Longitudinal disability curves for predicting the course of relapsing-remitting multiple sclerosis

Satisfaction and adherence with glatiramer acetate 40mg/mL TIW in RRMS after 12 months, and the effect of switching from 20mg/mL QD

BACKGROUND

Patient satisfaction with treatment in relapsing-remitting multiple sclerosis (RRMS) has a direct impact on adherence to treatment and, consequently, upon treatment outcomes and costs. Patient-reported outcomes (PROs) are a common method for determining patient satisfaction in MS and other diseases.

METHODS

The 12-month, open-label, Phase IV CONFIDENCE study assessed patient satisfaction and treatment adherence, using PROs, as well as safety outcomes in patients with RRMS treated with glatiramer acetate (GA). In the previously reported (Cutter et al., 2019) initial 6-month core phase of the study, patients were randomized to receive three-times-weekly (TIW) GA 40 mg/mL (GA40; n = 431) or once-daily GA 20 mg/mL (GA20; n = 430). In the 6-month, single-arm extension phase, 789 patients completing the core phase were treated with GA40 to determine whether benefits observed in the core phase were sustained during the extension phase, to ascertain if switching from GA20 to GA40 resulted in PRO changes, and to assess safety outcomes.

RESULTS

Superior PRO scores for patient satisfaction with treatment, patient perception of treatment convenience, and symptomatic changes (fatigue impact and mental health) observed in the GA40 group versus the GA20 group in the core phase were all maintained in the extension phase. Treatment adherence, significantly greater in the GA40 versus the GA20 group in the core phase, was sustained in patients continuing to receive GA40 in the extension phase, while those who switched from GA20 to GA40 increased their adherence during the extension phase. Safety variables remained consistent throughout the study, with no notable changes observed in patients switching from GA20 to GA40.

CONCLUSIONS

Data from the extension phase of the CONFIDENCE study show that the benefits associated with GA40 treatment in terms of medication satisfaction, treatment convenience perception, symptomatic changes in fatigue impact and mental health status, and treatment adherence were maintained over a 12-month observation period. These results confirm the preferential utility of GA40 versus GA20 in clinical practice, with no additional safety concerns associated with switching from GA20 to GA40.

Modelling disease progression in relapsing-remitting onset multiple sclerosis using multilevel models applied to longitudinal data from two natural history cohorts and one treated cohort

BACKGROUND

The ability to better predict disease progression represents a major unmet need in multiple sclerosis (MS), and would help to inform therapeutic and management choices.

OBJECTIVES

To develop multilevel models using longitudinal data on disease progression in patients with relapsing-remitting MS (RRMS) or secondary-progressive MS (SPMS); and to use these models to estimate the association of disease-modifying therapy (DMT) with progression.

DESIGN

Secondary analysis of three MS cohorts.

SETTING

Two natural history cohorts: University of Wales Multiple Sclerosis (UoWMS) cohort, UK, and British Columbia Multiple Sclerosis (BCMS) cohort, Canada. One observational DMT-treated cohort: UK MS risk-sharing scheme (RSS).

PARTICIPANTS

The UoWMS database has > 2000 MS patients and the BCMS database (as of 2009) has > 5900 MS patients. All participants who had definite MS (RRMS/SPMS), who reached the criteria set out by the Association of British Neurologists (ABN) for eligibility for DMT [i.e. age ≥ 18 years, Expanded Disability Status Scale (EDSS) score of ≤ 6.5, occurrence of two or more relapses in the previous 2 years] and who had at least two repeated outcome measures were included: 404 patients for the UoWMS cohort and 978 patients for the BCMS cohort. Through the UK MS RSS scheme, 5583 DMT-treated patients were recruited, with the analysis sample being the 4137 who had RRMS and were eligible and treated at baseline, with at least one valid EDSS score post baseline.

MAIN OUTCOME MEASURES

EDSS score observations post ABN eligibility.

METHODS

We used multilevel models in the development cohort (UoWMS) to develop a model for EDSS score with time since ABN eligibility, allowing for covariates and appropriate transformation of outcome and/or time. These methods were then applied to the BCMS cohort to obtain a 'natural history' model for changes in the EDSS score with time. We then used this natural history model to predict the trajectories of EDSS score in treated patients in the UK MS RSS database. Differences between the progression predicted by the natural history model and the progression observed at 6 years' follow-up for the UK MS RSS cohort were used as indicators of the effectiveness of the DMTs. Previously developed utility scores were assigned to each EDSS score, and differences in utility also examined.

