Analysis of the value of NLR, MLR and PLR levels in peripheral blood of patients with RRMS
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Abstract Background There is limited research on the relevance of neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and platelet-lymphocyte ratio (PLR) in patients diagnosed with relapse-remitting multiple sclerosis (RRMS). Objective The main objective of this study was to evaluate the significance of NLR, MLR, and PLR levels in the peripheral blood of patients diagnosed with RRMS. Methods A total of 109 patients with RRMS recruited from the Department of Neurology, the First Affiliated Hospital of Harbin Medical University from January 2018 to January 2024 were retrospectively analyzed, and 71 healthy population as controls (HC). Clinical data including age, sex, blood routine, serum uric acid (SUA),radiological investigations including magnetic resonance imaging (MRI) of brain and spinal cord were done(A standardized protocol of MRI comprising T2-weighted and T1-weighted gadolinium enhancing were performed using 3.0 Tesla superconducting MR imager)and Extended Disability Status Scale (EDSS) of all RRMS patients were collected. Results The levels of NLR, MLR and PLR were significantly higher in RRMS patients compared to the HC. RRMS patients with moderate-severe disability had higher NLR and MLR levels than those with mild disability. Logistic regression analysis showed that NLR was associated with disease disability (odds ratio(OR):1.470; confidence interval(CI):1.024–1.153; P:0.046). The cutoff value for the NLR to predict RRMS disability was 2.17.NLR was higher in RRMS patients with disease activity than in those without activity (p = 0.045), while SUA was lower in RRMS patients with disease activity than in those without activity (p = 0.033). Compared with HC,RRMS patients had lower SUA levels (p = 0.008). Additionally, SUA levels decreased with the increase of EDSS scores (P = 0.003), and NLR value was negatively correlated with SUA (p = 0.022). Conclusions The levels of NLR,MLR and PLR in peripheral blood of RRMS patients in the acute phase are higher than those of healthy people, and NLR has a certain predictive value for the severity of disability. Furthermore, we suggest that NLR and SUA are related to the disability and activity of RRMS, albeit exerting opposing effects on the disease.
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Analysis of the value of NLR, MLR and PLR levels in peripheral blood of patients with RRMS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of the value of NLR, MLR and PLR levels in peripheral blood of patients with RRMS Jiayun Ren, Weihua Zhang, Lamei Xue, Hongping Chen, Xinshu Du, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4428275/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background There is limited research on the relevance of neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and platelet-lymphocyte ratio (PLR) in patients diagnosed with relapse-remitting multiple sclerosis (RRMS). Objective The main objective of this study was to evaluate the significance of NLR, MLR, and PLR levels in the peripheral blood of patients diagnosed with RRMS. Methods A total of 109 patients with RRMS recruited from the Department of Neurology, the First Affiliated Hospital of Harbin Medical University from January 2018 to January 2024 were retrospectively analyzed, and 71 healthy population as controls (HC). Clinical data including age, sex, blood routine, serum uric acid (SUA),radiological investigations including magnetic resonance imaging (MRI) of brain and spinal cord were done(A standardized protocol of MRI comprising T2-weighted and T1-weighted gadolinium enhancing were performed using 3.0 Tesla superconducting MR imager)and Extended Disability Status Scale (EDSS) of all RRMS patients were collected. Results The levels of NLR, MLR and PLR were significantly higher in RRMS patients compared to the HC. RRMS patients with moderate-severe disability had higher NLR and MLR levels than those with mild disability. Logistic regression analysis showed that NLR was associated with disease disability (odds ratio(OR):1.470; confidence interval(CI):1.024–1.153; P:0.046). The cutoff value for the NLR to predict RRMS disability was 2.17.NLR was higher in RRMS patients with disease activity than in those without activity (p = 0.045), while SUA was lower in RRMS patients with disease activity than in those without activity (p = 0.033). Compared with HC,RRMS patients had lower SUA levels (p = 0.008). Additionally, SUA levels decreased with the increase of EDSS scores (P = 0.003), and NLR value was negatively correlated with SUA (p = 0.022). Conclusions The levels of NLR,MLR and PLR in peripheral blood of RRMS patients in the acute phase are higher than those of healthy people, and NLR has a certain predictive value for the severity of disability. Furthermore, we suggest that NLR and SUA are related to the disability and activity of RRMS, albeit exerting opposing effects on the disease. Relapsing-remitting multiple sclerosis Neutrophil-lymphocyte ratio Monocyte-lymphocyte ratio Platelet-lymphocyte ratio Serum uric acid Figures Figure 1 1.Introduction Multiple sclerosis (MS) is the most common inflammatory demyelinating autoimmune disease of the central nervous system (CNS) characterized by relapse and remission,and RRMS is the most common clinical type,accounting for 80%-85%[ 1 ]. The pathogenesis of the disease is thought to primarily involve the peripheral activation of Th1 lymphocytes,which migrate to the central nervous system and react with myelin autoantigens.Upon activation,these T cells recruit a variety of bone marrow cells,including monocytes/macrophages,to promote and carry out inflammatory responses,often leading to axonal transection and irreversible focal CNS damage[ 2 ].In addition to monocytes,neutrophils have also been found to play a role in the enhanced inflammatory response in MS[ 3 ].NLR,PLR,and MLR are cost-effective and readily available components of a standard complete blood count;They have gained increasing recognition as clinically relevant biomarkers of pathological inflammation in various medical disciplines (including oncology[ 4 – 6 ],metabolic[ 7 ],cardiovascular[ 8 ],and autoimmune diseases[ 9 ]).In the field of neurology,patients diagnosed with Neuromyelitis Optica Spectrum Disorders (NMOSD) exhibited significantly elevated levels of serum PLR,NLR,and MLR compared to healthy controls.Notably,PLR can serve as an independent marker for assessing disease severity in NMOSD patients[ 10 ].Furthermore,notable differences were observed in NLR,PLR,and MLR levels between adult patients who experienced convulsive status epilepticus after remission and healthy controls[ 11 ]. There has long been a search for an inflammatory marker that can predict disability and activity in MS.The identification of NLR,MLR,and PLR as biomarkers for various diseases could offer a more comprehensive assessment of systemic inflammation compared to neutrophils or lymphocytes alone.It is also important to search for biomarkers with high sensitivity and specificity to study the pathogenesis of RRMS and improve the diagnostic level.The main objective of this study was to assess the relevance of NLR,MLR,and PLR as markers of disability and activity in RRMS,and to explore the relationship between NLR,MLR, and PLR levels and SUA levels. 2.Materials and Methods 2.1. Study Design A total of 109 RRMS patients were recruited from to the Department of Neurology,the First Affiliated Hospital of Harbin Medical University from January 2018 to January 2024 were selected, while 71 healthy population were selected as HC. 2.2. Inclusion criteria (1)Patients aged ≥ 18 years and diagnosed as RRMS according to the McDonald criteria 2017[ 12 ].(2)Other diagnoses were excluded.(3)The patients were in the acute stage.(4)Complete clinical data. 2.3. Exclusion criteria (1)The patients were in remission.(2)Previous history of suspected demyelinating events.(3)Acute cerebrovascular disease.(4)Patients with severe liver and kidney diseases.(5)Patients with rheumatic immune diseases and infectious diseases.(6) Patients have had glucocorticoids or other immunosuppressants in the past 3 months,or have taken other medications that may affect levels of NLR,MLR,and PLR.