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The study will attempt to closely analyze Multiple Sclerosis (MS) patients after de-escalating or discontinuation of immunotherapy using clinical monitoring as well as digital and serological biomarkers in order to detect clinical progression or disease activity. As this is an observational study, it aims to closely follow-up on patients where the clinical decision to de-escalate or end treatment has been independently made. Specifically, we want to find out to what extent patients will show increased disease activity after de-escalation/discontinuation from high-efficacy treatment (HET) and which measurement method (clinical, digital, serological) retrospectively reflects the disease activity most closely or detects it most sensitively.
Due to the increasing scientific efforts in recent years, a variety of HET are now available for patients with MS. In addition to long-term clinical assessment, monitoring by means of magnetic resonance imaging (MRI) has also become increasingly established. No evidence of disease activity under appropriate immunotherapy has thus been defined in a wide variety of concepts using clinical and MRI parameters. These medical achievements have positively influenced the natural course of MS, especially by significantly reducing the relapse activity. In contrast, however, the risk of potential complications under long-term immunotherapy should not be underestimated. This concerns in particular infection risks but also an increased malignancy risk for various, mostly highly effective immunotherapies.
Therefore, the question increasingly arises in clinical practice as to what extent HET should be continued or should be de-escalated in case of long-term disease course. As patients and doctors take clinical decision to de-escalate their therapies, often after many years of little or even no disease activity, the central question of how to best monitor patients subsequently remains. Digital smartwatch-based measurements or app-based regular assessments could add high-frequency real-world data to the picture and thus improve the understanding of individual disease courses. Additionally, novel serological markers to detect neuronal damage are becoming more widely available. Consequently, this study aims to evaluate different digital measurements and blood-based analyses to monitor disease activity in MS patients, which have independently with their treating physicians decided to discontinue or de-escalate their disease-modifying treatment of MS.
Data captured by the used smartwatches (Withings Scanwatch) includes activity-related data (step count, minutes in certain intensity levels), basic cardiovascular measurements such as heart rate, and sleep-related data (total time asleep, sleep efficiency and quality etc.). Blood-based measurements include serum neurofilament-light-chain (sNfL), glial fibrillary acidic protein (GFAP) and proteomic data. The investigators will attempt to closely analyze MS patients after de-escalating or discontinuation of immunotherapy using digital and serological biomarkers in order to detect possible increased disease activity. In addition to clinical assessment, structural MRI examinations will be optionally conducted in patients from core center at baseline and in month 12 and 24. Measurement parameters from clinical MRI examinations (lesion load) are also taken into account from the other study centers. In addition to that, patients from core center will undergo an Optical coherence tomography (OCT) measurement. OCT is a non-invasive, interferometric method that allows for detailed visualization of retinal morphology and is known to reveal abnormalities in various central nervous system (CNS) disorders. Data will be collected for a 24-month prospective period.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Core center | In addition to clinical assessment, MRI examinations will be optionally conducted in patients from core center at baseline and in month 12 and 24. Measurement parameters from clinical MRI examinations (lesion load) are also taken into account from the other study centers. In addition to that, patients from core center will undergo an Optical coherence tomography (OCT) measurement. |
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| Extended cohort | Clinical assessment will be conducted in patients from extended cohort at baseline and in month 6, 12, 18 and 24. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Withings Scanwatch | Device | Data captured by the used smartwatches (Withings Scanwatch) includes activity-related data (step count, minutes in certain intensity levels), basic cardiovascular measurements such as heart rate, and sleep-related data (total time asleep, sleep efficiency and quality etc.). |
| Measure | Description | Time Frame |
|---|---|---|
| Percentage of disease activity, measured by loss of NEDA at month 24 | According to NEDA-3 (Giovannoni et al., 2015) indicated by relapse, EDSS or cerebral magnetic resonance imaging (MRI) activity. | Baseline up to 24 months |
