Optical coherence tomography versus other biomarkers: Associations with physical and cognitive disability in multiple sclerosis.

BACKGROUND: Optical coherence tomography (OCT) is a biomarker of neuroaxonal loss in multiple sclerosis (MS). OBJECTIVE: The objective was to assess the relative role of OCT, next to magnetic resonance imaging (MRI) and serum markers of disability in MS. METHODS: A total of 100 patients and 52 controls underwent OCT to determine peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform layers (GCIPL). Serum neurofilament light chain (sNfL), total lesion volume (TLV), and brain parenchymal fraction (BPF) were also assessed. The associations of OCT with disability were examined in linear regression models with correction for age, vision, and education. RESULTS: In patients, pRNFL was associated with the Symbol Digit Modalities Test (SDMT; p = 0.030). In the multivariate analysis including sNfL and MRI measures, pRNFL (ß = 0.19, p = 0.044) and TLV (ß = -0.24, p = 0.023) were the only markers associated with the SDMT. pRNFL (p < 0.001) and GCIPL (p < 0.001) showed associations with the Expanded Disability Status Scale (EDSS). In the multivariate analysis, GCIPL showed the strongest association with the EDSS (ß = -0.32, p < 0.001) followed by sNfL (ß = 0.18, p = 0.024). CONCLUSION: The associations of OCT measures with cognitive and physical disability were independent of serum and brain MRI markers of neuroaxonal loss. OCT can be an important tool for stratification in MS, while longitudinal studies using combinations of biomarkers are warranted.

Practice Effects of Mobile Tests of Cognition, Dexterity, and Mobility on Patients With Multiple Sclerosis: Data Analysis of a Smartphone-Based Observational Study.

BACKGROUND: Smartphones and their built-in sensors allow for measuring functions in disease-related domains through mobile tests. This could improve disease characterization and monitoring, and could potentially support treatment decisions for multiple sclerosis (MS), a multifaceted chronic neurological disease with highly variable clinical manifestations. Practice effects can complicate the interpretation of both improvement over time by potentially exaggerating treatment effects and stability by masking deterioration. OBJECTIVE: The aim of this study is to identify short-term learning and long-term practice effects in 6 active tests for cognition, dexterity, and mobility in user-scheduled, high-frequency smartphone-based testing. METHODS: We analyzed data from 264 people with self-declared MS with a minimum of 5 weeks of follow-up and at least 5 repetitions per test in the Floodlight Open study, a self-enrollment study accessible by smartphone owners from 16 countries. The collected data are openly available to scientists. Using regression and bounded growth mixed models, we characterized practice effects for the following tests: electronic Symbol Digit Modalities Test (e-SDMT) for cognition; Finger Pinching and Draw a Shape for dexterity; and Two Minute Walk, U-Turn, and Static Balance for mobility. RESULTS: Strong practice effects were found for e-SDMT (n=4824 trials), Finger Pinching (n=19,650), and Draw a Shape (n=19,019) with modeled boundary improvements of 40.8% (39.9%-41.6%), 86.2% (83.6%-88.7%), and 23.1% (20.9%-25.2%) over baseline, respectively. Half of the practice effect was reached after 11 repetitions for e-SDMT, 28 repetitions for Finger Pinching, and 17 repetitions for Draw a Shape; 90% was reached after 35, 94, and 56 repetitions, respectively. Although baseline performance levels were highly variable across participants, no significant differences between the short-term learning effects in low performers (5th and 25th percentile), median performers, and high performers (75th and 95th percentile) were found for e-SDMT up to the fifth trial (ß=1.50-2.00). Only small differences were observed for Finger Pinching (ß=1.25-2.5). For U-Turn (n=15,051) and Static Balance (n=16,797), only short-term learning effects could be observed, which ceased after a maximum of 5 trials. For Two Minute Walk (n=14,393), neither short-term learning nor long-term practice effects were observed. CONCLUSIONS: Smartphone-based tests are promising for monitoring the disease trajectories of MS and other chronic neurological diseases. Our findings suggest that strong long-term practice effects in cognitive and dexterity functions have to be accounted for to identify disease-related changes in these domains, especially in the context of personalized health and in studies without a comparator arm. In contrast, changes in mobility may be more easily interpreted because of the absence of long-term practice effects, even though short-term learning effects might have to be considered.

Assessment of cognitive performance in multiple sclerosis using smartphone-based training games: a feasibility study.