(7)Patients with malignant tumors, pregnancy,or surgical history within the past three months.(8)Patients with hematological diseases or blood transfusion were also excluded from the study.(9)Patients with mental illness.(10)Incomplete clinical data and lack of key clinical data. 2.4. Controls HC matched for age and sex with RRMS were selected, exhibiting no symptoms or signs of CNS disease,as well as no evidence of systemic or metabolic disorders.Laboratory tests confirmed the absence of infection,chronic diseases,or inflammatory conditions. 2.5 Research methods All patients completed routine biochemical tests such as blood routine,including complete blood count,liver and kidney function tests,within 24 hours after admission, The EDSS was used to assess[ 15 ]the disability of the disease.The healthy control group did not receive any additional clinical treatment following blood collection.The age,gender,white blood cell (WBC) count,neutrophil (NE) count,lymphocyte (LY) count,monocyte (MO) count,eosinophil (EO),basophil (BA),red blood cell (RBC), hemoglobin (HB),platelet(PLT),eosinophil (EO),basophil (BA),SUA,and EDSS scores of all enrolled patients were collected.The NLR,MLR,and PLR of blood were manually derived by dividing the neutrophil count, monocyte count,and platelet count by the lymphocyte count,respectively.For patients who have completed the imaging examination,MRI results of the brain and spinal cord are also collected.The clinical data and laboratory examination data of RRMS patients and HC were compared. According to EDSS score,RRMS patients were divided into two groups:mild (EDSS score ≤ 3.5) and moderate-severe(EDSS score > 3.5),for statistical analysis[ 14 ].Disease activity was defined as the presence of clinical recurrence and/or gadolinium enhancement on T1WI or new/enlarged lesions on T2WI[ 15 ].Therefore,RRMS patients were divided into disease active group and without active group according to MRI results of RRMS patients,and the clinical data between the two groups were compared.According to NLR,MLR and PLR counts,the patients were further divided into high value group(> median) and low value group(≤ median),and the correlation between NLR, MLR and PLR and SUA levels was analyzed. 2.6 Statistical methods The statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 27.0 software.The measurement data conforming to the normal distribution were expressed in the form of "mean ± standard deviation", the measurement data not conforming to the normal distribution were expressed in the form of "median (25th percentile-75th percentile)",Count data were reported as frequencies.Univariable analysis was performed for comparison between patients and controls using student t-test or chi-square test as deemed appropriate.Multivariate logistic regression analysis was used to determine the important factors related to disease disability.Receiver operating characteristic curve (ROC) analysis was performed to evaluate the overall discriminatory performance of NLR in comparison with MLR and PLR as markers for RRMS disability. The cutoff values of NLR, MLR, and PLR with the greatest sensitivity and specificity were determined. For all statistical data, p-value ≤ 0.05 was considered significant. 3.Results 3.1 Differences in basic clinical data between RRMS patients and HC patients According to the results of statistical analysis,the levels of WBC, NE, NLR, MLR and PLR in RRMS patients were higher than those in HC,while the levels of LY and SUA in RRMS patients were lower than those in HC,and these differences were statistically significant (P < 0.05),as shown in Table 1 . Table 1 Differences in basic clinical data between RRMS patients and HC patients RRMS HC 统计值Z/X 2 P Age 37(29-47.5) 40.89 ± 9.76 -1.94 0.052 Gender male 35(32.1%) 18(25.4%) 0.945 0.331 female 74(67.9%) 53(74.6%) WBC(10 9 /L) 7.00(6.16–8.22) 6.49(5.13–7.67) -2.861 0.004 NE(10 9 /L) 4.62(3.80–5.73) 3.69 ± 0.92 -5.405 < 0.001 LY(10 9 /L) 1.83(1.55–2.15) 2.15(1.75–2.45) -3.577 < 0.001 MO(10 9 /L) 0.40(0.32–0.48) 0.42 ± 0.13 -0.307 0.758 EO(10 9 /L) 0.08(0.04–0.17) 0.09(0.05–0.12) -0.478 0.633 BA(10 9 /L) 0.03(0.02–0.04) 0.03(0.02–0.04) -1.024 0.306 RBC(10 12 /L) 4.61 ± 0.47 4.61(4.39–5.06) -1.692 0.091 HB(g/L) 139.65 ± 14.81 139.00(133.00-153.00) -0.975 0.330 PLT(10 9 /L) 262.89 ± 60.68 255.00(209.00-299.00) -0.379 0.705 NLR 2.51(2.01–3.21) 1.72 ± 0.40 -7.438 < 0.001 MLR 0.22(0.18–0.26) 0.19 ± 0.05 -3.057 0.002 PLR 143.37(113.61-171.69) 121.16(91.12-148.02) -3.487 < 0.001 SUA 290.05 ± 76.30 318.83 ± 60.97 -2.67 0.008 EDSS 2.00(2.00-3.25) - - - 3.2 Comparison of clinical data between mild and moderate-severe disability patients with RRMS Patients were divided into two groups according to EDSS score:mild (EDSS score ≤ 3.5) and moderate-severe (EDSS > 3.5).Univariate analysis showed that there were significant differences in NLR (P = 0.037) and MLR (P = 0.046) between patients with mild disability and patients with moderate-severe disability.In addition,the level of SUA in RRMS patients with mild disability was higher than that in RRMS patients with moderate-severe disability,and the difference was statistically significant. However,there were no significant differences in other indicators between the two groups (Table 2 ).Further multivariate binary Logistic regression analysis was used to assess the significant factors associated with disability,and the results showed that NLR (95% CI:1.024–1.153;0.046) had a certain correlation with EDSS score,and may be one of the risk factors for neurological deficits in RRMS patients (Table 3 ). Table 2 Comparison of clinical data between RRMS patients with mild and moderate-severe disability Mild Moderate-severe Statistics P-value n = 85 n = 24 (X 2 /T/Z) Age 36.91 ± 11.88 41.65 ± 12.79 -1.548 0.122 Gender male 29(34.1%) 5(21.7%) 0.714 0.398 female 56(65.9%) 18(78.3%) WBC(10 9 /L) 6.97(6.20–8.21) 7.77 ± 2.86 -0.380 0.704 NE(10 9 /L) 4.57(3.80–5.55) 5.07(3.76–6.32) -0.984 0.325 LY(10 9 /L) 1.83(1.53–2.26) 1.85(1.63–2.01) -0.720 0.471 MO(10 9 /L) 0.39(0.31–0.48) 0.44(0.35–0.64) -1.094 0.274 EO(10 9 /L) 0.08(0.04–0.14) 0.08(0.03–0.25) -0.418 0.676 BA(10 9 /L) 0.03(0.02–0.04) 0.03 ± 0.02 -0.426 0.670 RBC(10 12 /L) 4.56(4.37–5.03) 4.48 ± 0.43 1.474 0.466 HB(g/L) 140.71 ± 14.27 135.92 ± 16.35 1.405 0.454 PLT(10 9 /L) 259.04 ± 57.22 279.54 ± 71.31 -1.251 0.240 NLR 2.41(1.94–3.12) 2.76(2.31–3.88) -2.245 0.025 MLR 0.21(0.17–0.26) 0.23(0.19–0.32) -1.996 0.046 PLR 141.57 ± 39.55 154.35(121.66-195.26) -1.865 0.062 SUA 300.68 ± 77.28 250.09 ± 56.26 2.987 0.003 Table 3 Multivariate Logistic regression analysis of factors associated with RRMS disability OR 95% CI P-value NLR 1.470 1.024–1.153 0.046 MLR 2.529 1.006–2.178 0.365 3.3 Comparison of clinical data between active and Non-active patients with RRMS In this study,a total of 46 patients with RRMS completed the MRI.Among them,33 patients showed lesion enhancement,while 13 patients had no lesion enhancement.These patients were divided into two groups according to the presence or absence of lesion enhancement:disease activity group and non-activity group. The results showed that the levels of WBC,NE,HB and NLR in the disease activity group were higher than those in the non-activity group,and the difference was statistically significant (P < 0.05).The level of SUA in the disease activity group was lower than that in the non-activity group,and the difference was statistically significant (P = 0.033).For details,see Table 4 . Table 4 Comparison of clinical data between active and inactive patients with RRMS activity group Non-activity group Statistical values P-value (n = 33) (n = 13) (X 2 /T/Z) Age 37.48 ± 12.74 34.69 ± 14.31 0.647 0.398 Gender male 11(33.3%) 2(18.2%) 0.463 0.496 female 22(66.7%) 11(84.6%) WBC(10 9 /L) 7.53(6.39–8.74) 6.14 ± 1.37 -2.708 0.007 NE(10 9 /L) 5.06(4.34-6.00) 3.97 ± 1.15 -2.671 0.008 LY(10 9 /L) 1.87(1.49–2.07) 1.83 ± 0.43 -0.122 0.903 MO(10 9 /L) 0.40(0.35–0.49) 0.38 ± 0.12 -1.027 0.305 EO(10 9 /L) 0.08(0.04–0.13) 0.07(0.03–0.16) -0.110 0.912 BA(10 9 /L) 0.03(0.02–0.04) 0.03 ± 0.02 -0.261 0.794 RBC(10 12 /L) 4.63 ± 0.53 4.65 ± 0.35 -0.109 0.098 HB(g/L) 140.12 ± 13.24 138.00 ± 7.56 0.542 0.038 PLT(10 9 /L) 267.48 ± 62.36 260.23 ± 62.99 0.354 0.974 EDSS 2.00(1.50–3.50) 2.00(1.25–2.25) -1.708 0.205 NLR 2.89(2.20–3.31) 2.63 ± 1.05 -2.001 0.045 MLR 0.23(0.19–0.26) 0.22 ± 0.07 -0.917 0.359 PLR 146.89(118.22-167.89) 156.03 ± 30.82 -0.183 0.855 SUA 288.21 ± 70.83 341.94 ± 85.19 -2.198 0.033 3.4Diagnostic performance of NLR as a disability marker for RRMS ROC analysis was used to determine cutoff values,sensitivity, and specificity to best distinguish RRMS disability.AUC was used to evaluate the overall performance of NLR markers and compare them with MLR and PLR. the Area under the ROC curve of NLR,MLR and PLR for identifying neurological deficits in RRMS was 0.65 (95%CI:0.528–0.773,P < 0.05),respectively.P = 0.025),0.634(95%CI:0.504–0.763,P = 0.046),0.625(95%CI 0.501–0.749,P = 0.062),respectively.The optimal cut-off value of NLR was 2.17,and the sensitivity and specificity were 0.388 and 0.875, respectively.The AUC of NLR as a disability marker was 0.65,which was higher than that of MLR and PLR (Fig. 1 ). 