Relationships Between the Corpus Callosum Index and Current Blood Parameters and Temporal Changes in these Parameters in Patients with Multiple Sclerosis

Summary

Objectives:

This study aimed to investigate changes in blood parameters and examine the relationships among the corpus callosum index (CCI), plaque characteristics, and blood parameters in multiple sclerosis (MS) patients. In MS, the CCI is associated with brain atrophy and disease progression.

Methods:

In this retrospective, cross-sectional study, demographic data from 103 MS patients (38 males), along with blood parameters obtained five years earlier and current values, were analyzed in relation to magnetic resonance imaging (MRI) findings. The CCI calculated from MRI scans was assessed in relation to plaque distribution and number. Statistical analyses included paired sample t tests, Wilcoxon tests, and Spearman correlation analysis.

Results:

Current lymphocyte, platelet, and monocyte levels were significantly lower than those measured five years earlier (p<0.001; p=0.026; p<0.001), whereas the systemic immune-inflammation index (SII) significantly increased (p=0.035). The CCI was positively correlated with the monocyte/neutrophil ratio (MNR) (p=0.011, r = 0.251) and negatively correlated with the SII (p=0.048, r=–0.196). Additionally, the CCI was significantly negatively correlated with periventricular and juxtacortical plaque number, the Expanded Disability Status Scale (EDSS), and MS attack frequency.

Conclusion:

In MS patients, the CCI is negatively associated with the SII, plaque distribution, and plaque number and positively associated with the MNR. A decreased MNR and increased SII are linked to corpus callosum atrophy.

Introduction

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease that is commonly observed in young adults [1,2]. Characterized by inflammatory lesions in the brain and spinal cord along with widespread low-grade inflammation, MS affects approximately 2.8 million people worldwide. MS typically manifests in individuals between the ages of 20 and 30, initially following a course marked by relapses and remissions, which may eventually evolve into a steadily progressive form. The pathophysiology of MS involves the onset of low-grade inflammation and intracellular dysregulation in the central nervous system (CNS) at an early stage, ultimately leading to widespread damage and atrophy [1].

The neutrophil/lymphocyte ratio (NLR) and the monocyte/lymphocyte ratio (MLR) may serve as useful markers for predicting clinical features such as disease course and progression in MS [2,3,4,5,6]. These inflammatory parameters are expected to vary during the active phase of the disease when inflammation is most pronounced [2,3]. In addition to the NLR and MLR, other inflammatory biomarkers, such as the systemic immune-inflammation index (SII) and the platelet/lymphocyte ratio (PLR), are considered potential markers for identifying active lesions in MS patients [3]. Previous studies have demonstrated that inflammatory markers are associated with disease activity and disability in MS patients. In particular, indices such as the SII, systemic immune response index (SIRI), and systemic total aggregation index (AISI) have been found to be important for predicting the no evidence of disease activity (NEDA) status [7]. Furthermore, during MS relapses, total white blood cell (WBC), monocyte, basophil, and neutrophil counts are significantly higher than in healthy controls [8]. Consequently, alterations in complete blood count parameters in MS patients may be linked to disease prognosis and could be utilized for early diagnosis and prognostic evaluation [8,9]. Additionally, the combined use of radiological and blood biomarkers may enhance our understanding of disease activity and prognosis in MS patients [10].

This study is among the first to investigate the relationships between the corpus callosum index (CCI) and current blood parameters in MS patients, with a particular focus on its association with the SII and the monocyte/neutrophil ratio (MNR). Additionally, temporal changes in these blood parameters over a five-year period were analyzed to explore their potential impact on MS pathophysiology. Secondary objectives include assessing the relationships between the CCI and the number and distribution of MS plaques, as well as relapse frequency and disease duration.

Methods

This retrospective observational study involving 2 distinct time points is based on the analysis of patient data obtained from the neurology department's records at our institution. A total of 103 patients who were diagnosed with MS and undergoing follow-up and treatment at our hospital were included in the study. Based on their demographic and clinical characteristics, the patient group consisted of 91 individuals with relapsing–remitting MS (RRMS), 9 with secondary progressive MS (SPMS), and 3 with primary progressive MS (PPMS). For all patients, blood parameters were evaluated across two distinct time periods: the first covering five years earlier (December 2018–December 2019) and the second representing the present period (December 2023–December 2024).