BACKGROUND: Cognitive impairment occurs in up to 70% of people with MS (pwMS) and has a large impact on quality of life and working capacity. As part of the development of a smartphone-app (dreaMS) for monitoring MS disease activity and progression, we assessed the feasibility and acceptance of using cognitive games as assessment tools for cognitive domains. METHODS: We integrated ten cognitive games in the dreaMS app. Participants were asked to play these games twice a week for 5 weeks. All subjects underwent a battery of established neuropsychological tests. User feedback on acceptance was obtained via a five-point Likert-scale questionnaire. We correlated game performance measures with predetermined reference tests (Spearman's rho) and analyzed differences between pwMS and Healthy Controls (rank biserial correlation). RESULTS: We included 31 pwMS (mean age 43.4 ± 12.0 years; 68% females; median Expanded Disability Status Scale score 3.0, range 1.0-6.0) and 31 age- and sex-matched HC. All but one game showed moderate-strong correlations with their reference tests, (|rs|= 0.34-0.77). Performance improved in both groups over the 5 weeks. Average ratings for overall impression and meaningfulness were 4.6 (range 4.2-4.9) and 4.7 (range 4.5-4.8), respectively. CONCLUSION: Moderate-strong correlations with reference tests suggest that adaptive cognitive games may be used as measures of cognitive domains. The practice effects observed suggest that game-derived measures may capture change over time. All games were perceived as enjoyable and meaningful, features crucial for long-term adherence. Our results encourage further validation of adaptive cognitive games as monitoring tools for cognition in larger studies of longer duration. STUDY REGISTER: ClinicalTrials.gov: NCT04413032.

Smartwatch-derived sleep and heart rate measures complement step counts in explaining established metrics of MS severity.

BACKGROUND: Passive remote monitoring of patients with MS (PwMS) with sensor-based wearable technologies promises near-continuous evaluation with high ecological validity. Step counts correlate strongly with traditional measures of MS severity. We hypothesized that remote monitoring of sleep and heart rate will yield complementary information. METHODS: We recruited 31 PwMS and 31 age- and sex-matched healthy volunteers (HV) as part of the dreaMS feasibility study (NCT04413032). Fitbit Versa 2 smartwatches were worn for 6 weeks and provided a total of 25 features for activity, heart rate, and sleep. Features were selected based on their pairwise intercorrelation (Pearson |r| < 0.6), test-retest reliability (intraclass correlation coefficient ≥ 0.6 or median coefficient of variation < 0.2) and group comparisons between HV and PwMS with moderate disability (expanded disability status scale (EDSS) ≥ 3.5) (rank-biserial |r| ≥ 0.5). These selected features were correlated with clinical reference tests (EDSS, timed 25-foot walk (T25FW), MS-walking scale (MSWS-12)) in PwMS, and multivariate models adjusted for age, sex, and disease duration were compared. RESULTS: We analyzed 28 PwMS (68% female, mean age 44 years, median EDSS 3.0) and 26 HV in our primary analysis. The objectively selected features discriminated well between HV and PwMS with moderate disability with rank-biserial r = 0.83 for Total number of steps, 0.51 for Deep sleep proportion, -0.51 for Median heart rate, 0.85 for Proportion very active, and 0.65 for Total number of floors. In PwMS they correlated strongly with the three clinical reference tests EDSS (strongest Spearman ρ = -0.75 for Proportion very active), T25FW (-0.75 for Total number of floors), and MSWS-12 (-0.72 for Total number of floors). Deep sleep proportion and Median heart rate complemented Total number of steps in explaining the variance of reference tests. CONCLUSIONS: Activity, deep sleep and heart rate measures can be derived reliably from smartwatches and contain independent clinically meaningful information about MS severity, highlighting their potential for continuous passive monitoring in both clinical trials and clinical care of PwMS.

Reliability and acceptance of dreaMS, a software application for people with multiple sclerosis: a feasibility study.

BACKGROUND: There is an unmet need for reliable and sensitive measures for better monitoring people with multiple sclerosis (PwMS) to detect disease progression early and adapt therapeutic measures accordingly. OBJECTIVE: To assess reliability of extracted features and meaningfulness of 11 tests applied through a smartphone application ("dreaMS"). METHODS: PwMS (age 18-70 and EDSS ≤ 6.5) and matched healthy volunteers (HV) were asked to perform tests installed on their smartphone once or twice weekly for 5 weeks. Primary outcomes were test-retest reliability of test features (target: intraclass correlation [ICC] ≥ 0.6 or median coefficient of variation [mCV] < 0.2) and reported meaningfulness of the tests by PwMS. Meaningfulness was self-assessed for each test on a 5-point Likert scale (target: mean score of > 3) and by a structured interview. CLINICALTRIALS: gov Identifier: NCT04413032. RESULTS: We included 31 PwMS (21 [68%] female, mean age 43.4 ± 12.0 years, median EDSS 3.0 [range 1.0-6.0]) and 31 age- and sex-matched healthy volunteers. Out of 133 features extracted from 11 tests, 89 met the preset reliability criteria. All 11 tests were perceived as highly meaningful to PwMS. CONCLUSION: The dreaMS app reliably assessed features reflecting key functional domains meaningful to PwMS. More studies with longer follow-up are needed to prove validity of these measures as digital biomarkers in PwMS.