3.5 Correlation between high value (> median) and low value (≤ median) groups and SUA levels According to the median of NLR,MLR and PLR,patients were divided into high NLR group (NLR > 2.51) and low NLR group (NLR ≤ 2.51),high MLR group (MLR > 0.22) and low MLR group (MLR ≤ 0.22),and high PLR group (PLR > 288.6) and low PLR group (PLR ≤ 288.6).The results showed that the SUA level of the high NLR group was significantly lower than that of the low NLR group,and the difference was statistically significant (P = 0.022).However,there was no significant difference between the high MLR group and the low MLR group (P = 0.235).Similarly, no significant difference was found between the high PLR group and the low PLR group (P = 0.366).For details,see Table 5 , 6 , 7 . Table 5 Comparison of high NLR group and low NLR group with SUA levels High NLR Low NLR Statistical values(T) P-value n = 46 n = 63 SUA 270.59 ± 80.38 304.26 ± 70.46 2.322 0.022 Table 6 Comparison of high MLR group and low MLR group with SUA levels High MLR Low MLR Statistical values(T) P-value n = 51 n = 58 SUA 280.77 ± 79.22 298.21 ± 73.34 1.193 0.235 Table 7 Comparison of high PLR group and low PLR group with SUA levels High PLR Low PLR Statistical values(T) P-value n = 50 n = 59 SUA 282.84 ± 80.99 296.17 ± 70.47 0.908 0.366 4.Discussion Multiple sclerosis (MS),a chronic inflammatory demyelinating disease, is the disease of the CNS most often associated with disability in young adults[ 16 ].This study proved that there was a statistical difference in NLR between RRMS patients in acute stage and healthy control group,which was similar to the results of Farhmi et al[ 17 ].MLR and PLR levels in RRMS patients in acute stage in this study were also higher than those in healthy control group,showing a statistical difference.It was further confirmed that MS is a central nervous system disease involving a variety of inflammatory factors.The counts of neutrophils,lymphocytes,monocytes and platelets are closely related to inflammatory response and immune status of the body,and the integration of NLR,PLR and MLR as four indicators can more sensitivities reflect the inflammatory status of the body.Naegele et al[ 18 ].demonstrated that the increase in neutrophil count in RRMS patients is most likely due to a decrease in apoptosis,and that neutrophils have an altered cell surface expression of certain proteins,which may enhance recruitment to sites of inflammation. Our results showed that,in terms of disease disability,EDSS scores of mild disabled RRMS patients were statistically different from those of moderate-severe disabled RRMS patients. In multivariate logistic regression analysis,there was a significant correlation between NLR and higher disability scores. According to the differentiation performance shown by AUC,as a marker of disability,the AUC of NLR is 0.65.NLR has a certain predictive value for the severity of disability,and its sensitivity and specificity are 0.388 and 0.875,respectively.Farhmi et al[ 17 ].'s study also supports that NLR is a risk factor for moderate and severe neurological impairment in MS.Hemond et al[ 19 ].found that in MS patients, higher NLR and MLR were significantly correlated with the increase of EDSS score,which was different from the results in this study that MLR was not significantly correlated with EDSS score in multivariate logistic regression analysis.However,Bisgaard et al [ 20 ]. found that NLR had no significant value in predicting disease disability.In terms of disease activity,RRMS patients with disease activity had higher levels of NLR than RRMS patients without disease activity,and NLR was associated with RRMS activity, a result consistent with the findings of D'Amico et al[ 21 ].The association of NLR with neuroinflammation related disability could be attributable to neutrophils might cause tissue injury through enhanced degranulation,oxidative burst and release of neutrophil extracellular traps[ 18 ].Neutrophils could enhance T-cell activation,releasing proinflammatory cytokines,reactive oxidative species and proinflammatory enzymes contributing to parenchymal brain inflammation and impair the blood brain barrier[ 22 ]. In addition,our results showed a negative correlation between NLR values and SUA levels, so that SUA levels decreased as NLR levels increased during the acute phase of the disease.We also observed an inverse correlation between SUA levels and EDSS values.The SUA levels of RRMS patients with disease activity were significantly lower than those of RRMS patients without disease activity,and SUA was significantly negatively correlated with RRMS activity.The results of a study, in which more than 20 million patient records were statistically evaluated,showed that hyperuricemia protects against MS[ 23 ],and our results also demonstrate that SUA is protective against the disease,possibly because SUA is a natural scavenger of peroxynitrite,a toxic product of nitric oxide and superoxide,It induces inflammation, demyelination and axonal damage in the pathogenesis of MS[ 24 ]. 5.Conclusion The levels of NLR,MLR and PLR in peripheral blood of patients with RRMS in the acute phase are higher than those of healthy people.The NLR in peripheral blood of patients with RRMS in the acute phase has a certain predictive value for the severity of disability,and emphasizing the role of NLR in the diagnosis may help doctors predict the severity of patients.We conclude that NLR and SUA are associated with RRMS disability and activity, and that they have opposite effects.Our findings seem to suggest that evaluation of NLR values together with SUA values may be more effective in assessing disability as well as mobility in MS patients than evaluation of these parameters alone.However,due to the limitation of objective conditions,this study was a single-center open study with a small sample size, and there may be a certain selection bias.Therefore,the conclusions of this paper still need to be verified by multi-center and large-sample studies. Declarations Author contributions RJY, Study design,data collection and curation, conceptualization,writing draft,prepared the final manuscript, and submission.ZWH, XLM, DXS,YZZ,collected data/investigation and participated in writing the manuscript.CHP contributed to study conceptualization.LGZ and ZD revised the eventual manuscript.All authors have read and approved this manuscript. Data availability This data set may be available from the corresponding author on reasonable request. Ethics approval and consent to participate The Institutional Review Board of the First Affiliated Hospital of Harbin Medical University examined and authorized the studies involving human subjects. Furthermore, informed consent was not required, according to the Institutional Review No.2021JS34（Research 2019118) Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to reasons of patient confidentiality; this dataset may be available from the corresponding author on reasonable request. Declaration of Competing Interest The authors declare that they have no conflict of interests. References Bisgaard AK, Pihl-Jensen G. Frederiksen JL.The neutrophil-to-lymphocyte ratio as disease activity marker in multiple sclerosis and optic neuritis. Mult Scler Relat Disord. 2017;18:213–7. Hemmer B. Kerschensteiner M,Korn T.Role of the innate and adaptiveimmune responses in the course of multiple sclerosis. Lancet Neurol. 