RESULTS

The model best fitting the UoWMS data showed a non-linear increase in EDSS score over time since ABN eligibility. This model fitted the BCMS cohort data well, with similar coefficients, and the BCMS model predicted EDSS score in UoWMS data with little evidence of bias. Using the natural history model predicts EDSS score in a treated cohort (UK MS RSS) higher than that observed [by 0.59 points (95% confidence interval 0.54 to 0.64 points)] at 6 years post treatment.

LIMITATIONS

Only two natural history cohorts were compared, limiting generalisability. The comparison of a treated cohort with untreated cohorts is observational, thus limiting conclusions about causality.

CONCLUSIONS

EDSS score progression in two natural history cohorts of MS patients showed a similar pattern. Progression in the natural history cohorts was slightly faster than EDSS score progression in the DMT-treated cohort, up to 6 years post treatment.

FUTURE WORK

Long-term follow-up of randomised controlled trials is needed to replicate these findings and examine duration of any treatment effect.

FUNDING DETAILS

The National Institute for Health Research Health Technology Assessment programme.

A web-based decision support tool for prognosis simulation in multiple sclerosis

A multiplicity of natural history studies of multiple sclerosis provides valuable knowledge of the disease progression but individualized prognosis remains elusive. A few decision support tools that assist the clinician in such task have emerged but have not received proper attention from clinicians and patients. The objective of the current work is to implement a web-based tool, conveying decision relevant prognostic scientific evidence, which will help clinicians discuss prognosis with individual patients. Data were extracted from a set of reference studies, especially those dealing with the natural history of multiple sclerosis. The web-based decision support tool for individualized prognosis simulation was implemented with NetLogo, a program environment suited for the development of complex adaptive systems. Its prototype has been launched online; it enables clinicians to predict both the likelihood of CIS to CDMS conversion, and the long-term prognosis of disability level and SPMS conversion, as well as assess and monitor the effects of treatment. More robust decision support tools, which convey scientific evidence and satisfy the needs of clinical practice by helping clinicians discuss prognosis expectations with individual patients, are required. The web-based simulation model herein introduced proposes to be a step forward toward this purpose.

A longitudinal model for disease progression was developed and applied to multiple sclerosis

Objectives

To develop a model of disease progression using multiple sclerosis (MS) as an exemplar.

Study Design and Settings

Two observational cohorts, the University of Wales MS (UoWMS), UK (1976), and British Columbia MS (BCMS) database, Canada (1980), with longitudinal disability data [the Expanded Disability Status Scale (EDSS)] were used; individuals potentially eligible for MS disease-modifying drugs treatments, but who were unexposed, were selected. Multilevel modeling was used to estimate the EDSS trajectory over time in one data set and validated in the other; challenges addressed included the choice and function of time axis, complex observation-level variation, adjustments for MS relapses, and autocorrelation.

Results

The best-fitting model for the UoWMS cohort (404 individuals, and 2,290 EDSS observations) included a nonlinear function of time since onset. Measurement error decreased over time and ad hoc methods reduced autocorrelation and the effect of relapse. Replication within the BCMS cohort (978 individuals and 7,335 EDSS observations) led to a model with similar time (years) coefficients, time [0.22 (95% confidence interval {CI}: 0.19, 0.26), 0.16 (95% CI: 0.10, 0.22)] and log time [−0.13 (95% CI: −0.39, 0.14), −0.15 (95% CI: −0.70, 0.40)] for BCMS and UoWMS, respectively.

Conclusion

It is possible to develop robust models of disability progression for chronic disease. However, explicit validation is important given the complex methodological challenges faced.