Blood parameters measured 5 years earlier and at the present point, along with brain and spinal MRI scans obtained during routine follow-up over the past year, were included in the analysis. Brain MRI scans were acquired with a 1.5 Tesla MRI system. On MRI scans, the numbers of T2 hyperintense plaques in axial brain images and sagittal spinal cord sections were independently assessed in a blinded manner by two neurologists and one radiologist. Plaques were individually identified and recorded in the following anatomical regions: periventricular (PV; right and left), juxtacortical (JC; right and left), infratentorial (IT; right and left), and spinal regions. Furthermore, to assess corpus callosum (CC) atrophy, the CCI was measured by the same expert team and utilized as an indicator [11]. The CCI was calculated on the optimal mid-sagittal T1-weighted images by measuring the anterior (aa’), middle (cc’), and posterior (bb’) segments of the CC and then dividing the sum of these segments by the maximum anteroposterior diameter of the CC (ab): CCI = (aa’ + bb’ + cc’)/ab [11] (Fig. 1). Additionally, demographic data, including the duration of MS, number of attacks, MS type, Expanded Disability Status Scale (EDSS) score, and MS medications used, were recorded.

Fig. 1.

Illustration of the formula used to calculate the corpus callosum index (CCI) on T1 sagittal magnetic resonance imaging. CCI = (aa’ + bb’ + cc’) / ab.

Inclusion criteria

Individuals were included in the study if they were 18 years of age or older, had a confirmed diagnosis of MS according to the 2017 McDonald criteria, had undergone both brain and spinal MRI within the preceding year, had complete blood count results from two distinct time points (current and five years prior), and had been regularly monitored in our neurology clinic throughout the study period.

Exclusion criteria

Participants were not considered for the study if they had neurological conditions other than MS, any hematological or oncological disorder, evidence of active infection or systemic inflammation at the time of blood sampling, experienced a relapse during the sampling period, were receiving high-dose corticosteroids or other immunosuppressive agents, or lacked complete clinical or radiological information.

The evaluation of disease-modifying therapies (DMTs) was based on retrospective patient records. The medications prescribed and used by patients over the past five years were categorized into treatment groups, namely, teriflunomide, ocrelizumab, dimethyl fumarate (DMF), fingolimod, glatiramer acetate, interferon beta-1a, cladribine, natalizumab, and a nonmedicated group. These treatment groups were further analyzed, and blood parameters were compared between the 2 time points. The effects of different DMTs on systemic inflammatory markers such as the SII and MNR were also assessed.

The evaluated blood parameters included WBC, lymphocyte, neutrophil, monocyte, eosinophil, basophil, and platelet counts, as well as red blood cell (RBC) count, hemoglobin level, and hematocrit. The following ratios were derived from the blood parameters: MLR, MNR, NLR, neutrophil/monocyte ratio (NMR), PLR, platelet/monocyte ratio (PMR), platelet/neutrophil ratio (PNR), pan-immune-inflammation index (PIV) = (neutrophil × platelet × monocyte)/lymphocyte, SIRI = (neutrophils × monocytes)/lymphocytes, and SII = (platelet × neutrophil)/lymphocyte.

This study was approved by the Aksaray University Health Sciences Ethics Committee (Decision No: 2024/117, Date: 07.11.2024) and was conducted in accordance with the Declaration of Helsinki.

Statistical analysis

Numerical variables were described using appropriate measures of central tendency and dispersion, whereas ordinal data were expressed as median values together with their minimum and maximum limits. The distribution characteristics of each parameter were examined through the Kolmogorov–Smirnov test. For variables exhibiting a normal distribution pattern, comparisons between the two time points were performed using the paired-samples t-test. When normality criteria were not met, the corresponding paired comparisons were carried out with the Wilcoxon signed-rank test. Since the CCI values showed a non-Gaussian distribution, associations with clinical and laboratory variables were evaluated using Spearman's rank-based correlation method. All the statistical procedures were executed with SPSS software (version 23.0, MacOS), and a p-value less than 0.05 was considered to indicate statistical significance.

Results

A total of 103 MS patients (38 males, 65 females; mean age: 37±10 years) were included. Among them, 91 had RRMS, 9 had SPMS, and 3 had PPMS. The mean duration since diagnosis was 9±5.31 years, with an average of 2.0±1.71 attacks. Analysis of the normally distributed data revealed no significant differences in the current hemoglobin and hematocrit values of the patients compared with those measured five years earlier (p=0.158 and p=0.541, respectively). However, the current WBC, lymphocyte, RBC, and platelet counts were significantly lower than those measured five years earlier (p=0.005, p< 0.001, p<0.001, and p=0.026, respectively) (Table 1).