2015,;14(4):406–19. ,. Zostawa J, Adamczyk J, Sowa P. et al.The infl uence of sodium on Pathophysiology of multiple sclerosis.Neurol Sci,2017,38(3):389–98. Ocana A, Nieto-Jiménez C. Pandiella A,Templeton AJ.Neutrophils in cancer:prognostic role and therapeutic strategies. Mol Cancer. 2017,;16(1):137. ,. Nishijima TF. 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CLIN IMMUNOL. 2016;189:23–8. 10.1016/j.clim.2016.06.017 . Staub M. Uric acid as a scavenger in oxidative stress. Orv Hetil. 1999;140:275–9. Toncev G, Milicic B,Toncev S. Serum uric acid levels in multiple sclerosis patients correlate with activity of disease and blood-brain barrier dysfunction. Eur J Neurol. 2002;;9(3):221–6. . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4428275","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308262331,"identity":"1332057f-c234-4fbb-9971-db112ce0c9b3","order_by":0,"name":"Jiayun Ren","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiayun","middleName":"","lastName":"Ren","suffix":""},{"id":308262332,"identity":"456b43cf-9507-4943-900d-8cd06b1c3de8","order_by":1,"name":"Weihua Zhang","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weihua","middleName":"","lastName":"Zhang","suffix":""},{"id":308262333,"identity":"2103af4d-7bc7-436a-a1d2-593db7423447","order_by":2,"name":"Lamei Xue","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lamei","middleName":"","lastName":"Xue","suffix":""},{"id":308262334,"identity":"fb8f8176-ef07-4698-bc2e-67f5c1da12c5","order_by":3,"name":"Hongping Chen","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongping","middleName":"","lastName":"Chen","suffix":""},{"id":308262335,"identity":"85dec1fc-6fc6-404a-97c9-507ba5550c50","order_by":4,"name":"Xinshu Du","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xinshu","middleName":"","lastName":"Du","suffix":""},{"id":308262336,"identity":"5fef5871-2326-4c73-bf5d-0ec8e3db3e4c","order_by":5,"name":"Zizhe Yu","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zizhe","middleName":"","lastName":"Yu","suffix":""},{"id":308262337,"identity":"b58dead8-c9ac-442e-8380-1166d6684456","order_by":6,"name":"Di Zhong","email":"","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Di","middleName":"","lastName":"Zhong","suffix":""},{"id":308262338,"identity":"c009ad22-af1c-4500-a104-4153df361c2e","order_by":7,"name":"Guozhong Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACPgYGNiCSkONnbz5w4MMPIrSwQZCFsWTPscSDM3uI11KRuGFGjvFhDjZitPAvf/aYp0wicQNDzofDDDwM8vxiBwhokXiQbsxzTsJ4O8PZDYcLLBgMZ85OIKTlwDFp3jYJ2Z2NvRsOz+BhSDC4TVDLwTaQFsYNh3keHOZhI0YLfzMbSIvihmM8DERqkWBjk5wD9ItkD5sBMJAlCPuFn//4M4k3ZXVy/PKPH3/48MNGnl+agBYGiQQGJh4kLgHlYGsOMDASk0xGwSgYBaNgBAMAnbVDNLnkX+MAAAAASUVORK5CYII=","orcid":"","institution":"the First Affiliated Hospital of Harbin Medical University","correspondingAuthor":true,"prefix":"","firstName":"Guozhong","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-05-16 04:05:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4428275/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4428275/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58155042,"identity":"eda7db77-61af-438b-9c52-f58254ecbc48","added_by":"auto","created_at":"2024-06-11 20:42:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88271,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4428275/v1/06a8e0a9899da3c6e0faf08f.png"},{"id":69862433,"identity":"f4b4a02c-e0f2-4ed1-a647-76ba53ec75b0","added_by":"auto","created_at":"2024-11-26 06:02:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":803968,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4428275/v1/592daca0-cb51-44f1-bcc9-fe7c426c67e5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of the value of NLR, MLR and PLR levels in peripheral blood of patients with RRMS","fulltext":[{"header":"1.Introduction","content":"\u003cp\u003eMultiple sclerosis (MS) is the most common inflammatory demyelinating autoimmune disease of the central nervous system (CNS) characterized by relapse and remission,and RRMS is the most common clinical type,accounting for 80%-85%[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]. The pathogenesis of the disease is thought to primarily involve the peripheral activation of Th1 lymphocytes,which migrate to the central nervous system and react with myelin autoantigens.Upon activation,these T cells recruit a variety of bone marrow cells,including monocytes/macrophages,to promote and carry out inflammatory responses,often leading to axonal transection and irreversible focal CNS damage[\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e].In addition to monocytes,neutrophils have also been found to play a role in the enhanced inflammatory response in MS[\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e].NLR,PLR,and MLR are cost-effective and readily available components of a standard complete blood count;They have gained increasing recognition as clinically relevant biomarkers of pathological inflammation in various medical disciplines (including oncology[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e],metabolic[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e],cardiovascular[\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e],and autoimmune diseases[\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]).In the field of neurology,patients diagnosed with Neuromyelitis Optica Spectrum Disorders (NMOSD) exhibited significantly elevated levels of serum PLR,NLR,and MLR compared to healthy controls.Notably,PLR can serve as an independent marker for assessing disease severity in NMOSD patients[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e].Furthermore,notable differences were observed in NLR,PLR,and MLR levels between adult patients who experienced convulsive status epilepticus after remission and healthy controls[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThere has long been a search for an inflammatory marker that can predict disability and activity in MS.The identification of NLR,MLR,and PLR as biomarkers for various diseases could offer a more comprehensive assessment of systemic inflammation compared to neutrophils or lymphocytes alone.It is also important to search for biomarkers with high sensitivity and specificity to study the pathogenesis of RRMS and improve the diagnostic level.The main objective of this study was to assess the relevance of NLR,MLR,and PLR as markers of disability and activity in RRMS,and to explore the relationship between NLR,MLR, and PLR levels and SUA levels.\u003c/p\u003e"},{"header":"2.Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design\u003c/h2\u003e \u003cp\u003eA total of 109 RRMS patients were recruited from to the Department of Neurology,the First Affiliated Hospital of Harbin Medical University from January 2018 to January 2024 were selected, while 71 healthy population were selected as HC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Inclusion criteria\u003c/h2\u003e \u003cp\u003e(1)Patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years and diagnosed as RRMS according to the McDonald criteria 2017[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].(2)Other diagnoses were excluded.(3)The patients were in the acute stage.(4)Complete clinical data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Exclusion criteria\u003c/h2\u003e \u003cp\u003e(1)The patients were in remission.(2)Previous history of suspected demyelinating events.(3)Acute cerebrovascular disease.(4)Patients with severe liver and kidney diseases.(5)Patients with rheumatic immune diseases and infectious diseases.(6) Patients have had glucocorticoids or other immunosuppressants in the past 3 months,or have taken other medications that may affect levels of NLR,MLR,and PLR.(7)Patients with malignant tumors, pregnancy,or surgical history within the past three months.(8)Patients with hematological diseases or blood transfusion were also excluded from the study.(9)Patients with mental illness.