Prevalence, treatment and correlates of depression in multiple sclerosis.

BACKGROUND: The prevalence of depression in Multiple Sclerosis (MS) is often assessed by administering patient reported outcome measures (PROMs) examining depressive symptomatology to population cohorts; a recent review summarised 12 such studies, eight of which used the Hospital Anxiety and Depression Scale-Depression (HADS-D). In clinical practice, depression is diagnosed by an individual structured clinical interview; diagnosis often leads to treatment options including antidepressant medication. It follows that an MS population will include those whose current depressive symptoms meet threshold for depression diagnosis, plus those who previously met diagnostic criteria for depression and have been treated such that depressive symptoms have improved below that threshold. We examined a large MS population to establish a multi-attribute estimate of depression, taking into account probable depression on HADS-D, as well as anti-depressant medication use and co-morbidity data reporting current treatment for depression. We then studied associations with demographic and health status measures and the trajectories of depressive symptoms over time. METHODS: Participants were recruited into the UK-wide Trajectories of Outcome in Neurological Conditions-MS (TONiC-MS) study, with demographic and disease data from clinical records, PROMs collected at intervals of at least 9 months, as well as co-morbidities and medication. Interval level conversions of PROM data followed Rasch analysis. Logistic regression examined associations of demographic characteristics and symptoms with depression. Finally, a group-based trajectory model was applied to those with depression. RESULTS: Baseline data in 5633 participants showed the prevalence of depression to be 25.3 % (CI: 24.2-26.5). There were significant differences in prevalence by MS subtype: relapsing 23.2 % (CI: 21.8- 24.5), primary progressive 25.8 % (CI: 22.5-29.3), secondary progressive 31.5 % (CI: 29.0-34.0); disability: EDSS 0-4 19.2 % (CI: 17.8-20.6), EDSS ≥4.5 31.9 % (CI: 30.2-33.6); and age: 42-57 years 27.7 % (CI: 26.0-29.3), above or below this range 23.1 % (CI: 21.6-24.7). Fatigue, disability, self-efficacy and self esteem correlated with depression with a large effect size (>0.8) whereas sleep, spasticity pain, vision and bladder had an effect size >0.5. The logistic regression model (N = 4938) correctly classified 80 % with 93 % specificity: risk of depression was increased with disability, fatigue, anxiety, more comorbidities or current smoking. Higher self-efficacy or self esteem and marriage reduced depression. Trajectory analysis of depressive symptoms over 40 months in those with depression (N = 1096) showed three groups: 19.1 % with low symptoms, 49.2 % with greater symptoms between the threshold of possible and probable depression, and 31.7 % with high depressive symptoms. 29.9 % (CI: 27.6-32.3) of depressed subjects were untreated, conversely of those treated, 26.1 % still had a symptom level consistent with a probable case (CI: 23.5-28.9). CONCLUSION: A multi-attribute estimate of depression in MS is essential because using only screening questionnaires, diagnoses or antidepressant medication all under-estimate the true prevalence. Depression affects 25.3 % of those with MS, almost half of those with depression were either untreated or still had symptoms indicating probable depression despite treatment. Services for depression in MS must be pro-active and flexible, recognising the heterogeneity of outcomes and reaching out to those with ongoing symptoms.

Measuring coping in multiple sclerosis: The Coping Index-MS.

BACKGROUND: Coping in multiple sclerosis (MS) refers to cognitive and behavioural efforts to manage stresses imposed by the illness. Existing generic and disease-specific coping scales do not meet modern guidelines for scale development and cannot produce interval-level metrics to allow for change scores. OBJECTIVE: The main aim of this study was to develop a brief patient-reported outcome measure for coping in MS, capable of interval-level measurement. METHODS: Qualitative work in 43 people with MS leads to a draft scale which was administered to 5747 participants, with longitudinal collection in 2290. A calibration sample of 1000 subjects split into development and validation sets was used to generate three scales consistent with Rasch model expectations. RESULTS: The total Coping Index-MS (CI-MS-T), CI-MS-Internal (CI-MS-I) and CI-MS-External (CI-MS-E) cover total, internal and externally focused coping. All three scales are capable of interval-level measurement. Trajectory analysis of 9000 questionnaires showed two trajectories in CI-MS-T: Group 1 showed a low level of coping with slight decline over 40 months, while Group 2 had a better and stable level of coping due to improving CI-MS-I which compensated for the deteriorating CI-MS-E over time. CI-MS-T < 30 identified group membership at baseline. CONCLUSION: The CI-MS-T, CI-MS-I and CI-MS-E, comprising 20 items, provide interval-level measurement and are free-for-use in not-for-profit settings.

The four self-efficacy trajectories among people with multiple sclerosis: Clinical associations and implications.

BACKGROUND: Longitudinal studies among people with Multiple Sclerosis (pwMS) have shown that self-efficacy is linked to physical, cognitive and psychological functioning. OBJECTIVES: To determine the distribution of self-efficacy in a large sample of pwMS, examining whether there are distinct groups which show different self-efficacy trajectories over time, and the health status characteristics of any groups identified. METHODS: Participants completed serial questionnaire packs, including Unidimensional Self-efficacy-MS (USE-MS) scale, for the Trajectories of Outcome in Neurological Conditions-MS (TONiC-MS) study over an average 46-month period. The resulting longitudinal data were analysed by a group-based trajectory model. RESULTS: 5887 pwMS were studied: mean age 50.2 years (SD 12.0); 73.6% female; Relapsing Remitting MS (61.8%), Secondary Progressive (22.9%), Primary Progressive (11.1%), Rapidly Evolving Relapsing Remitting MS (4.2%). Four distinct self-efficacy trajectories emerged, with declining, slightly declining, stable or improving self-efficacy, each showing different patterns of health status indicators such as EQ-5D-5L, disability and depression. USE-MS ≤ 18 at baseline detected all participants in the two declining groups. CONCLUSION: Future trials on interventions for self-efficacy should assume a priori that those with low levels of self-efficacy (USE-MS ≤ 18 at baseline) are likely to be on a declining trajectory and may need different interventions from those with stable self-efficacy.

Quality of life in multiple sclerosis is dominated by fatigue, disability and self-efficacy.

BACKGROUND AND OBJECTIVE: Quality of life in multiple sclerosis (MS) reflects complex relationships between symptoms (fatigue, spasticity pain, and bladder or vision dysfunction), disability, health perceptions, and self-efficacy. METHODS: In this cross-sectional study, a self-report questionnaire pack of patient reported outcome measures was collected from 5695 people with MS (pwMS) alongside clinical data from their neurologists. Each patient reported outcome measure was converted to interval-scaled estimates following fit to the Rasch model. The patient reported outcome measures, as well as perceived health, age, disease subtype and gender, were then subject to path analysis to analyse their relationships with quality of life (QoL), guided by the Wilson and Clearly conceptual framework. RESULTS: The final model explains 81.2% of the variance of QoL. Fatigue is clearly dominant, suggesting a means to intervene and improve QoL. The next most influential factors were disability and self-efficacy, which have similar effect levels. The model can be replicated for pwMS on disease modifying therapy and is largely invariant for gender and disease subtype. Age had an insignificant effect. CONCLUSIONS: In order to promote better QoL, MS care should include management of fatigue, interventions to ameliorate disability, and support to enhance self-efficacy. The range of skills needed for these treatments will require input from medical, nursing, therapy and psychology staff, so these findings provide evidence substantiating the need for pwMS to be provided with care by comprehensive multidisciplinary teams.