Table 1.

Mean (± SD) values and p values of various blood parameters in multiple sclerosis patients measured five years earlier and currently.

Parameter	Current (Mean ± SD)	5 years earlier (Mean ± SD)	P*
WBC, 109/L	6.61 ±1.82	7.25 ±1.91	0.005
Lymphocyte, 109/L	1.65 ±0.79	2.03 ±0.77	<0.001
RBC, 1012/L	4.74 ±0.42	4.9 ±0.46	<0.001
Hemoglobin, g/dL	13.6 ± 1.42	13.8 ± 1.6	0.158
Hematocrit, %	41.6 ±3.87	41.4 ±4.19	0.541
Platelet, 109/L	257.17 ±71.5	270 ±71.06	0.026

^*paired t test; WBC: white blood cell; RBC: red blood cell; SD: standard deviation.

The analysis of the nonnormally distributed data revealed no significant differences in the current neutrophil, eosinophil, basophil, PNR, MLR, MNR, PIV, PMR, or SIRI values of the patients compared with those measured five years earlier (p=0.091, p=0.473, p=0.13, p=0.966, p=0.051, p=0.074, p=0.859, p=0.071, and p=0.36, respectively). However, the current monocyte counts were significantly lower (p<0.001), and the current NLR, PLR, and SII values were significantly greater (p<0.001, p=0.001, and p=0.035, respectively) than those measured five years earlier (Table 2).

Table 2.

Median values and p-values of various blood parameters in MS patients measured five years earlier and currently.

Parameter	Current Value (Min–Max)	5 years earlier(Min–Max)	P*
Monocyte, 109 /L	0.43 (0.01–0.88)	0.49 (0.21–1.02)	<0.001
Neutrophil, 109 /L	4.05 (1.78–9.64)	4.38 (1.91–10.34)	0.091
Eosinophil, 109 /L	0.1 (0.01–1.28)	0.1 (0.001–2.0)	0.473
Basophil, 109 /L	0.03 (0.001–0.12)	0.03 (0.001–0.5)	0.13
NLR	2.58 (0.76–13.69)	2.23 (0.64–11.2)	0.001
PLR	153.33 (37.3–966.67)	135.83 (55.52–1368.0)	0.001
PNR	59.82 (14.87–162.5)	58.77 (20.7–194.39)	0.966
MLR	0.27 (0.03–1.67)	0.24 (0.1–1.58)	0.051
MNR	0.11 (0.0–0.28)	0.11 (0.03–0.35)	0.074
SII	640.29 (88.03–4853.0)	609.75 (120.81–3502.08)	0.035
PIV	286.21 (35.19–3251.51)	293.82 (45.91–1305.37)	0.859
PMR	550.0 (280.0–25700.0)	502.38 (225.68–1944.44)	0.071
SIRI	1.15 (0.14–8.32)	1.09 (0.24–6.1)	0.36

^*Wilcoxon signed-rank test; MLR: monocyte/lymphocyte ratio; MNR: monocyte/neutrophil ratio; NLR: neutrophil/lymphocyte ratio; PIV: pan-immune-inflammation value = neutrophil count × platelet count × monocyte count/lymphocyte ratio; PLR: platelet/lymphocyte ratio; PMR: platelet/monocyte ratio; PNR: platelet/neutrophil ratio; SIRI: systemic immune response index = neutrophil × monocyte/lymphocyte; SII: systemic immune-inflammation index = platelet × neutrophil count/lymphocyte count; MS: multiple sclerosis.

Spearman correlation analysis revealed that the CCI was negatively correlated with the right PV plaque (PVP) (p < 0.001 and rho: –0.503), left PVP (p < 0.001 and rho: –0.466), right JCP (p = 0.001 and rho: –0.317), left JCP (p < 0.001 and rho: –0.345), left ITP (p = 0.023 and rho: –0.224), EDSS (p = 0.001 and rho: –0.324), MS attack frequency (p = 0.011 and rho: –0.249), and disease duration (years) (p = 0.042 and rho: –0.201). The correlation of CCI with blood parameters 5 years earlier was not significant (p > 0.05). The correlation of the CCI with current blood parameters revealed that the CCI was positively correlated with the MNR (p = 0.011 and rho: 0.251) and negatively correlated with the SII (p = 0.048 and rho: –0.196) (Table 3).

Table 3.