(10)Incomplete clinical data and lack of key clinical data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Controls\u003c/h2\u003e \u003cp\u003eHC matched for age and sex with RRMS were selected, exhibiting no symptoms or signs of CNS disease,as well as no evidence of systemic or metabolic disorders.Laboratory tests confirmed the absence of infection,chronic diseases,or inflammatory conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Research methods\u003c/h2\u003e \u003cp\u003eAll patients completed routine biochemical tests such as blood routine,including complete blood count,liver and kidney function tests,within 24 hours after admission, The EDSS was used to assess[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]the disability of the disease.The healthy control group did not receive any additional clinical treatment following blood collection.The age,gender,white blood cell (WBC) count,neutrophil (NE) count,lymphocyte (LY) count,monocyte (MO) count,eosinophil (EO),basophil (BA),red blood cell (RBC), hemoglobin (HB),platelet(PLT),eosinophil (EO),basophil (BA),SUA,and EDSS scores of all enrolled patients were collected.The NLR,MLR,and PLR of blood were manually derived by dividing the neutrophil count, monocyte count,and platelet count by the lymphocyte count,respectively.For patients who have completed the imaging examination,MRI results of the brain and spinal cord are also collected.The clinical data and laboratory examination data of RRMS patients and HC were compared. According to EDSS score,RRMS patients were divided into two groups:mild (EDSS score\u0026thinsp;\u0026le;\u0026thinsp;3.5) and moderate-severe(EDSS score\u0026thinsp;\u0026gt;\u0026thinsp;3.5),for statistical analysis[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].Disease activity was defined as the presence of clinical recurrence and/or gadolinium enhancement on T1WI or new/enlarged lesions on T2WI[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].Therefore,RRMS patients were divided into disease active group and without active group according to MRI results of RRMS patients,and the clinical data between the two groups were compared.According to NLR,MLR and PLR counts,the patients were further divided into high value group(\u0026gt;\u0026thinsp;median) and low value group(\u0026le;\u0026thinsp;median),and the correlation between NLR, MLR and PLR and SUA levels was analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical methods\u003c/h2\u003e \u003cp\u003eThe statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 27.0 software.The measurement data conforming to the normal distribution were expressed in the form of \"mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation\", the measurement data not conforming to the normal distribution were expressed in the form of \"median (25th percentile-75th percentile)\",Count data were reported as frequencies.Univariable analysis was performed for comparison between patients and controls using student t-test or chi-square test as deemed appropriate.Multivariate logistic regression analysis was used to determine the important factors related to disease disability.Receiver operating characteristic curve (ROC) analysis was performed to evaluate the overall discriminatory performance of NLR in comparison with MLR and PLR as markers for RRMS disability. The cutoff values of NLR, MLR, and PLR with the greatest sensitivity and specificity were determined. For all statistical data, p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3.Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Differences in basic clinical data between RRMS patients and HC patients\u003c/h2\u003e \u003cp\u003eAccording to the results of statistical analysis,the levels of WBC, NE, NLR, MLR and PLR in RRMS patients were higher than those in HC,while the levels of LY and SUA in RRMS patients were lower than those in HC,and these differences were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05),as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in basic clinical data between RRMS patients and HC patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRRMS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e统计值Z/X\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(29-47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.89\u0026thinsp;\u0026plusmn;\u0026thinsp;9.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35(32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74(67.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(74.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.00(6.16\u0026ndash;8.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.49(5.13\u0026ndash;7.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNE(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.62(3.80\u0026ndash;5.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLY(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.83(1.55\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.15(1.75\u0026ndash;2.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMO(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.40(0.32\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEO(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08(0.04\u0026ndash;0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09(0.05\u0026ndash;0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBA(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03(0.02\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03(0.02\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC(10 \u003csup\u003e12\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.61(4.39\u0026ndash;5.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139.65\u0026thinsp;\u0026plusmn;\u0026thinsp;14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139.00(133.00-153.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262.89\u0026thinsp;\u0026plusmn;\u0026thinsp;60.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e255.00(209.00-299.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.51(2.01\u0026ndash;3.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22(0.18\u0026ndash;0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143.37(113.61-171.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121.16(91.12-148.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290.05\u0026thinsp;\u0026plusmn;\u0026thinsp;76.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e318.83\u0026thinsp;\u0026plusmn;\u0026thinsp;60.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEDSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00(2.00-3.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparison of clinical data between mild and moderate-severe disability patients with RRMS\u003c/h2\u003e \u003cp\u003ePatients were divided into two groups according to EDSS score:mild (EDSS score\u0026thinsp;\u0026le;\u0026thinsp;3.5) and moderate-severe (EDSS\u0026thinsp;\u0026gt;\u0026thinsp;3.5).Univariate analysis showed that there were significant differences in NLR (P\u0026thinsp;=\u0026thinsp;0.037) and MLR (P\u0026thinsp;=\u0026thinsp;0.046) between patients with mild disability and patients with moderate-severe disability.In addition,the level of SUA in RRMS patients with mild disability was higher than that in RRMS patients with moderate-severe disability,and the difference was statistically significant. However,there were no significant differences in other indicators between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).Further multivariate binary Logistic regression analysis was used to assess the significant factors associated with disability,and the results showed that NLR (95% CI:1.024\u0026ndash;1.153;0.046) had a certain correlation with EDSS score,and may be one of the risk factors for neurological deficits in RRMS patients (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical data between RRMS patients with mild and moderate-severe disability\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate-severe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;85\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;24\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(X\u003csup\u003e2\u003c/sup\u003e /T/Z)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.91\u0026thinsp;\u0026plusmn;\u0026thinsp;11.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.65\u0026thinsp;\u0026plusmn;\u0026thinsp;12.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29(34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(21.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56(65.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(78.