Surg Oncol 2022;42:101750.

Zhang MH, Wang H, Wang HG, Wen X, Yang XZ. Effective immune-inﬂammation index for ulcerative colitis and activity assessments. World J Clin Cases 2021;9:334-43.

Kurtul BE, Cakmak AI, Elbeyli A, Ozcan SC, Ozarslan Ozcan D, Kimyon G. Evaluation of systemic immune-inflammation index level as a novel marker for severity of noninfectious uveitis. Int Ophthalmol 2021;41:3615-22.

Kınar A, Ulu Ş, Bucak A, Kazan E. Can Systemic Immune-Inflammation Index (SII) be a prognostic factor of Bell’s palsy patients? Neurol Sci 2021;42:3197-201.

Güven İE, Başpınar B, Atalay R. Relationship between systemic immune-inflammation index and irritable bowel syndrome. Turk J Gastroenterol 2022;33:30-4.

Gambichler T, Hessam S, Cramer P, Abu Rached N, Bechara FG. Complete blood collection-based systemic inflammation biomarkers for patients with hidradenitis suppurativa. J Eur Acad Dermatol Venereol 2022;36:1593-6.

Dincer Rota D, Tanacan E. The utility of systemic-immune inflammation index for predicting the disease activation in patients with psoriasis. Int J Clin Pract 2021;75:e14101.

Topuz MF, Ture N, Akdag G, Arik O, Gulhan PY. The importance of systemic immune-inflammation index in obstructive sleep apnea syndrome. Eur Arch Otorhinolaryngol 2022;279:5033-8.

Choe JY, Kim SK. Association between hematological indicesand disease activity in patients with rheumatoid arthritis treated with janus kinase inhibitors for 24 weeks. Medicina (Kaunas) 2022;58:426.

Tanacan E, Dincer D, Erdogan FG, Gurler A. A cutoff value for the systemic immune-inflammation index in determining activity of Behçet disease. Clin Exp Dermatol 2021;46:286-91.

Kim JW, Jung JY, Suh CH, Kim HA. Systemic immune-inflammation index combined with ferritin can serve as a reliable assessment score for adult-onset Still’s disease. Clin Rheumatol 2021;40:661-8.

Kim Y, Choi H, Jung SM, Song JJ, Park YB, Lee SW. Systemic immune-inflammation index could estimate the cross-sectional high activity and the poor outcomes in immunosuppressive drug-naïve patients with antineutrophil cytoplasmic antibody-associated vasculitis. Nephrology (Carlton) 2019;24:711-7.

Wu J, Yan L, Chai K. Systemic immune-inflammation index is associated with disease activity in patients with ankylosing spondylitis. J Clin Lab Anal 2021;35:e23964.

Taha SI, Samaan SF, Ibrahim RA, Moustafa NM, El-Sehsah EM, Youssef MK. Can complete blood count picture tell us more about the activity of rheumatological diseases?. Clin Med Insights Arthritis Musculoskelet Disord 2022;15:11795441221089182.

Deodhar A. Axial spondyloarthritis criteria and modified NY criteria: issues and controversies. Clin Rheumatol 2014;33:741-7.

Akkoc Y, Karatepe AG, Akar S, Kirazli Y, Akkoc N. A Turkish version of the Bath Ankylosing Spondylitis Disease Activity Index: reliability and validity. Rheumatol Int 2005;25:280-4.

Doğan M, Boyacıoğlu M, Doğan AG. Evaluation of neutrophyl/lymphocyte ratio, platelet/lymphocyte ratio and mean platelet volume according to the disease activity index in patients of ankylosing spondylitis. J Heal Sci Med 2022;5:247-51.

Systemic Immune Inflammation Index in Ankylosing Spondylitis Patients