Quality of life and patient preferences: identification of subgroups of multiple sclerosis patients

Key Drivers and Facilitators of the Choice to Use mHealth Technology in People With Neurological Conditions: Observational Study

Background

There is increasing interest in the potential uses of mobile health (mHealth) technologies, such as wearable biosensors, as supplements for the care of people with neurological conditions. However, adherence is low, especially over long periods. If people are to benefit from these resources, we need a better long-term understanding of what influences patient engagement. Previous research suggests that engagement is moderated by several barriers and facilitators, but their relative importance is unknown.

Objective

To determine preferences and the relative importance of user-generated factors influencing engagement with mHealth technologies for 2 common neurological conditions with a relapsing-remitting course: multiple sclerosis (MS) and epilepsy.

Methods

In a discrete choice experiment, people with a diagnosis of MS (n=141) or epilepsy (n=175) were asked to select their preferred technology from a series of 8 vignettes with 4 characteristics: privacy, clinical support, established benefit, and device accuracy; each of these characteristics was greater or lower in each vignette. These characteristics had previously been emphasized by people with MS and or epilepsy as influencing engagement with technology. Mixed multinomial logistic regression models were used to establish which characteristics were most likely to affect engagement. Subgroup analyses explored the effects of demographic factors (such as age, gender, and education), acceptance of and familiarity with mobile technology, neurological diagnosis (MS or epilepsy), and symptoms that could influence motivation (such as depression).

Results

Analysis of the responses to the discrete choice experiment validated previous qualitative findings that a higher level of privacy, greater clinical support, increased perceived benefit, and better device accuracy are important to people with a neurological condition. Accuracy was perceived as the most important factor, followed by privacy. Clinical support was the least valued of the attributes. People were prepared to trade a modest amount of accuracy to achieve an improvement in privacy, but less likely to make this compromise for other factors. The type of neurological condition (epilepsy or MS) did not influence these preferences, nor did the age, gender, or mental health status of the participants. Those who were less accepting of technology were the most concerned about privacy and those with a lower level of education were prepared to trade accuracy for more clinical support.

Conclusions

For people with neurological conditions such as epilepsy and MS, accuracy (ie, the ability to detect symptoms) is of the greatest interest. However, there are individual differences, and people who are less accepting of technology may need far greater reassurance about data privacy. People with lower levels of education value greater clinician involvement. These patient preferences should be considered when designing mHealth technologies.

Patient-based benefit-risk assessment of medicines: development, refinement, and validation of a content search strategy to retrieve relevant studies

Introduction:

Poor indexing and inconsistent use of terms and keywords may prevent efficient retrieval of studies on the patient-based benefit-risk assessment (BRA) of medicines. We aimed to develop and validate an objectively derived content search strategy containing generic search terms that can be adapted for any search for evidence on patient-based BRA of medicines for any therapeutic area.

Methods:

We used a robust multistep process to develop and validate the content search strategy: (1) we developed a bank of search terms derived from screening studies on patient-based BRA of medicines in various therapeutic areas, (2) we refined the proposed content search strategy through an iterative process of testing sensitivity and precision of search terms, and (3) we validated the final search strategy in PubMed by firstly using multiple sclerosis as a case condition and secondly computing its relative performance versus a published systematic review on patient-based BRA of medicines in rheumatoid arthritis.

Results:

We conceptualized a final search strategy to retrieve studies on patient-based BRA containing generic search terms grouped into two domains, namely the patient and the BRA of medicines (sensitivity 84%, specificity 99.4%, precision 20.7%). The relative performance of the content search strategy was 85.7% compared with a search from a published systematic review of patient preferences in the treatment of rheumatoid arthritis. We also developed a more extended filter, with a relative performance of 93.3% when compared with a search from a published systematic review of patient preferences in lung cancer.