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.97(6.20\u0026ndash;8.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.77\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNE(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.57(3.80\u0026ndash;5.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.07(3.76\u0026ndash;6.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLY(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.83(1.53\u0026ndash;2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.85(1.63\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMO(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39(0.31\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44(0.35\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEO(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08(0.04\u0026ndash;0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08(0.03\u0026ndash;0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBA(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03(0.02\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC(10 \u003csup\u003e12\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.56(4.37\u0026ndash;5.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140.71\u0026thinsp;\u0026plusmn;\u0026thinsp;14.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.92\u0026thinsp;\u0026plusmn;\u0026thinsp;16.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e259.04\u0026thinsp;\u0026plusmn;\u0026thinsp;57.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e279.54\u0026thinsp;\u0026plusmn;\u0026thinsp;71.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.41(1.94\u0026ndash;3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76(2.31\u0026ndash;3.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21(0.17\u0026ndash;0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23(0.19\u0026ndash;0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141.57\u0026thinsp;\u0026plusmn;\u0026thinsp;39.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154.35(121.66-195.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300.68\u0026thinsp;\u0026plusmn;\u0026thinsp;77.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250.09\u0026thinsp;\u0026plusmn;\u0026thinsp;56.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate Logistic regression analysis of factors associated with RRMS disability\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.024\u0026ndash;1.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.006\u0026ndash;2.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Comparison of clinical data between active and Non-active patients with RRMS\u003c/h2\u003e \u003cp\u003eIn this study,a total of 46 patients with RRMS completed the MRI.Among them,33 patients showed lesion enhancement,while 13 patients had no lesion enhancement.These patients were divided into two groups according to the presence or absence of lesion enhancement:disease activity group and non-activity group. The results showed that the levels of WBC,NE,HB and NLR in the disease activity group were higher than those in the non-activity group,and the difference was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).The level of SUA in the disease activity group was lower than that in the non-activity group,and the difference was statistically significant (P\u0026thinsp;=\u0026thinsp;0.033).For details,see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical data between active and inactive patients with RRMS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eactivity group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-activity group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatistical values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(X\u003csup\u003e2\u003c/sup\u003e/T/Z)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.48\u0026thinsp;\u0026plusmn;\u0026thinsp;12.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.69\u0026thinsp;\u0026plusmn;\u0026thinsp;14.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(84.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.53(6.39\u0026ndash;8.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNE(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.06(4.34-6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLY(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.87(1.49\u0026ndash;2.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMO(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.40(0.35\u0026ndash;0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEO(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08(0.04\u0026ndash;0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07(0.03\u0026ndash;0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBA(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03(0.02\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC(10 \u003csup\u003e12\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140.12\u0026thinsp;\u0026plusmn;\u0026thinsp;13.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT(10 \u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e267.48\u0026thinsp;\u0026plusmn;\u0026thinsp;62.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e260.23\u0026thinsp;\u0026plusmn;\u0026thinsp;62.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEDSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00(1.50\u0026ndash;3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.00(1.25\u0026ndash;2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.89(2.20\u0026ndash;3.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23(0.19\u0026ndash;0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146.89(118.22-167.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156.03\u0026thinsp;\u0026plusmn;\u0026thinsp;30.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e288.21\u0026thinsp;\u0026plusmn;\u0026thinsp;70.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e341.94\u0026thinsp;\u0026plusmn;\u0026thinsp;85.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4Diagnostic performance of NLR as a disability marker for RRMS\u003c/h2\u003e \u003cp\u003eROC analysis was used to determine cutoff values,sensitivity, and specificity to best distinguish RRMS disability.AUC was used to evaluate the overall performance of NLR markers and compare them with MLR and PLR. the Area under the ROC curve of NLR,MLR and PLR for identifying neurological deficits in RRMS was 0.65 (95%CI:0.528\u0026ndash;0.773,P\u0026thinsp;\u0026lt;\u0026thinsp;0.05),respectively.P\u0026thinsp;=\u0026thinsp;0.025),0.634(95%CI:0.504\u0026ndash;0.763,P\u0026thinsp;=\u0026thinsp;0.046),0.625(95%CI 0.501\u0026ndash;0.749,P\u0026thinsp;=\u0026thinsp;0.062),respectively.The optimal cut-off value of NLR was 2.17,and the sensitivity and specificity were 0.388 and 0.875, respectively.The AUC of NLR as a disability marker was 0.65,which was higher than that of MLR and PLR (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Correlation between high value (\u0026gt;\u0026thinsp;median) and low value (\u0026le;\u0026thinsp;median) groups and SUA levels\u003c/h2\u003e \u003cp\u003eAccording to the median of NLR,MLR and PLR,patients were divided into high NLR group (NLR\u0026thinsp;\u0026gt;\u0026thinsp;2.51) and low NLR group (NLR\u0026thinsp;\u0026le;\u0026thinsp;2.51),high MLR group (MLR\u0026thinsp;\u0026gt;\u0026thinsp;0.22) and low MLR group (MLR\u0026thinsp;\u0026le;\u0026thinsp;0.22),and high PLR group (PLR\u0026thinsp;\u0026gt;\u0026thinsp;288.6) and low PLR group (PLR\u0026thinsp;\u0026le;\u0026thinsp;288.6).The results showed that the SUA level of the high NLR group was significantly lower than that of the low NLR group,and the difference was statistically significant (P\u0026thinsp;=\u0026thinsp;0.022).However,there was no significant difference between the high MLR group and the low MLR group (P\u0026thinsp;=\u0026thinsp;0.235).Similarly, no significant difference was found between the high PLR group and the low PLR group (P\u0026thinsp;=\u0026thinsp;0.366).For details,see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e,\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e,\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of high NLR group and low NLR group with SUA levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh NLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow NLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistical values(T)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;46\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;63\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e270.59\u0026thinsp;\u0026plusmn;\u0026thinsp;80.