Spearman correlation of CCI with clinical, radiological, and inflammatory markers in MS.

Variable	r	P
MNR(Current blood test results)	+0.251	0.011
SII(Current blood test results)	–0.196	0.048
Right PVP	–0.503	<0.001
Left PVP	–0.466	<0.001
Right JCP	–0.317	0.001
Left JCP	–0.345	<0.001
Left ITP	–0.224	0.023
MS attack frequency	–0.249	0.011
Disease duration (years)	–0.201	0.042
EDSS	–0.324	0.001

PVP: periventricular plaque; JCP: juxtacortical plaque; ITP: infratentorial plaque; MS: multiple sclerosis; EDSS: expanded disability status scale; MNR: monocyte/neutrophil ratio; SII: systemic immune-inflammation index; CCI: corpus callosum index.

Analysis of normally distributed parameters from data collected five years apart revealed a statistically significant increase in the SII only in the DMF group (n = 37; p = 0.037), with the MNR showing no significant changes across all treatment groups (p ≥ 0.05). In the teriflunomide group (n = 14), a slight decrease in the MNR (p = 0.522) and a modest increase in the SII (p = 0.638) were observed, but these differences were not statistically significant. Similarly, in the ocrelizumab group (n = 13), both the MNR (p = 0.980) and the SII (p = 0.920) remained essentially unchanged. Moreover, analyses of the glatiramer acetate (n = 8) and nonmedicated (n = 3) groups revealed no significant differences in MNR (p = 0.779 and p = 0.267, respectively) or SII (p = 0.573 and p = 0.624, respectively) (Table 4). For nonnormally distributed parameters, no significant changes were identified in the fingolimod group (n = 16) for MNR (p = 0.063) and SII (p = 0.088), in the interferon beta-1a group (n = 6) for MNR (p = 0.733), in the cladribine group (n = 4) for both MNR (p = 0.407) and SII (p = 0.170), or in the natalizumab group (n = 2) for either parameter (p = 0.655) (Table 5).

Table 4.

Groups comparisons of current vs. five-year earlier values in normally distributed parameters across treatment groups.

Drug Name	Group N	Parameter	Current (Mean ± SD)	5 years earlier (Mean ± SD)	P*
Teriflunomide	14	MNR	0.1469 ± 0.0613	0.1590 ± 0.0750	0.522
Ocrelizumab	13	MNR	0.1129 ± 0.0418	0.1132 ± 0.0416	0.980
Interferon Beta-1a	6	MNR	0.0981 ± 0.0256	0.0948 ± 0.0260	0.733
Cladribine	4	MNR	0.1221 ± 0.0190	0.1600 ± 0.0928	0.407
Glatiramer Acetate	8	MNR	0.1015 ± 0.0463	0.0975 ± 0.0307	0.779
Non-Medicated Group	3	MNR	0.1152 ± 0.0251	0.1766 ± 0.0659	0.267
Ocrelizumab	13	SII	737.54 ± 418.30	719.14 ± 400.75	0.920
Cladribine	4	SII	986.68 ± 580.01	653.09 ± 268.29	0.170
Glatiramer Acetate	8	SII	653.56 ± 360.02	361.73 ± 38.66	0.573
Non-Medicated Group	3	SII	412.64 ± 118.20	361.73 ± 38.66	0.624

^*Paired t-test analysis; MNR: monocyte/neutrophil ratio; SII: systemic immune-inflammation index; SD: standard deviation.

Table 5.

Comparisons of current vs. five-year earlier values in non-normally distributed parameters across treatment groups.

Drug Name	Group N	Parameter	Current Value Median (Min–Max)	5 years earlier Median (Min–Max)	P*
Teriflunomide	14	SII	528.06 (88.03–2232.17)	428.69 (120.81–783.51)	0.638
Dimethyl Fumarate	37	MNR	0.1067 (0.00–0.22)	0.1073 (0.03–0.25)	0.886
Dimethyl Fumarate	37	SII	908.15 (298.79–3519.47)	669.59 (270.93–2541.74)	0.037
Fingolimod	16	MNR	0.1059 (0.05–0.18)	0.1369 (0.06–0.29)	0.063
Fingolimod	16	SII	1722.77 (420.64–4853.00)	1175.35 (233.91–3502.08)	0.088
Natalizumab	2	MNR	0.1388 (0.14–0.14)	0.1564 (0.13–0.18)	0.655
Natalizumab	2	SII	506.74 (483.51–529.97)	494.10 (319.55–668.65)	0.655

^*Wilcoxon signed-rank test; MNR: monocyte/neutrophil ratio; SII: systemic immune-inflammation index.

