Browsing by Author "Zengin, Ela Simay"

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Autoimmune Thyroiditis and Its Impact on the Clinical Course of Multiple Sclerosis: a Retrospective Cohort Study
(Elsevier Sci Ltd, 2025) Kaya, Ergi; Samadzade, Ulvi; Zengin, Ela Simay; Ozakbas, Serkan
Introduction: Autoimmune thyroiditis (AT) stands out as one of the most prevalent accompanying comorbidity of Multiple Sclerosis (MS). However, the specific impact of AT on the clinical course of MS is relatively unexplored. Objectives: The primary objective of this study is to determine the frequency of AT within an MS cohort and to assess its influence on the prognosis of MS. Method: We retrospectively detected those who had an AT diagnosis during their lifetime. Patients who had been diagnosed with AT before a diagnosis of MS or during the diagnosis process were analyzed for prognosis. (aMS) Demographic variables, baseline Expanded Disability Status Scale (EDSS) score and relapse number, disease- modifying treatment duration and type, the relapse number, new/expanding lesions in brain and spinal MRI in first five years, fifth-year EDSS and fifth year No Evidence of Disease Activitiy-3 results were collected. These variables were compared to people with MS who had similar baseline and demographic characteristics. (non-AT) Results: Fifty-seven people with MS (1.6 %) were diagnosed with AT, all of whom were female. Twenty-four of them were included in the prognosis analysis. There was no statistical difference between aMS and nonAT in diagnosis age, baseline relapse number and baseline EDSS score. (p > 0.05) There were no statistical differences in relapse number, MRI activity in five years, EDSS scores and NEDA-3 status in the fifth year. (P > 0.05) Conclusion: Comorbid AT is frequently seen in the MS population. It has a neutral effect on the MS course.
Development of a Machine Learning Model to Predict the Expanded Disability Status Scale in Multiple Sclerosis Patients
(Elsevier Sci Ltd, 2026) Ozdogar, Asiye Tuba; Emec, Murat; Kaya, Ergi; Zengin, Ela Simay; Ozcanhan, Mehmet Hilal; Ozakbas, Serkan
Objective: The assessment of disability in multiple sclerosis (MS) patients is crucial for treatment decisions and prognosis estimation. The Expanded Disability Status Scale (EDSS) provides a standardized way to quantify disability in MS. However, predicting EDSS scores can be challenging due to the complex and heterogeneous nature of the disease. Machine learning techniques offer a promising approach to predict EDSS scores based on various patient characteristics. Methods: 231 people with MS (pwMS) who had an assessment of physical, psychosocial, and cognitive functions in three timelines (baseline (T0), first year (T1), and second year (T2)) were enrolled. The dataset used for the study consists of 126 features. Feature selection was based on feature saliency and correlation analysis. Three machine learning models -XGBoost, Random Forest, and Linear Regression -were trained on the selected features. Hyperparameter tuning was also carried out on the models. Model performance was evaluated using standard evaluation metrics, including MAE, MSE, and R2. Results: The Machine Learning model based on the XGBoost algorithm performed best in predicting EDSS scores (T2). The MAE value obtained with the XGBoost model is 0.2361, the MSE value is 0.2408, and the R2 value is 0.9705. These results indicate that XGBoost's predictive ability on the current dataset is promising. Conclusion: Our study demonstrates the feasibility of using machine learning techniques to predict EDSS scores in MS patients. The developed models show promising performance and have the potential to enhance clinical decision-making and patient management in MS care.
Familial Multiple Sclerosis Is Associated With Accelerated Progression to Secondary Progressive Phase: A Retrospective Single-Center Cohort Study
(Springer Heidelberg, 2025) Ozakbas, Serkan; Alizada, Said; Caliskan, Can; Simsek, Yasemin; Zengin, Ela Simay
Background Familial multiple sclerosis (MS), defined by the occurrence of MS in one or more relatives, is thought to represent a genetically influenced subtype of the disease. Objective To compare clinical progression, cerebrospinal fluid (CSF) parameters, and treatment responses between familial and sporadic MS patients. Methods We conducted a retrospective analysis of 1,035 patients diagnosed with MS according to the 2017 McDonald criteria (523 familial, 512 sporadic). Demographic variables, MS subtypes, expanded disability status scale (EDSS) scores, CSF oligoclonal band (OCB) status, IgG index, and treatment regimens were evaluated. Statistical tests included t tests, chi-square, and multivariable regression. Results Familial MS patients showed a higher incidence of secondary progressive MS (10.9%) compared to sporadic cases (7.0%, p = 0.030). Disease duration was significantly longer in familial MS (14.5 vs. 12.3 years, p < 0.01) though time to diagnosis did not differ. OCB positivity rates were comparable, but the IgG index was significantly elevated in familial MS (p < 0.01). Treatment responses did not differ between groups. Conclusion Familial MS is associated with more rapid disease progression and enhanced humoral immune activation, suggesting a distinct phenotype. These findings support the need for genetic and immunologic investigations to guide personalized treatment strategies.
Kinematic Analysis of Gait Parameters in Patients Affected by Neuromyelitis Optica Spectrum Disorders: a Comparative Study
(Sage Publications Ltd, 2024) Ozdogar, Asiye Tuba; Aslan, Taha; Zengin, Ela Simay; Ozakbas, Serkan
Pain in Neuromyelitis Optica Spectrum Disorder: Determination of Prevalence and Characteristics
(Springer Heidelberg, 2025) Ozdogar, Asiye Tuba; Yesiloglu, Pervin; Unal, Gozde Deniz; Engenc, Veysel; Zengin, Ela Simay; Cilingir, Vedat; Ozakbas, Serkan
Introduction The aim was to determine the prevalence and characteristics of pain in people with neuromyelitis optica spectrum disorders (pwNMOSD).
