Clusters of Onset Symptoms in Multiple Sclerosis: Characteristics, Comorbidities, and Risk Factors

Abstract

Background: Multiple Sclerosis (MS) is a chronic, immune-mediated disease of the central nervous system, characterized by diverse and often debilitating symptoms that manifest in various clusters at disease onset. Understanding these symptom clusters, along with their associated comorbidities and risk factors, is critical for developing targeted interventions that can improve patient outcomes and slow disease progression.

Aim: This study aimed to identify and analyze clusters of onset symptoms in MS patients, exploring their associated characteristics, comorbidities, and risk factors, to inform more personalized treatment approaches.

Methods: A cross-sectional observational study was conducted involving 100 participants diagnosed with MS. Data were collected through patient interviews, medical record reviews, and standardized diagnostic tests. Symptom clusters were identified using cluster analysis, and associations with comorbidities and risk factors were explored using chi-square tests and logistic regression analyses. Statistical analysis was performed using SPSS version 23.0.

Results: Three distinct symptom clusters were identified: Sensory Symptoms (45%), Motor Symptoms (35%), and Visual and Cognitive Symptoms (20%). The Sensory Symptoms cluster had a significant female predominance and was mainly associated with relapsing-remitting MS (RRMS). The Motor Symptoms cluster showed a higher prevalence of smoking and was more often linked to primary progressive MS (PPMS). The Visual and Cognitive Symptoms cluster had the highest prevalence of depression. Significant associations were found between symptom clusters and both comorbidities and risk factors.

Conclusion: The study revealed distinct clusters of onset symptoms in MS, each with unique demographic characteristics, comorbidities, and risk factors. These findings suggest the need for personalized treatment strategies tailored to the specific symptom profiles of MS patients.

Recommendations: Further research should explore the longitudinal impact of these symptom clusters on disease progression and treatment outcomes. Clinicians are encouraged to incorporate these findings into the development of individualized care plans for MS patients, focusing on early intervention strategies that address both physical and mental health needs.

Keywords: Multiple Sclerosis, Symptom Clusters, Comorbidities, Risk Factors, Personalized Treatment