Discussion

The key outcomes of the present study can be outlined as follows: A positive correlation was found between CCI and MNR, and a negative correlation between CCI and SII. When comparing blood parameters from five years ago with current values, significant decreases were observed in WBC, lymphocyte, RBC, platelet, and monocyte levels, whereas notable increases were found in NLR, PLR, and SII levels. In the analysis evaluating the effects of DMTs, a statistically significant increase in SII values was observed only in the DMF group. No notable changes in SII were detected in other medication groups, and differences in MNR were not observed in any of the treatment groups. On the other hand, the negative correlation between CCI and disease duration indicated that CC atrophy became more pronounced as the disease progressed. A negative relationship was observed between CCI and the location and number of existing plaques. Additionally, a negative correlation was found between CCI and the EDSS score as well as the frequency of MS attacks.

The CC is the largest commissure in the brain, facilitating interhemispheric communication. In patients with MS, CC atrophy occurs due to focal demyelination, axonal damage, and Wallerian degeneration resulting from distant lesions [11]. These structural changes play a significant role in the progression of MS [11]. CCI is an important indicator for predicting brain atrophy and disease progression. More pronounced reductions are observed in SPMS compared to RRMS, and these declines become more significant in untreated patients [12]. Studies have demonstrated that CCI is associated with cognitive impairment and disability, [13] while CC volume loss is linked to neurodegeneration and disease progression [14]. The findings of this study suggest that the number of plaques in the bilateral PV, bilateral JC, and left IT regions exhibits a negative correlation with CCI, indicating that an increased plaque burden exacerbates CC atrophy. Furthermore, the negative correlation between CCI and disease duration, attack frequency, and EDSS supports the use of CCI as a biomarker for monitoring MS progression [11,12,13,14]. The reduction in CCI appears to play a crucial role in monitoring early neurodegeneration in MS patients and predicting increasing levels of disability.

Over time, changes in inflammatory markers and blood parameters play a crucial role in predicting the clinical status of patients with MS [1,2,3,4,5,6,7]. In recent years, SII has been frequently used as an inflammatory marker [3,7,15,16,17]. High SII values have been associated with disease progression [15]. In the study conducted by Vural et al., SII was found to be statistically significantly higher in MS patients compared to the control group. Moreover, patients with active lesions exhibited higher SII values than those without active lesions [3]. Saçmacı et al. reported that SII is associated with disease-related disability in MS patients and that a significant correlation exists between EDSS and SII. The authors suggested that high SII values could be useful in predicting disability in MS patients [16]. Another study highlighted that SII shows a significant association with the EDSS score and may serve as an important biomarker for predicting NEDA status. Additionally, SII has been reported to show a strong positive correlation with other inflammatory indices [7]. In the study conducted by Vural et al., SII was found to be significantly elevated during MS attacks, indicating that this biomarker could be an important predictor of MS attacks [17]. In the present study, a significant difference was observed between the current SII values and those measured five years earlier in the same patient group, with the current SII values being markedly higher. This finding indicates that, in MS patients, SII values—which are already elevated compared to the healthy control group—further increase as disease duration progresses. Furthermore, considering that current SII values are significantly higher than those from five years ago, the weak negative correlation observed between the CCI and SII suggests that increased systemic inflammation may be associated with CC atrophy. Although the heterogeneous distribution of DMTs in our study limits intergroup comparisons, the significant increase in SII observed in patients treated with DMF, which parallels the overall rise in the group, suggests a more pronounced immunomodulatory response compared to other treatment groups. To validate these findings and elucidate the long-term effects on neurodegeneration, further studies with larger and more homogeneous patient groups are warranted.