| Measure | Description | Time Frame |
|---|---|---|
| EDSS: Change From Baseline in Expanded Disability Status Scale (EDSS) Score | The EDSS is used to quantify disability due to symptoms of MS and to track changes in disability status over time. Scores range from 0 (normal neurological exam) to 10 (death due to multiple sclerosis). Higher scores indicate the worse level of disability. | Baseline up to 24 months (after 6 months, 12 months, 18 months, 24 months) |
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Inclusion Criteria:
Exclusion Criteria:
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150 MS patients after treatment de-escalation/discontinuation
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Marc Günter Pawlitzki, PD Dr. med. | Contact | +49 02118117887 | MarcGuenter.Pawlitzki@med.uni-duesseldorf.de |
| Name | Affiliation | Role |
|---|---|---|
| Marc Günter Pawlitzki, PD Dr. med. | Heinrich-Heine University, Duesseldorf | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Heinrich-Heine University, Duesseldorf | Recruiting | Düsseldorf | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 42368888 | Derived | Pawlitzki M, Kirschner P, Masanneck L, Hagler R, Meier E, Vach M, Inojosa H, Ziemssen T, Ivan VL, More S, Patil K, Firouzi-Memarpuri P, Caspers J, Repple J, Dannlowski U, Khalil M, Meuth SG, Rubbert C. Brain age gap in multiple sclerosis: associated with disability but independent of serum biomarkers. Ther Adv Neurol Disord. 2026 Jun 23;19:17562864261458516. doi: 10.1177/17562864261458516. eCollection 2026. |
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| ID | Term |
|---|---|
| D009103 | Multiple Sclerosis |
| ID | Term |
|---|---|
| D020278 | Demyelinating Autoimmune Diseases, CNS |
| D020274 | Autoimmune Diseases of the Nervous System |
| D009422 | Nervous System Diseases |
| D003711 | Demyelinating Diseases |
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Serum
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| Change From Baseline in World Health Organization Quality of Life Brief Version (WHOQOL-BREF) Score | • The WHOQOL-BREF questionnaire measures quality of life across 4 domains: Physical health, psychological health, social relationships and environment. It also includes one question on overall QOL and one on general health. The WHOQOL-BREF scores correlate highly (.89 or above) with WHOQOL-100 scores, and demonstrate good discriminant validity, content validity, internal consistency and test-retest reliability. The four WHOQOL-BREF domain scores will be used as main outcome measure. The measure is calculated by summing the point values for the questions corresponding to each domain and then transforming the scores to a 0-100 point interval, higher score correspond to greater QOL. | Baseline up to 24 months (after 6 months, 12 months, 18 months, 24 months) |
| Change From Baseline in Multiple Sclerosis Functional Composite (MSFC) Score - Component Paced Auditory Serial Addition Test | The Paced Auditory Serial Addition Test (PASAT) measures cognitive processing speed and working memory by evaluating how accurately participants can perform mental arithmetic tasks while listening to a series of numbers. It's one of the components of the Multiple Sclerosis Functional Composite (MSFC), alongside the Timed 25-foot walk (T25FW) and the 9-hole peg test (9HPT) for both dominant and nondominant hands. The MSFC Z-score is calculated by creating Z-scores for each component of the MSFC and averaging them to create an overall composite score. A Z-score represented the number of standard deviations participant's test result was higher (Z >0) or lower (Z <0) than the average test result (Z = 0) from the reference population. Higher scores indicate better outcomes. | Baseline up to 24 months (after 6 months, 12 months, 18 months, 24 months) |
| Change From Baseline in Multiple Sclerosis Functional Composite (MSFC) Score - Component 9-hole peg test | The 9-hole peg test (9HPT) evaluates manual dexterity by assessing the time it takes for a participant to complete the task using both dominant and nondominant hands. It's part of the Multiple Sclerosis Functional Composite (MSFC), which also includes the Timed 25-foot walk (T25FW) and the Paced Auditory Serial Addition Test (PASAT). The MSFC Z-score is calculated by creating Z-scores for each component of the MSFC and averaging them to create an overall composite score. A Z-score represented the number of standard deviations participant's test result was higher (Z >0) or lower (Z <0) than the average test result (Z = 0) from the reference population. Higher scores indicate better outcomes. | Baseline up to 24 months (after 6 months, 12 months, 18 months, 24 months) |