Integrating patient-reported outcomes and quantitative timed tasks to identify relapsing remitting multiple sclerosis patient subgroups: a latent profile analysis

BACKGROUND

Multiple sclerosis (MS) patients experience wide-ranging symptoms with varied severity, and approaches that integrate patient-reported outcomes and objective quantitative measures will present opportunities for advancing clinical profiling. The primary objective of the current study was to conduct exploratory data analysis using latent variable modeling to empirically identify clusters of relapsing remitting (RR) MS patients with shared impairment patterns across three patient-reported outcomes and two timed task measures.

METHODS

Latent profile analyses and impairment data for 2,012 RRMS patients identified distinct patient clusters using timed task measures of upper and lower limb performance, and patient-reported outcomes measuring quality of life, depression symptom severity, and perceived global disability. Multinomial logistic regression models were used to characterize associations between socio-demographic attributes and assignment to the patient clusters.

RESULTS

There were 6 distinct clusters of RRMS patients that differed by symptom patterns, and by their socio-demographic attributes. Most notable were were no differences in age, sex, or disease duration between the least and most impaired classes, representing 14% and 4% of patients, respectively. Patients in the most impaired class were much more likely to be Black American, have a history of smoking, have a higher body mass index, and be of lower socioeconomic status than the least impaired class. There were positive relationships between age and classification to clusters of increasing moderately severe impairment but not the most severe clusters.

CONCLUSION

We present a framework for discerning phenotypic impairment clusters in RRMS. The results demonstrate opportunities for advancing clinical profiling, which is necessary for optimizing personalized MS care models and clinical research.

Multiple Sclerosis Performance Test: Technical Development and Usability

Introduction

In the clinic, the assessment of patients with multiple sclerosis (MS) is typically qualitative and non-standardized.

Objectives

To describe the MS Performance Test (MSPT), an iPad Air^® 2 (Apple, Cupertino, CA, USA)-based neurological assessment platform allowing patients to input relevant information without the aid of a medical technician, creating a longitudinal, clinically meaningful, digital medical record. To report results from human factor (HF) and usability studies, and the initial large-scale implementation in a practice setting.

Methods

The HF study examined use-error patterns in small groups of MS patients and healthy controls (n = 14), the usability study assessed the effectiveness of patient interaction with the tool by patients with a range of MS disability (n = 60) in a clinical setting, and the implementation study deployed the MSPT across a diverse population of patients (n = 1000) in a large MS center for routine clinical care.

Results

MSPT assessments were completed by all users in the HF study; minor changes to design were recommended. In the usability study, 73% of patients with MS completed the MSPT, with an average administration time of 32 min; 85% described their experience with the tool as satisfactory. In the initial implementation for routine care, 84% of patients with MS completed the MSPT, with an average administration time of 28 min.

Conclusion

Patients with MS with varying disability levels completed the MSPT with minimal or no supervision, resulting in comprehensive, efficient, standardized, quantitative, clinically meaningful data collection as part of routine medical care, thus allowing for large-scale, real-world evidence generation.

Funding

Biogen.

Trial Registration

NCT02664324.

Electronic supplementary material

The online version of this article (10.1007/s12325-019-00958-x) contains supplementary material, which is available to authorized users.

A Systematic Review of Discrete-Choice Experiments and Conjoint Analysis Studies in People with Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic disabling, inflammatory, and degenerative disease of the central nervous system that, in most cases, requires long-term disease-modifying treatment (DMT). The drugs used vary in efficacy and adverse effect profiles. Several studies have used attribute-based stated-preference methods, primarily to investigate patient preferences for initiating or escalating DMT.

OBJECTIVES

To conduct a systematic review of attribute-based stated-preference studies in people with MS to identify common methods employed and to assess study quality, with reference to the specific challenges of this disease area.

METHODS

We conducted a systematic search for studies related to attribute-based stated-preference and MS in multiple databases, including Cochrane and MEDLINE. Studies were included if they were published in a peer-reviewed journal, were on the topic of MS, and used a survey methodology that measured stated preferences for attributes of a whole. Analysis was conducted using narrative synthesis and summary statistics. Study quality was judged against the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) conjoint analysis checklist.