Monocytes and neutrophils play crucial roles in both pro-inflammatory and anti-inflammatory processes in MS pathogenesis. While monocytes contribute to the repair of damaged tissues, neutrophils increase the permeability of the blood brain barrier (BBB), triggering inflammation and demyelination [18,19,20]. An increase in neutrophil levels in MS patients has been associated with disease activity and progression [15]. Regarding monocytes, the study by Taha et al. demonstrated that classical, intermediate, and non-classical monocyte levels were significantly higher in RRMS patients compared to the control group. In particular, the proportion of non-classical monocytes has been reported to be higher in patients with active plaques, and these cells have been suggested to play a significant role in MS pathology [21]. Rodriguez et al. demonstrated that CD206^hiCD209^hi classical monocytes are associated with an aggressive disease phenotype, high inflammatory activity, and poor prognosis, particularly in patients carrying the HLA-DRB1*15:01 allele. These cells were also linked to increased inflammatory burden in gadolinium-enhanced MRI scans [22]. Arneth's review demonstrated that monocytes play a central role in regulating inflammatory responses and monitoring disease activity. Furthermore, non-classical monocytes have been proposed as potential biomarkers. It has been suggested that variability in monocyte populations according to disease stages may facilitate a better understanding of MS progression.[19]. In our study, a significant decrease in monocyte levels was observed compared to measurements taken five years ago. Although previous studies have reported that monocyte levels in RRMS patients are higher than those in the control group regardless of disease activity, [21] our findings indicate that this increase has significantly decreased over time. Although a decrease in neutrophil levels was also observed, this decline was not found to be statistically significant. When considering the monocyte-to-neutrophil ratio, the weak positive correlation between current MNR and CCI may indicate the potential impact of inflammatory processes on CC integrity. As MS progresses, the decrease in monocyte levels, the changes in MNR, and the decline in CCI occur in parallel. This finding supports the expectation of a decline in CCI levels and suggests that the increase in MNR is associated with the increase in CCI. On the other hand, when comparing the MNR values from five years ago and the current values based on the drug groups used by the patients, no statistically significant difference was observed. This suggests that despite the notable changes in SII, MNR has remained relatively stable regardless of the treatment applied. In conclusion, it can be inferred that maintaining monocyte levels (likely non-classical subtypes) during inflammatory processes may contribute to the preservation of CC structural integrity. Our findings suggest that, although weak, MNR plays a role in monitoring neurodegenerative processes in MS patients and identifying potential therapeutic targets. In this context, further research is needed to examine the impact of monocyte subpopulations on MNR and CCI in greater detail. The observed correlations between CCI and hematological indices such as MNR and SII represent a novel aspect of this study, highlighting the potential of combining neuroimaging and peripheral blood markers to monitor neurodegeneration in MS.

Limitations

The interpretation of our results should consider a number of inherent methodological limitations. First, its retrospective and cross-sectional design restricts establishment of causal relationships. Second, the small sample size may limit generalizability. Additionally, the data used in this study were obtained from a single center, and multicenter studies are required to validate the results. Furthermore, variations in treatment protocols among patients and the numerical imbalance between drug-using patient groups have made it challenging to strengthen comparisons regarding the effects on both inflammatory markers and neurodegenerative processes. While CCI offers a practical and accessible measure of CC atrophy, volumetric analyses using advanced imaging techniques may provide more objective assessments. Future studies should explore the comparative reliability of CCI versus volumetric metrics in tracking MS-related neurodegeneration. Additionally, the absence of a healthy control group—due to the retrospective nature of the study—limits direct comparisons and interpretation of CCI and hematological parameters.

Conclusions

This study suggests the relevance of inflammatory markers and hematological parameters in the clinical progression and neurodegenerative processes of MS patients over time. Compared to five years ago, an increase in SII values was observed, while CCI showed a negative correlation with SII and a positive correlation with MNR, indicating a possible association between hematological changes and neurodegenerative mechanisms. Regarding treatment effects, a statistically significant increase in SII was observed exclusively in patients treated with DMF, suggesting its potential role in enhancing the inflammatory response. These results underscore the need for further large-scale, multicenter studies to evaluate treatment protocols more comprehensively. In conclusion, the relationship between inflammatory processes, hematological parameters, and CCI may provide valuable insights into MS pathophysiology, disease monitoring, and treatment strategies.

Ethical approval

This retrospective study was approved by Aksaray University Health Sciences Scientific Research Ethics Committee (Decision No: 2024/117, Meeting Date: 07.11.2024, Protocol: SAGETIK88).

Acknowledgments

We would like to extend our sincere gratitude to Dr. Muhammed Şamil Aydın, Radiology Specialist at Aksaray University Training and Research Hospital, for his valuable contributions to the radiological evaluation of this study. We would like to thank Ulatus (www.ulatus.com) for English language editing.

AI disclosure

This manuscript did not use any artificial intelligence tools for data collection, data analysis, image creation, or scientific content generation. An AI-based language model was used only for minor language editing during the drafting process. All scientific interpretations, results, and conclusions are solely the responsibility of the authors.