An agent-based simulation model for informed shared decision making in multiple sclerosis

Shared decision making (SDM) is concerned with patient involvement into medical decisions and chronic conditions such as Multiple sclerosis (MS), with only partially effective treatments leading to potential severe side effects, conflicting evidence, and uncertain evidence on outcomes, constitute a typical condition for SDM. As treatment options increase and patients participate more intensively in decisions, the need for evidence-based information (EBI) becomes clear. Natural history (NH) studies of MS represent the basic sources for required EBI and are especially useful to contribute to the practical exercise of prognosis formulation and to enable the evaluation of effectiveness in the context of treatment. Several of these identify early clinical factors predictive of the course of MS but there is no consensus method for determining the long term progression of disability and evolution of individual patients on the basis of observations on the early stages of the disease, which constitutes a major challenge for the practicing neurologist. Aiming at delivering more reliable prognosis estimation, this study combines the distribution of patients reaching specific levels of disability within defined time periods as determined in NH studies, with disability curves and severity scores as a function of time, in terms of percentiles and deciles respectively, derived from longitudinal data analysis studies. A computer agent-based simulation model was implemented as a comprehensive and easy to utilize tool able to predict and monitor progression of disability in MS patients, and to support the neurologist discussing prognosis scenarios with the individual patient for effective SDM.

Health-related quality of life as an independent predictor of long-term disability for patients with relapsing-remitting multiple sclerosis

BACKGROUND AND PURPOSE

Predictive factors of long-term disability in patients with relapsing-remitting multiple sclerosis (RR-MS) are well known, but the weight of these factors does not explain the entire change of disability. Few studies have examined the predictive value of quality of life (QoL).

OBJECTIVES

To determine the value of the initial level of QoL to predict changes in the disability status of patients with MS and to determine if specific-MS questionnaires predict more accuracy in these changes than generic questionnaires.

METHODS

DESIGN

multicenter, multi-regional, and longitudinal study. Main inclusion criteria: patients with RR-MS subtype and an Expanded Disability Status Scale (EDSS) score lower than 7.0. Sociodemographic and clinical data were recorded at baseline. Every 6 months up to month 24, QoL (MusiQoL and SF-36) was recorded. At 24 months, individuals were defined into two 'disability change' groups: the worsened and not worsened patients.

RESULTS

Five-hundred and twenty-six patients were enrolled: 386 (83.7%) not worsened and 75 (16.3%) worsened patients at 24 months. The activity of daily living and the relationship with healthcare workers dimensions of MusiQoL questionnaire were independent predictors of change in the EDSS score after 24 months. The physical-functioning dimension of the SF-36 questionnaire predicted independently disability change after 24 months.

CONCLUSIONS

Patient-reported baseline QoL levels provide additional prognostic information on MS disability beyond traditional clinical or sociodemographic factors. These findings reinforce the importance of incorporating a patient's evaluation of their own QoL level during patient monitoring and the assessment of treatment effects.

Possible clinical outcome measures for clinical trials in patients with multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease with both clinical and pathological heterogeneity. The complexity of the MS population has offered challenges to the measurement of MS disease progression in therapeutic trials. The current standard clinical outcome measures are relapse rate, Expanded Disability Severity Scale (EDSS), and the MS Functional Composite (MSFC). These measures each have strengths and some weakness. Two additional measures, the six-minute walk and accelerometry, show promise in augmenting current measures. MS therapeutics is a quickly advancing field which requires sensitive clinical outcome measures that can detect small changes in disability that reliably reflect long-term changes in sustained disease progression in a complex population. A single clinical outcome measure of sustained disease progression may remain elusive. Rather, an integration of current and new outcome measures may be most appropriate and utilization of different measures depending on the MS population and stage of the disease may be preferred.

Progressive multifocal leukoencephalopathy and multiple sclerosis: lessons from natalizumab

Three patients have developed progressive multifocal leukoencephalopathy while being treated with natalizumab for their autoimmune diseases. One patient had relapsing-remitting multiple sclerosis (RRMS), one had Crohn's disease, and one (who had been enrolled in an RRMS phase III trial) had no evidence of multiple sclerosis on autopsy. The patient with RRMS now has severe, permanent neurologic damage and the other two patients died. In this article, we recommend revised entry and diagnostic criteria to prevent enrollment of RRMS patients with a favorable prognosis or questionable diagnosis into trials of drugs with unknown safety profiles. In light of the risk of progressive multifocal leukoencephalopathy, we strongly recommend that RRMS patients who are at low risk of disability not be treated with natalizumab. Finally, we discuss what additional natalizumab efficacy data need to be presented before any decisions should be made about treating RRMS patients with a high risk of developing long-term disability.

Cognitive fatigue in multiple sclerosis: findings from a two-wave screening project

BACKGROUND

Multiple sclerosis (MS) patients commonly suffer from fatigue and define it as one of their most disabling symptom profoundly disrupting their lives. However, the relationship of fatigue to cognitive functions and its impact on quality of life have not been widely studied.

AIM

To define (1) "cognitive fatigue", (2) survey its frequency and (3) characterize severity and impact on quality of life in MS patients in the first 10 years of the disease.

METHODS

A two-wave design was utilized to enrich the studied population in subjects whose fatigue is significant. In the first wave, fatigue was measured by the self-reported fatigue severity scale (FSS) in randomly selected MS patients from our computerized database. Patients responding to the 9th item of the FSS i.e., "Fatigue interferes with my work, family, or social life" by a grade of 3 or higher (of 7) were further assessed (wave two) by the fatigue impact scale (FIS) and the RAYS quality of life questionnaire.

RESULTS

Of the 259 patients that completed the first-wave screening, 158 patients (61%, 118 females, mean age 41.1+/-9.2 years, mean disease duration 6.2+/-5.5 years) satisfied the additional criterion and were defined to suffer from significant fatigue. The great majority of these patients-91.7%-had a relapsing-remitting disease course, mean FIS score was 77+/-25.9 and their mean EDSS was 2.9+/-2.6. Fatigue was reported to occur most of the day in 30.9% of patients, persist in 69% for more than 1 year, and in 59.8%, it was reported not to be associated with effort. No correlations were found between age, gender, disease duration or neurological disability and FIS cognitive subscale score. Significant correlations were found between the FIS cognitive subscale score and the three domains (physical, psychological and social-familial) of the RAYS quality of life questionnaire (p<0.001).

CONCLUSIONS

Cognitive fatigue was found in more than half of MS patients in the first decade from onset that were particularly selected for significant fatigue in their lives. This aspect of fatigue correlated with all quality of life domains and especially with psychological everyday tasks.

Predicting the course of relapsing-remitting MS using longitudinal disability curves

BACKGROUND AND OBJECTIVE

Multiple sclerosis (MS) is a chronic, progressive disease of the central nervous system that generally occurs in adults under the age of 40 years and ultimately leads to severe neurological disability. Following the progression of MS by monitoring changes in disability levels can facilitate treatment decisions taken by physicians. The aim of this review is to present longitudinal disability curves enabling the assessment of disease progression in patients with relapsing-remitting (RR)MS.

METHODS

Patients with a definite diagnosis of MS and an RR disease course were identified using the Multiple Sclerosis Center computerised database. Patients were stratified into major percentile groups based on their Expanded Disability Status Scale (EDSS) score 1 year after disease onset. Model disability curves for each percentile were constructed using mean consecutive EDSS scores for 10 years after disease onset. Model curves were generated by smoothing (parametric and non-parametric regression) and curve approximation (linear regression and moving averages). The predictive ability of model curves was validated by superimposing data from a separate group of patients with RRMS.

RESULTS

Disability curves were constructed using data from 1001 patients. A significant difference between the initial percentile assignment and disability progression was indicated by the log-rank test (p < 0.001). Kaplan-Meier and life table analyses demonstrated the validity of the model in predicting disease progression. The probability of experiencing more severe disability than predicted (i. e. deviating from the initial percentile to a higher percentile over time) ranged from 6.5 % (50th percentile) to 15.4 % (75th percentile), while the probability of experiencing less severe disability than predicted (i. e. deviating from the initially assigned percentile to a lower percentile over time) ranged from 6.9% (50th percentile) to 1.6 % (75th percentile). Both suggest reasonable predictive validity.

CONCLUSION

In MS, longitudinal disability curves can help to assess individual patient disability, map the effects of immunomodulatory treatments over time, and generally build on the overall clinical impression of disease progression. Such models can act as a tool to aid and support the clinical decision-making process. This review is based on the study published in Multiple Sclerosis (2003) 9:486-491.