Physical and Mental Health–Related Quality of Life Trajectories Among People With Multiple Sclerosis

Abstract

Background and Objectives:Most studies of health-related quality of life (HRQoL) in multiple sclerosis (MS) have been cross-sectional. The few longitudinal studies have not accounted for potential heterogeneity in HRQOL trajectories. There may be groups of individuals with common physical and mental HRQoL trajectories over time. Identification of early risk factors for membership in trajectories with poor HRQoL would inform on those at risk. We aimed to identify physical and mental HRQoL trajectories among people with MS and early risk factors for membership in the trajectory groups with the worst HRQoL.Methods:Between 2004 and 2020, we queried NARCOMS participants regarding HRQoL using the RAND-12, demographics, fatigue, and physical impairments (using Patient Determined Disease Steps). We included participants who were enrolled in the NARCOMS registry within three years of MS diagnosis, lived in the United States, reported physician-confirmed MS, and had ≥3 HRQoL observations. We used group-based trajectory modelling to determine whether there were distinct clusters of individuals who followed similar HRQoL trajectories over time. We evaluated whether baseline participant characteristics associated with the probability of trajectory group membership using a multinomial logit model.Results:We included 4,888 participants who completed 57,564 HRQoL questionnaires between one and 27 years after MS diagnosis. Participants had a mean (SD) age of 41.7 (9.5) years at diagnosis, and 3,978 participants (81%) were women. We identified five distinct physical HRQoL trajectories and four distinct mental HRQoL trajectories. Older age at diagnosis, worse physical impairments, and worse fatigue were associated with increased odds of being in the group with the worst physical HRQoL when compared to the four other groups. Income ≤$50,000 and no post-secondary education were associated with increased odds of membership in the group with the lowest mental HRQoL when compared to the other three groups.Discussion:We identified groups of people with MS who reported similar physical and mental HRQoL trajectories over time. There are early risk factors for membership in the groups with the worst HRQoL that are easily identifiable by clinicians, providing an opportunity for early interventions.

Participants’ perspectives of “NeuroSask: Active and Connect”—a virtual chronic disease management program for individuals with a neurological condition

“…Our findings also align with current literature in people with multiple sclerosis that highlights self-esteem, self-efficacy, resilience, and social support contribute to an improved quality of life ( 39 ). Negative predictors for quality of life in this population include older age at diagnosis, increased fatigue, lack of disease specific information, lack of social support, fun, or entertainment ( 40 , 41 ). In certain cases, our respondents reported on the “fun” nature of NeuroSask as well as increased independence, involvement in other physical activities, becoming more active members of their community, and reporting improvements in their mental health.…”

Long-term trajectories of ambulatory impairment in multiple sclerosis

“…This work adds to the modest literature that has characterized trajectories in MS for depression, Expanded Disability Status Scale, and healthrelated quality of life. 13,[31][32][33][34][35] An important future step would be to examine the relationships across these trajectories, as well as the directionality of these possible relationships. This study is also the largest study population, to our knowledge, in whom trajectories have been modeled.…”

Within-person fluctuations over three years in depression, anxiety, fatigue, and health-related quality of life in multiple sclerosis

“…We cannot assume that if a person who is depressed at one point in time reports lower HRQOL than someone who is not depressed; she or he will necessarily report better HRQoL if the depression subsequently resolves. A recent study used group-based trajectory models to address heterogeneity in the evolution of HRQoL; 29 while this approach identified several distinct subgroups for physical and mental HRQoL, inference at the individual level remained lacking. In contrast, we separately assessed the population-level (average) effects from the within-person effects of changes in symptoms, such as depression and anxiety, which often fluctuate over time.…”