RESULTS

We identified 16 relevant articles reporting 17 separate studies, all but one focusing on DMTs. Most studies were discrete-choice experiments. Study quality was generally high, but we recommend the following: (1) that consideration of sample sizes be improved, (2) that survey design choices be justified and documented, (3) that qualitative approaches for attribute and level selection be incorporated to better involve patients, and (4) that reporting of experimental practice be improved. The effects of DMTs on reproduction and the impact of how risk and uncertainty are presented were identified as neglected research topics. The ISPOR conjoint analysis checklist was found to be unsuitable for the assessment of study quality.

CONCLUSION

Attribute-based stated preference is a useful method with which to examine the preferences of people with MS in their choice of DMT. However, further research embracing the methodological recommendations identified, particularly greater use of qualitative methods in attribute development, is needed.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.

PREFERENCES OF PATIENTS WITH MULTIPLE SCLEROSIS FOR ATTRIBUTES OF INJECTABLE MULTIPLE SCLEROSIS TREATMENTS IN THE UNITED KINGDOM AND FRANCE

Objectives:

Adherence to injectable disease-modifying treatments in patients with multiple sclerosis (MS) impacts outcomes and can be influenced by perceptions of treatment efficacy, side effects, injection frequency, and the duration of injection. This study aimed to quantify preferences for selected attributes of injectable treatments among individuals with MS in the United Kingdom and France.

Methods:

Respondents with a self-reported diagnosis of MS completed an online discrete-choice-experiment survey, consisting of a series of treatment-choice questions. Each choice question presented two hypothetical treatments, each with six attributes (years until disability progression, relapses in the next 4 years, injection time, injection frequency, flu-like symptoms (FLS), and injection-site reactions), each with various levels. Mixed-logit regression analysis was used to estimate preference weights for attribute levels and to calculate the relative importance of changes in treatment attributes (vertical distance between preference weights). Minimum acceptable efficacy estimates indicate improvement in efficacy that respondents would require in exchange for worsening injection frequency and FLS.

Results:

In both countries, 100 respondents completed the survey. In the United Kingdom and France, respectively, improving the time until disability progression from 2 to 4 years, reducing injection frequency from “daily” to “every 2 weeks”, and reducing FLS from 3 days after every injection to none had a relative importance of 2.9 and 2.6, 3.0 and 3.5, and 2.5 and 3.1. Given the ranges included in the study, changes in these attributes were more important than most changes in other attributes assessed.

Conclusions:

Reductions in the injection frequency of MS treatments and FLS can be as important to patients as improvements in treatment efficacy.

Assessing Rationality in Discrete Choice Experiments in Health: An Investigation into the Use of Dominance Tests

BACKGROUND

Dominance tests are often applied to test for the rationality in the choice behavior of participants in discrete choice experiments (DCEs).

OBJECTIVES

To examine how dominance tests have been implemented in recent DCE applications in health and discuss their theoretical and empirical interpretation.

METHODS

Health-related DCEs published in 2015 were reviewed for the inclusion of tests on choice behavior. For studies that implemented a dominance test, information on application and interpretation of the test was extracted. Authors were contacted for test choice sets and observed proportions of subjects who chose the dominated option. Coefficients corresponding to the choice set were extracted to estimate the expected probability of choosing the dominated option with a logistic model and compared with the observed proportion. The theoretical range of expected probabilities of possible dominance tests was calculated.

RESULTS

Of 112 health-related DCEs, 49% included at least one test for choice behavior; 28 studies (25%) included a dominance test. The proportion of subjects in each study who chose the dominated option ranged from 0% to 21%. In 46% of the studies, the dominance test led to the exclusion of participants. In the 15 choice sets that were analyzed, 2 had larger proportions of participants choosing the dominated option than expected (P < 0.05).