Methods The Nordic Musculoskeletal Questionnaire (NMQ) was used to determine the participants' pain levels and pain localization. The PainDETECT Questionnaire (PD-Q) was used to differentiate between nociceptive and neuropathic pain. The scores <= 12 were considered as presence of musculoskeletal pain (MSP) and > 12 as neuropathic pain (NP). The Preference-Based Multiple Sclerosis Index (PBMSI) was used to measure health-related quality of life. Information such as Expanded Disability Status Scale (EDSS), disease duration and age of the participants were also recorded.
Results The 62 participants included in the study were divided into 3 groups: 14 without pain, 17 with MSP and 31 with NP. There was no difference between the groups in terms of age, disease duration and EDSS scores (p > .05). When the pain distribution was analyzed, the regions with the most pain complaints in the last 12 months were neck (n = 22, 34.9%), foot-ankle (n = 16, 25.4%) and back (n = 15, 25.8%), respectively. When the quality of life of the three groups were compared, there was a difference between PBMSI-Walk, PBMSI-Fatigue and total score.
Conclusion The results of this study showed that the neck, back, and foot-ankle were the most common and most disabling pain areas in pwNMOSD, regardless of the age, disease duration, and EDSS score of the participant. However, there was a difference between the groups in the parameters related to gait, fatigue and total quality of life against NP.
Prognostic Significance of Oligoclonal Bands and Their Subtypes in Relapsing-Remitting Multiple Sclerosis
(Elsevier Sci Ltd, 2025) Ozakbas, Serkan; Alizada, Said; Cevik, Sumeyye; Samadzade, Ulvi; Yapici, Nurbanu Aygunduz; Zengin, Ela Simay; Caliskan, Can
Objective: To investigate the long-term prognostic significance of cerebrospinal fluid oligoclonal band (OCB) positivity and its subtypes (Type 2 and Type 3) in patients with relapsing-remitting multiple sclerosis (RRMS). Methods: This retrospective cohort included 2324 RRMS patients diagnosed using the 2017 McDonald criteria. All patients had documented OCB status and at least 2 years of clinical follow-up; a subset had 5-year data. Outcomes included Expanded Disability Status Scale (EDSS), annualised relapse rate (ARR), and conversion to secondary progressive MS (SPMS). Subgroup analysis compared Type 2 and Type 3 OCBpositive patients. Results: OCB positivity was observed in 82.4 % of patients. At year 2, no significant differences in EDSS, ARR, or SPMS conversion were found between OCB-positive and OCB-negative groups. However, by year 5, the OCBpositive group had a significantly higher rate of conversion to SPMS (p < 0.05). Subgroup analysis showed that Type 3 OCB patients had significantly lower EDSS scores at year 2 compared to Type 2 (p < 0.05), but this difference disappeared at year 5. Conclusion: OCB positivity may be associated with a higher risk of progression to SPMS over the long term. Type 3 OCB may indicate a milder early disease course, although its protective effect diminishes over time. Incorporating OCB subtype analysis into RRMS prognosis may enhance early risk stratification.
Revisiting the Diagnostic Marker: Oligoclonal Band Positivity is Not Associated with Early Disability or Cognitive Performance in Relapsing-Remitting Multiple Sclerosis
(Elsevier Sci Ltd, 2025) Samadzade, Ulvi; Alizada, Said; Zengin, Ela Simay; Cevik, Sumeyye; Yapici, Nurbanu Aygunduz; Kara, Irem; Ozakbas, Serkan
Background: Oligoclonal bands (OCBs) in the cerebrospinal fluid (CSF) are a hallmark diagnostic biomarker for multiple sclerosis (MS), found in over 80 % of patients. While their role in diagnosis and disease conversion from clinically isolated syndrome (CIS) to MS is well-established, their relationship with baseline clinical, physical, and cognitive characteristics in relapsing-remitting MS (RRMS) remains less clear. Objective: To investigate whether OCB positivity is associated with differences in demographic variables, physical disability, and cognitive performance in patients with RRMS at disease onset. Methods: In this retrospective observational study, 2324 treatment-na & iuml;ve patients diagnosed with RRMS were stratified into OCB-positive and OCB-negative groups based on CSF analysis performed at diagnosis. Baseline assessments included demographic data, Expanded Disability Status Scale (EDSS) scores, and cognitive and motor performance measured by the Brief International Cognitive Assessment for MS (BICAMS), Timed 25-Foot Walk Test (T25FW), and 9-Hole Peg Test (9-HPT). Group comparisons were conducted using t-tests and chisquare tests; multivariate analyses controlled for confounders. Results: OCBs were detected in 82.4 % (n = 1915) of patients. No significant differences were observed between OCB+ and OCB- groups in terms of age at onset, sex, initial symptom type, or baseline EDSS. Similarly, cognitive scores (SDMT, CVLT-II, BVMTR) and physical test performance (T25FW, 9-HPT) did not differ significantly between the two groups. Multivariate regression confirmed no independent association between OCB status and clinical, cognitive, or motor variables at diagnosis. Additional follow-up data: At the 2-year follow-up, no significant differences were observed between OCB-positive and OCB-negative groups regarding EDSS, ARR, or SPMS conversion (all p > 0.05). At the 5-year follow-up, EDSS and relapse rates remained similar, but a significantly higher proportion of OCB-positive patients had converted to SPMS (p < 0.05). Conclusion: Although OCB positivity remains a crucial diagnostic tool and a known prognostic factor for conversion from CIS to MS, our findings suggest that it does not significantly influence early cognitive or physical performance in patients with established RRMS. Further longitudinal studies are needed to determine the prognostic utility of OCBs in relation to disease progression and neurodegeneration.