Author Of 2 Presentations
P0450 - Comorbidity patterns in people with multiple sclerosis: A latent class analysis of the Australian Multiple Sclerosis Longitudinal Study (ID 1065)
Abstract
Background
Published studies are designed towards identifying the impact of the total number and individual comorbidities, and therefore limited knowledge exists on the comorbidity patterns and their influence on people with multiple sclerosis (MS).
Objectives
To identify the comorbidity patterns and examine their association with the sociodemographic characteristics of people with MS.
Methods
We conducted latent class analysis (LCA) to identify clinically distinct comorbidity classes in PwMS using the 15 most common comorbidities among 1,518 Australian Multiple Sclerosis Longitudinal Study (AMSLS) participants. The associations between comorbidity classes and sociodemographic characteristics were explored using multinomial logistic regression.
Results
Five classes with distinct comorbidity patterns were identified: “minimally-diseased class” (30.8%) for participants with no or one comorbidity; “metabolic class” (22.7%), “mental health-allergy class” (21.7%), “non-metabolic class” (7.6%) or “severely-diseased class” (7.0%) for participants with higher prevalence of comorbidities. The relative probability (relative risk ratios, 95%CI) of being assigned to other comorbidity classes over the “minimally-diseased class” were significantly increased for participants who were older (metabolic: 1.09 (1.06-1.11); non-metabolic: 1.07 (1.04-1.11); severely-diseased: 1.04 (1.01-1.08)), female (non-metabolic: 5.35 (1.98-14.42); severely-diseased: 2.21 (1.02-4.77)), obese (metabolic: 4.06 (2.45-6.72); mental health-allergy: 1.57 (1.00-2.46); severely-diseased: 4.53 (2.21-9.29)) and had moderate disability (mental health-allergy: 2.32 (1.47-3.64); severely-diseased: 2.65 (1.16-6.04)).
Conclusions
Comorbidities in MS tend to cluster into distinct disease patterns and are associated with some demographics and clinical characteristics. Understanding comorbidity patterns in MS may be used to design more appropriate comorbidity prevention and management strategies.
P0504 - The relative contribution of comorbidities on the severity of symptoms in people with Multiple Sclerosis (ID 1064)
Abstract
Background
The symptoms reported by people with Multiple Sclerosis (MS) vary greatly and are influenced by comorbidities, but our understanding on the contribution of comorbidities on MS symptomatology remains limited.
Objectives
To examine the dose-response relationship between the number of comorbidities and symptoms severity and to assess the relative contribution of comorbidity groups and individual comorbidities to symptoms severity.
Methods
Cross-sectional analysis of data on the presence of 30 comorbidities and the severity of 13 most common symptoms (0-10 scale) of the Australian Multiple Sclerosis Longitudinal Study participants (n=1,223). The dose-response relationship between comorbidities and symptoms severity were assessed using negative binomial regression. The relative contribution of comorbidities to the severity of symptoms was assessed using general dominance analysis.
Results
Higher number of comorbidities was most strongly associated with a higher severity in feelings of anxiety, feelings of depression and pain (ratios of means >0.12 per comorbidity increase). Comorbidities explained between 3.7% (spasticity) and 22.0% (feelings of anxiety) of the total variance of symptoms severity variables. Mental health disorders contributed most strongly to the severity of 6/13 symptoms (feelings of anxiety, feelings of depression, cognitive symptoms, sensory symptoms, fatigue and sexual dysfunction). Musculoskeletal disorders contributed most strongly to the severity of another 6/13 symptoms (pain, walking difficulties, difficulty with balance, bladder problems, bowel problems and spasticity).
Conclusions
Our findings support that early recognition and optimal management of comorbidities, particularly of mental health and musculoskeletal disorders, could have a positive impact on the severity of symptom of people with MS.
Presenter Of 2 Presentations
P0450 - Comorbidity patterns in people with multiple sclerosis: A latent class analysis of the Australian Multiple Sclerosis Longitudinal Study (ID 1065)
Abstract
Background
Published studies are designed towards identifying the impact of the total number and individual comorbidities, and therefore limited knowledge exists on the comorbidity patterns and their influence on people with multiple sclerosis (MS).
Objectives
To identify the comorbidity patterns and examine their association with the sociodemographic characteristics of people with MS.
Methods
We conducted latent class analysis (LCA) to identify clinically distinct comorbidity classes in PwMS using the 15 most common comorbidities among 1,518 Australian Multiple Sclerosis Longitudinal Study (AMSLS) participants. The associations between comorbidity classes and sociodemographic characteristics were explored using multinomial logistic regression.
Results
Five classes with distinct comorbidity patterns were identified: “minimally-diseased class” (30.8%) for participants with no or one comorbidity; “metabolic class” (22.7%), “mental health-allergy class” (21.7%), “non-metabolic class” (7.6%) or “severely-diseased class” (7.0%) for participants with higher prevalence of comorbidities. The relative probability (relative risk ratios, 95%CI) of being assigned to other comorbidity classes over the “minimally-diseased class” were significantly increased for participants who were older (metabolic: 1.09 (1.06-1.11); non-metabolic: 1.07 (1.04-1.11); severely-diseased: 1.04 (1.01-1.08)), female (non-metabolic: 5.35 (1.98-14.42); severely-diseased: 2.21 (1.02-4.77)), obese (metabolic: 4.06 (2.45-6.72); mental health-allergy: 1.57 (1.00-2.46); severely-diseased: 4.53 (2.21-9.29)) and had moderate disability (mental health-allergy: 2.32 (1.47-3.64); severely-diseased: 2.65 (1.16-6.04)).
Conclusions
Comorbidities in MS tend to cluster into distinct disease patterns and are associated with some demographics and clinical characteristics. Understanding comorbidity patterns in MS may be used to design more appropriate comorbidity prevention and management strategies.
P0504 - The relative contribution of comorbidities on the severity of symptoms in people with Multiple Sclerosis (ID 1064)
Abstract
Background
The symptoms reported by people with Multiple Sclerosis (MS) vary greatly and are influenced by comorbidities, but our understanding on the contribution of comorbidities on MS symptomatology remains limited.
Objectives
To examine the dose-response relationship between the number of comorbidities and symptoms severity and to assess the relative contribution of comorbidity groups and individual comorbidities to symptoms severity.
Methods
Cross-sectional analysis of data on the presence of 30 comorbidities and the severity of 13 most common symptoms (0-10 scale) of the Australian Multiple Sclerosis Longitudinal Study participants (n=1,223). The dose-response relationship between comorbidities and symptoms severity were assessed using negative binomial regression. The relative contribution of comorbidities to the severity of symptoms was assessed using general dominance analysis.
Results
Higher number of comorbidities was most strongly associated with a higher severity in feelings of anxiety, feelings of depression and pain (ratios of means >0.12 per comorbidity increase). Comorbidities explained between 3.7% (spasticity) and 22.0% (feelings of anxiety) of the total variance of symptoms severity variables. Mental health disorders contributed most strongly to the severity of 6/13 symptoms (feelings of anxiety, feelings of depression, cognitive symptoms, sensory symptoms, fatigue and sexual dysfunction). Musculoskeletal disorders contributed most strongly to the severity of another 6/13 symptoms (pain, walking difficulties, difficulty with balance, bladder problems, bowel problems and spasticity).
Conclusions
Our findings support that early recognition and optimal management of comorbidities, particularly of mental health and musculoskeletal disorders, could have a positive impact on the severity of symptom of people with MS.