CONCLUSIONS

Although dominance tests are frequently applied in DCEs, there is no consensus on how to account for them in data analysis and interpretation. Comparison of expected and observed proportions of participants failing the test might be indicative of DCE quality.

Identifying priority outcomes that influence selection of disease-modifying therapies in MS

Background

Persons with multiple sclerosis (MS) may now choose from a broad array of approved disease-modifying treatments (DMTs). The priority that patients and practitioners assign to specific clinical outcomes is likely to influence the MS DMT selection process.

Methods

We invited 9,126 participants in the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry and 18 members of the American Academy of Neurology MS DMT guideline development panel to complete a brief survey prioritizing outcomes of importance to MS DMT selection. The frequency of outcomes ranked as first, second, or third priority by respondents were compared across groups.

Results

A total of 2,056 of 9,126 (23.6%) NARCOMS participants and all 18 members of the MS DMT guideline development panel (100%) completed the survey. Reduced disability progression was identified as a priority by a majority of respondents in both groups. Guideline panelists tended to be more likely than persons with MS to prioritize relapse rate reduction (p = 0.055). Respondents from both groups commonly cited the "selection of therapies most likely to lead to improvements in quality of life measures, MS symptoms, and preservation of cognition" as top priorities in DMT selection; however, these priority outcomes were reported in fewer than 20% of clinical trials used to inform MS DMT guideline development.

Conclusion

Specific outcomes were defined by similar proportions of persons with MS and guideline panelists as priority outcomes influencing MS DMT selection. Several of these priority outcomes were not routinely reported in clinical trials, identifying areas for future evidence development.

Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review

BACKGROUND

Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood.

OBJECTIVE

We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications.

METHODS

We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist.

RESULTS

We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p > 0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences between classes. Less than half of the studies reported that individual characteristics were included in the segmentation models, and 30% reported that post-estimation analyses were conducted to examine class characteristics. While a higher percentage of studies discussed clinical implications of the segmentation results, an increasing number of studies proposed policy recommendations based on segmentation results since 2010.

CONCLUSIONS

LCA is increasingly used to study preference heterogeneity in health and support decision-making. However, there is little consensus on best practices as its application in health is relatively new. With an increasing demand to study preference heterogeneity, guidance is needed to improve the quality of applications of segmentation methods in health to support policy development and clinical practice.

Preferences for Multiple Sclerosis Treatments: Using a Discrete-Choice Experiment to Examine Differences Across Subgroups of US Patients

BACKGROUND

The growing number of treatments for relapsing multiple sclerosis (MS) provides opportunities to consider patient preferences in treatment decisions.

METHODS

We designed a Web-based, discrete-choice experiment survey to analyze treatment preferences in patients with relapsing-remitting MS (RRMS). The survey presented hypothetical MS treatments defined by six attributes: risk of MS progression, time between relapses, risk of serious infection, treatment-related flu-like symptoms and gastrointestinal symptoms, and route and frequency of administration. Preference weights estimated with random-parameters logit were used to calculate importance scores and preference shares among three pairs of subsamples.

RESULTS

Patients with a self-reported physician diagnosis of RRMS (N = 301) completed the survey: 56% rated their disability level as normal or mild; 43% currently used a self-injectable treatment. Respondents with normal or mild disability levels placed greater weight on avoiding injections with flu-like symptoms and risk of progression, whereas patients with worse disability placed greater weight on reducing risk of progression and risk of serious infection. Patients taking injectables placed the most weight on risk of progression and risk of serious infection, whereas respondents not taking injectables placed the most weight on route and frequency of administration. Differences in preferences between subgroups were significant (P < .05). The presence of common adverse events associated with daily pills and injectables altered predicted preferences for route of administration.

CONCLUSIONS

Preferences of patients with RRMS varied depending on current treatment and disability level, especially regarding mode of administration. Considering patient preferences for treatment features may lead to higher treatment satisfaction and adherence.