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e304.26\u0026thinsp;\u0026plusmn;\u0026thinsp;70.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of high MLR group and low MLR group with SUA levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh MLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow MLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistical values(T)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;51\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;58\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e280.77\u0026thinsp;\u0026plusmn;\u0026thinsp;79.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e298.21\u0026thinsp;\u0026plusmn;\u0026thinsp;73.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of high PLR group and low PLR group with SUA levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh PLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow PLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistical values(T)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;59\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e282.84\u0026thinsp;\u0026plusmn;\u0026thinsp;80.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e296.17\u0026thinsp;\u0026plusmn;\u0026thinsp;70.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4.Discussion","content":"\u003cp\u003eMultiple sclerosis (MS),a chronic inflammatory demyelinating disease, is the disease of the CNS most often associated with disability in young adults[\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e].This study proved that there was a statistical difference in NLR between RRMS patients in acute stage and healthy control group,which was similar to the results of Farhmi et al[\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].MLR and PLR levels in RRMS patients in acute stage in this study were also higher than those in healthy control group,showing a statistical difference.It was further confirmed that MS is a central nervous system disease involving a variety of inflammatory factors.The counts of neutrophils,lymphocytes,monocytes and platelets are closely related to inflammatory response and immune status of the body,and the integration of NLR,PLR and MLR as four indicators can more sensitivities reflect the inflammatory status of the body.Naegele et al[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].demonstrated that the increase in neutrophil count in RRMS patients is most likely due to a decrease in apoptosis,and that neutrophils have an altered cell surface expression of certain proteins,which may enhance recruitment to sites of inflammation.\u003c/p\u003e\n\u003cp\u003eOur results showed that,in terms of disease disability,EDSS scores of mild disabled RRMS patients were statistically different from those of moderate-severe disabled RRMS patients. In multivariate logistic regression analysis,there was a significant correlation between NLR and higher disability scores. According to the differentiation performance shown by AUC,as a marker of disability,the AUC of NLR is 0.65.NLR has a certain predictive value for the severity of disability,and its sensitivity and specificity are 0.388 and 0.875,respectively.Farhmi et al[\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].\u0026apos;s study also supports that NLR is a risk factor for moderate and severe neurological impairment in MS.Hemond et al[\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e].found that in MS patients, higher NLR and MLR were significantly correlated with the increase of EDSS score,which was different from the results in this study that MLR was not significantly correlated with EDSS score in multivariate logistic regression analysis.However,Bisgaard et al [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. found that NLR had no significant value in predicting disease disability.In terms of disease activity,RRMS patients with disease activity had higher levels of NLR than RRMS patients without disease activity,and NLR was associated with RRMS activity, a result consistent with the findings of D\u0026apos;Amico et al[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e].The association of NLR with neuroinflammation related disability could be attributable to neutrophils might cause tissue injury through enhanced degranulation,oxidative burst and release of neutrophil extracellular traps[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].Neutrophils could enhance T-cell activation,releasing proinflammatory cytokines,reactive oxidative species and proinflammatory enzymes contributing to parenchymal brain inflammation and impair the blood brain barrier[\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eIn addition,our results showed a negative correlation between NLR values and SUA levels, so that SUA levels decreased as NLR levels increased during the acute phase of the disease.We also observed an inverse correlation between SUA levels and EDSS values.The SUA levels of RRMS patients with disease activity were significantly lower than those of RRMS patients without disease activity,and SUA was significantly negatively correlated with RRMS activity.The results of a study, in which more than 20 million patient records were statistically evaluated,showed that hyperuricemia protects against MS[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e],and our results also demonstrate that SUA is protective against the disease,possibly because SUA is a natural scavenger of peroxynitrite,a toxic product of nitric oxide and superoxide,It induces inflammation, demyelination and axonal damage in the pathogenesis of MS[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e"},{"header":"5.Conclusion","content":"\u003cp\u003eThe levels of NLR,MLR and PLR in peripheral blood of patients with RRMS in the acute phase are higher than those of healthy people.The NLR in peripheral blood of patients with RRMS in the acute phase has a certain predictive value for the severity of disability,and emphasizing the role of NLR in the diagnosis may help doctors predict the severity of patients.We conclude that NLR and SUA are associated with RRMS disability and activity, and that they have opposite effects.Our findings seem to suggest that evaluation of NLR values together with SUA values may be more effective in assessing disability as well as mobility in MS patients than evaluation of these parameters alone.However,due to the limitation of objective conditions,this study was a single-center open study with a small sample size, and there may be a certain selection bias.Therefore,the conclusions of this paper still need to be verified by multi-center and large-sample studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRJY, Study design,data collection and curation, conceptualization,writing draft,prepared the final manuscript, and submission.ZWH, XLM, DXS,YZZ,collected data/investigation and participated in writing the manuscript.CHP contributed to study conceptualization.LGZ and ZD revised the eventual manuscript.All authors have read and approved this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis data set may be available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Board of the First Affiliated Hospital of Harbin Medical University examined and authorized the studies involving human subjects. Furthermore, informed consent was not required, according to the Institutional Review No.2021JS34（Research 2019118)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to reasons of patient confidentiality; this dataset may be available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBisgaard AK, Pihl-Jensen G. Frederiksen JL.The neutrophil-to-lymphocyte ratio as disease activity marker in multiple sclerosis and optic neuritis. Mult Scler Relat Disord. 2017;18:213\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHemmer B. Kerschensteiner M,Korn T.Role of the innate and adaptiveimmune responses in the course of multiple sclerosis. Lancet Neurol. 2015,;14(4):406\u0026ndash;19. ,.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZostawa J, Adamczyk J, Sowa P. et al.The infl uence of sodium on Pathophysiology of multiple sclerosis.Neurol Sci,2017,38(3):389\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOcana A, Nieto-Jim\u0026eacute;nez C. Pandiella A,Templeton AJ.Neutrophils in cancer:prognostic role and therapeutic strategies. Mol Cancer. 2017,;16(1):137. ,.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishijima TF. Muss HB,Shachar SS,Tamura K,Takamatsu Y.Prognostic value of lymphocyte-to-monocyte ratio in patients with solid tumors: a systematic review and meta-analysis. Cancer Treat Rev. 2015,;41(10):971\u0026ndash;8. ,.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHosoda K. Umemura K,Shimizu A,Soejima Y.The platelet-to-lymphocyte ratio is a complementary prognostic factor to tumor markers in predicting early recurrence of hepatocellular carcinoma after hepatectomy. J Surg Oncol. 2024;129(4):765\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfari ME. Bhat T.Neutrophil to lymphocyte ratio (NLR) and cardiovascular diseases: an update. Expert Rev Cardiovas 2016,14(5):573\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJaaban M,Zetoune AB,Hesenow S,Hessenow R.Neutrophil -lymphocyte ratio and platelet-lymphocyte ratio as novel risk markers for diabetic nephropathy in patients with type 2 diabetes.Heliyon,2021,7(7):e07564.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu H,Qin B,Hu Z,Ma N,Yang M,Wei T et al.Neutrophil- and platelet-to-lymphocyte ratios are correlated with disease activity in rheumatoid arthritis.Clin Lab,2015,61(3\u0026ndash;4):269\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYanHongjing. Combined platelet-to-lymphocyte ratio and blood-brain barrier biomarkers as indicators of disability in acute neuromyelitis optica spectrum disorder. Neurol Sci. 2024;45(2):709\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHi,Xiangsong;Zhang,Xiulin. et al.Correlation between inflammatory markers over time and disease severity in status epilepticus: a preliminary study.Front Neurol,2024,15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson A, Banwell B,Barkhof F. et al.Diagnosis of multiple sclerosis:2017 revisions of the McDonald criteria.Lancet Neurol,2018,17(2):162\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurtzke JF. Rating neurologic impairment in multiple sclerosis:An expanded disability status scale (EDSS).Neurology,1983,33(11):1444\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConradsson D, Ytterberg C, von Koch L et al. Changes in disability in people with multiple sclerosis:a 10-year prospective study.J Neurol,2018,265(1):119\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e中华医学会神经病学分会神经免疫学组.多发性硬化诊断与治疗中国指南(2023版).中华神经科杂志,2024,Vol.57,No.1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolayir A. ,Cigdem B,Gokce SF,Yilmaz D.The relationship between neutrophil/lymphocyte ratio and uric acid levels in multiple sclerosis patients.Bratisl Med J 2021,122(5):357\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFahmi RM, Ramadan BM,Salah H. Neutrophil-lymphocyte ratio as a marker for disability and activity in multiple sclerosis. Mult Scler Relat Dis. 2021;51:102921.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaegele M, Tillack. K,Reinhardt,S,et al.Neutrophils in multiple sclerosis are characterized by a primed phenotype. J NEUROIMMUNOL. 2011;242(1\u0026ndash;2):60\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jneuroim.2011.11.009\u003c/span\u003e\u003cspan address=\"10.1016/j.jneuroim.2011.11.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHemond CC, Glanz BI, Bakshi R, Neurol. 2019,19(1):23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurtzke JF. Rating neurologic impairment in multiple sclerosis:An expanded disability status scale (EDSS).Neurology,1983,33(11):1444\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Amico. E,Zangh\u0026igrave;,A,Romano,A,et al.The Neutrophil-to-Lymphocyte Ratio is Related to Disease Activity in Relapsing. Remitting Multiple Scler Cells. 2019;8(10). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cells8101114\u003c/span\u003e\u003cspan address=\"10.3390/cells8101114\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePierson ER. Wagner,CA,Goverman,JM.The contribution of neutrophils to CNS autoimmunity. CLIN IMMUNOL. 2016;189:23\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clim.2016.06.017\u003c/span\u003e\u003cspan address=\"10.1016/j.clim.2016.06.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStaub M. Uric acid as a scavenger in oxidative stress. Orv Hetil. 1999;140:275\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToncev G, Milicic B,Toncev S. Serum uric acid levels in multiple sclerosis patients correlate with activity of disease and blood-brain barrier dysfunction. Eur J Neurol. 2002;;9(3):221\u0026ndash;6. .\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Relapsing-remitting multiple sclerosis, Neutrophil-lymphocyte ratio, Monocyte-lymphocyte ratio, Platelet-lymphocyte ratio, Serum uric acid","lastPublishedDoi":"10.21203/rs.3.rs-4428275/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4428275/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is limited research on the relevance of neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and platelet-lymphocyte ratio (PLR) in patients diagnosed with relapse-remitting multiple sclerosis (RRMS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main objective of this study was to evaluate the significance of NLR, MLR, and PLR levels in the peripheral blood of patients diagnosed with RRMS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 109 patients with RRMS recruited from the Department of Neurology, the First Affiliated Hospital of Harbin Medical University from January 2018 to January 2024 were retrospectively analyzed, and 71 healthy population as controls (HC). Clinical data including age, sex, blood routine, serum uric acid (SUA),radiological investigations including magnetic resonance imaging (MRI) of brain and spinal cord were done(A standardized protocol of MRI comprising T2-weighted and T1-weighted gadolinium enhancing were performed using 3.0 Tesla superconducting MR imager)and Extended Disability Status Scale (EDSS) of all RRMS patients were collected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe levels of NLR, MLR and PLR were significantly higher in RRMS patients compared to the HC. RRMS patients with moderate-severe disability had higher NLR and MLR levels than those with mild disability. Logistic regression analysis showed that NLR was associated with disease disability (odds ratio(OR):1.470; confidence interval(CI):1.024–1.153; P:0.046). The cutoff value for the NLR to predict RRMS disability was 2.17.NLR was higher in RRMS patients with disease activity than in those without activity (p = 0.045), while SUA was lower in RRMS patients with disease activity than in those without activity (p = 0.033). Compared with HC,RRMS patients had lower SUA levels (p = 0.008). Additionally, SUA levels decreased with the increase of EDSS scores (P = 0.003), and NLR value was negatively correlated with SUA (p = 0.022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe levels of NLR,MLR and PLR in peripheral blood of RRMS patients in the acute phase are higher than those of healthy people, and NLR has a certain predictive value for the severity of disability. Furthermore, we suggest that NLR and SUA are related to the disability and activity of RRMS, albeit exerting opposing effects on the disease.\u003c/p\u003e","manuscriptTitle":"Analysis of the value of NLR, MLR and PLR levels in peripheral blood of patients with RRMS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-11 20:42:30","doi":"10.21203/rs.3.rs-4428275/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5aac3c5-558c-4702-9d83-b64f18b86931","owner":[],"postedDate":"June 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-26T05:38:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-11 20:42:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4428275","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4428275","identity":"rs-4428275","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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