| Change From Baseline in Multiple Sclerosis Functional Composite (MSFC) Score - Component Timed 25-foot walk (T25FW) | The Timed 25-foot walk (T25FW) assesses mobility and ambulation by measuring the time it takes for a participant to walk 25 feet. It's a component of the Multiple Sclerosis Functional Composite (MSFC), along with the 9-hole peg test (9HPT) for both dominant and nondominant hands, and the Paced Auditory Serial Addition Test (PASAT). The MSFC Z-score is calculated by creating Z-scores for each component of the MSFC and averaging them to create an overall composite score. A Z-score represented the number of standard deviations participant's test result was higher (Z >0) or lower (Z <0) than the average test result (Z = 0) from the reference population. Higher scores indicate better outcomes. | Baseline up to 24 months (after 6 months, 12 months, 18 months, 24 months) |
| Change in Pittsburgh Sleep Quality Index (PSQI) | Time frame: Screening + Baseline (V1), After 6 months (V2), After 12 months (V3), After 18 months (V4), After 24 months (V5) |
| Change From Baseline in Fatigue Severity Scale (FSS) | The FSS is a self-assessment questionnaire that provides a score as a measurement of the severity of fatigue. It consists of 9 questions scored from 1 to 7, low value indicates strong disagreement with the statement, whereas a high value indicates strong agreement. A total score of 36 or more suggests the presence of fatigue. | Baseline up to 24 months (after 6 months, 12 months, 18 months, 24 months) |
| Change in Blood analysis (levels of sNfl, GFAP, serum proteomics) | Time frame: Screening + Baseline (V1), After 6 months (V2), After 12 months (V3), After 18 months (V4), After 24 months (V5) |
| Questionnaire about smartwatch usage (System Usability Score) | The System Usability Scale (SUS) is a widely recognized and straightforward tool for evaluating the usability of various systems, including software applications, websites, and various user interfaces. It consists of a 10-item questionnaire with five response options ranging from Strongly Agree to Strongly Disagree. The SUS provides a global view of subjective assessments of usability, making it applicable to a range of design products and services, including healthcare systems and applications. | After 6 months and 24 months of use |
| Wearing time of smartwatch (daily) | during the entire observation period |
| Longitudinal development of activity parameter: step count | during the entire observation period |
| Longitudinal development of activity parameter: approximate distance traveled (meter) | during the entire observation period |
| Longitudinal development of activity parameter: duration of soft activity (seconds) defined by Withings | during the entire observation period |
| Longitudinal development of activity parameter: duration of moderate activity (seconds) defined by Withings | during the entire observation period |
| Longitudinal development of activity parameter: duration of intense activity (seconds) defined by Withings | during the entire observation period |
| Longitudinal development of activity parameter: sum of all active time (seconds) | during the entire observation period |
| Longitudinal development of sleep parameter: time awake (seconds) | during the entire observation period |
| Longitudinal development of activity parameter: approximate calories burned | during the entire observation period |
| Longitudinal development of sleep parameter: number of times user woke up | during the entire observation period |
| Longitudinal development of sleep parameter: time to sleep (seconds) | during the entire observation period |
| Longitudinal development of sleep parameter: heart rate variability (ms) | during the entire observation period |
| Longitudinal development of sleep parameter: total time asleep (seconds) | during the entire observation period |
| Longitudinal development of sleep parameter: total time in bed (seconds) | during the entire observation period |
| Longitudinal development of sleep parameter: ratio of sleep/time in bed | during the entire observation period |
| Longitudinal development of sleep parameter: time spent in bed before falling asleep (seconds) | during the entire observation period |
| Longitudinal development of sleep parameter: time awake after first falling asleep (seconds) | during the entire observation period |
| Longitudinal development of sleep parameter: Withings Sleep score | during the entire observation period |
| Longitudinal development of cardiovascular parameter: average heartrate | during the entire observation period |
| Longitudinal development of cardiovascular parameter: maximal heartrate | during the entire observation period |
| Longitudinal development of cardiovascular parameter: minimum heartrate | during the entire observation period |
| Longitudinal development of cardiovascular parameter: time in light heartrate zone (seconds) | during the entire observation period |
| Longitudinal development of cardiovascular parameter: time in moderate heartrate zone (seconds) | during the entire observation period |
| Longitudinal development of cardiovascular parameter: time in intense heartrate zone (seconds) | during the entire observation period |
| Longitudinal development of cardiovascular parameter: time in maximal heartrate zone (seconds) | during the entire observation period |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |