Comorbidity patterns in people with multiple sclerosis: A latent class analysis of the Australian Multiple Sclerosis Longitudinal Study

Health, Wellness, and the Effect of Comorbidities on the Multiple Sclerosis Disease Course: Tackling the Modifiable

Multiple sclerosis (MS) is a disease of the central nervous system characterized by inflammatory demyelination and neurodegeneration. Numerous disease-modifying therapies for MS exist but are only partially effective, making it essential to optimize all factors that may influence the course of the disease. This includes conscientious management of both mental and physical comorbidities, as well as a comprehensive strategy for promoting wellness in patients with MS. Thoughtful engagement of those living with MS through shared decision making and involvement of a multidisciplinary team that includes primary care, relevant specialists, psychology, and rehabilitation is likely to lead to better outcomes.

A mixture model for differentiating longitudinal courses of multiple sclerosis

BACKGROUND

Multiple sclerosis has a broad spectrum of clinical courses. Early identification of patients at greater risk of accumulating disability is essential.

OBJECTIVES

Identify groups of patients with similar presentation through a mixture model and predict their trajectories over the years.

METHODS

Retrospective study of patients from 1994 to 2019. We performed a latent profile analysis followed by a latent transition analysis based on eight parameters: age, disease duration, EDSS, number of relapses, multi-topographic symptoms, motor impairment, sphincter impairment, and infratentorial lesions.

RESULTS

We included 629 patients, regardless of the phenotypical classification. We identified three distinct groups at the beginning and end of the follow-up. The three-classes model disclosed the "No disability regardless disease duration" (NDRDD) class with low EDSS and younger patients, the "Disability within a short disease duration" (DSDD) class with the worse disability besides short illness, and the "Disability within a long disease duration" (DLDD) class that achieved high EDSS over a long disease duration. EDSS, disease duration, and no sphincter impairment had the best entropy to distinguish classes at the initial presentation. Over time, the patients from NDRDD had a 52.1 % probability of changing to DLDD and 7.7 % of changing to DSDD.

CONCLUSIONS

We identified three groups of clinical presentations and their evolution over time based on considered prognostic factors. The most likely transition is from NDRDD to DLDD.

Building a monitoring matrix for the management of multiple sclerosis

Multiple sclerosis (MS) has a longitudinal and heterogeneous course, with an increasing number of therapy options and associated risk profiles, leading to a constant increase in the number of parameters to be monitored. Even though important clinical and subclinical data are being generated, treating neurologists may not always be able to use them adequately for MS management. In contrast to the monitoring of other diseases in different medical fields, no target-based approach for a standardized monitoring in MS has been established yet. Therefore, there is an urgent need for a standardized and structured monitoring as part of MS management that is adaptive, individualized, agile, and multimodal-integrative. We discuss the development of an MS monitoring matrix which can help facilitate data collection over time from different dimensions and perspectives to optimize the treatment of people with MS (pwMS). In doing so, we show how different measurement tools can combined to enhance MS treatment. We propose to apply the concept of patient pathways to disease and intervention monitoring, not losing track of their interrelation. We also discuss the use of artificial intelligence (AI) to improve the quality of processes, outcomes, and patient safety, as well as personalized and patient-centered care. Patient pathways allow us to track the patient's journey over time and can always change (e.g., when there is a switch in therapy). They therefore may assist us in the continuous improvement of monitoring in an iterative process. Improving the monitoring process means improving the care of pwMS.

The influence of disease-modifying therapy on hidden disability burden in people with newly diagnosed relapsing-remitting multiple sclerosis

BACKGROUND

In addition to motor disability, "hidden disability" such as depression, anxiety, fatigue, sleep disturbance, cognitive impairment and pain is a major complaint of people with multiple sclerosis. We explored changes in hidden disability burden in the early post-diagnostic period and examined the hypothesis that disease modifying therapies have a beneficial effect on hidden disability burden.

METHODS

Adults with recently diagnosed (< 6 months) relapsing-remitting multiple sclerosis (n = 440, mean age 37.4 ± 10.4, 76% female), from a national multicentre cohort study (FutureMS) underwent testing with clinical and neuropsychological instruments as well as brain MRI at baseline and after 12-months. Disease modifying therapies were only started after baseline assessment and were classified into injectables (n = 70, interferons, glatiramer acetate), other DMTs (n = 215) and no DMT (n = 117, reference). Sensitivity analyses were undertaken using alternative classifications (disease modifying therapy vs none, and a 3-category system). We performed latent transition analysis with hidden disability burden as the latent variable including propensity score weights.

RESULTS

We identified three classes with low (58%), moderate (25%) and high (17%) hidden disability burden. 70% did not transition ("unchanged", reference), 26% transitioned into a lower burden class ("improvement") and 4% transitioned into a higher burden class ("worsening"). Median treatment duration was 11 months (IQR 9-12). Injectables [OR 1.3 (95%CIs 0.7, 2.3); P = 0.4] and other DMTs [OR 1.4 (95%CIs 0.9, 2.1); P = 0.2] were not associated with significant change in hidden disability burden in either direction ("improvement" or "worsening"). In the alternative 3-category classification, category 2 treatment (fingolimod, cladribine, n = 22) was associated with improvement [OR 4.3 (2.6, 7.0); P < 0.001].

CONCLUSION

Hidden disability was present in most newly diagnosed people with multiple sclerosis. The majority remained unchanged and approximately a quarter improved over the immediate post-diagnostic period. Disease modifying therapy had no significant influence on hidden disability burden in the study period of one year following diagnosis. The trend towards favourable outcomes with fingolimod and cladribine should be interpreted with caution due to the small sample size. Our exploratory data are observational, with scope for attendant biases, but highlight the need for further study including longer-term evaluation as well as randomised trials for non-motor disability.

Physical activity participation in Australians with multiple sclerosis: associations with geographical remoteness

PURPOSE

Physical activity (PA) participation offers many benefits for persons with multiple sclerosis (MS). Persons with MS are significantly less active than the general population; however, there is insufficient evidence regarding the association between geographical remoteness and PA participation in persons with MS. We identify PA levels across levels of rurality in an Australian MS population.

MATERIALS AND METHODS

The Australian MS Longitudinal Study collects regular survey data from persons with MS in Australia, including demographic, clinical, and health behavioural data. Physical activity engagement was identified with the International Physical Activity Questionnaire-short form and geographical remoteness was identified from participants' postcode using the Access and Remoteness Index for Australia. Hurdle regression analysis examined the relationship between remoteness and PA participation, and level of PA, after controlling for confounding.

RESULTS

Data from 1260 respondents showed that 24% of persons with MS did not participate in any PA. Remoteness was not associated with the participation in any PA (OR 1.04; 89% highest density probability interval (HDPI) estimate 0.88, 1.22). Amongst those with any PA (n = 960), those living in more remote areas had, on average, higher levels of PA (RR 1.21; 89% HDPI estimate 1.11, 1.34).

CONCLUSIONS

Physical activity promotion does not need to differ based on geographical location. Implications for rehabilitationAlmost one quarter of persons with MS in our study recorded no participation in any physical activity (PA).Healthcare practitioners are encouraged to include the promotion of PA as part of MS management.Physical activity participation is similar for persons with MS across different geographical locations.Physical activity promotion does not need to differ based on geographical location.