Background

Chronic active lesions (‘smoldering lesions’) in MS patients have recently gained increasing interest as possible markers of MS activity. Yet there is no in vivo marker to detect these lesions and characterize their structural dynamics.

Objectives

Our objective was to detect chronic active lesions in MS patients and characterize their intraindividual volume dynamics over time.

Methods

581 MRI datasets in 200 relapsing-remitting MS patients (2 - 5 per individual) from a 3-year multi-centre observational INSPIRATION-MRI study were investigated using Voxel-Guided-Morphometry (VGM), a method for intraindividual detection and quantification of structural changes in volumetric MRI scans (T1 – weighted MPRAGE-sequence) over time. Chronic active lesions were identified and differentiated into chronic shrinking vs. chronic enlarging lesions.

Results

Intervals between consecutive scans varied between 53 and 1199 days, mean = 443 days. Overall, individual MRI scan intervals varied between 53 (2 scans) and 1360 (3 scans) days. In total, 2419 active lesions were identified, characterized and quantified, corresponding to a mean active lesion load of 12 lesions per patient. In chronic shrinking lesions, mean volume change was -33% (from -11% to -59%), in chronic enlarging lesions mean volume change was +53% (from 29% to 425%). We found a mean annual volume decrease for white matter of 0.17% and gray matter of 0.12%. 31 patients exclusively demonstrated chronic enlarging lesions, in 16 patients only chronic shrinking lesions were detected, and 119 patients were found to have a mixture of both types of active lesions. In 34 patients, no active lesions were identified.

Conclusions

Chronic active lesions were detected in 83% of the investigated patients using Voxel-Guided-Morphometry in longitudinal 3D-MRI datasets. As these chronic active lesions are supposed to represent MS activity with corresponding brain tissue damage also in patients who do not demonstrate new contrast-enhancing lesions, they might be regarded as an additional biomarker for MS activity. The relationship between chronic active brain tissue lesions and clinical MS progression needs to be further investigated.

Background

Hallmarks of secondary progressive multiple sclerosis (SPMS) are amongst others progressive motoric dysfunction and cognitive decline. Siponimod (Mayzent®), a selective sphingosine-1-phosphate receptor modulator, has been approved by the EMA for the treatment of active SPMS, evidenced by relapses or imaging features of inflammatory activity. AMASIA (ImpAct of Mayzent® (Siponimod) on secondAry progressive multiple Sclerosis patients in a long-term non-Iinterventional study in GermAny) is the first prospective non-interventional study to assess long-term effectiveness and safety of siponimod in clinical routine and the impact on quality of life and socioeconomic conditions.

Objectives

Characterization of the siponimod patient profile and SPMS diagnostic criteria based on clinical routine in Germany.

Methods

In AMASIA treatment effects of siponimod will be analyzed in 1,500 SPMS patients over 3 years. Disability progression and cognitive changes are evaluated every 6 months by the expanded disability status scale (EDSS) and the symbol digit modalities test (SDMT). Additional measures including MS activity by magnetic resonance imaging (MRI), assessments of functional domains, and questionnaires from patient’s, physician’s, and relatives’ perspectives of disability progression, cognitive worsening, and quality of life as well as socioeconomic aspects are analyzed.

Results

Results of the first interim analysis will be presented and will show patient characteristics of the first approx. 200 patients in Germany treated with siponimod in clinical routine. These data will include demography, but also all relevant clinical information including disease and therapy history, allowing for a comparison with data from phase II and III clinical studies with siponimod.

Conclusions

The combination of clinical parameters and patient reported outcomes including quality of life and socioeconomics allows a more detailed insight in the siponimod treated SPMS patient population in clinical routine in Germany. This will contribute to a better understanding of SPMS management in the medical community.

Background

Diagnosis of secondary progressive multiple sclerosis (SPMS) patients and the identification of the transition phase from relapsing-remitting multiple sclerosis (RRMS) to SPMS remain a challenge as reliable clinical diagnostic criteria and diagnostic tools are lacking.

Objectives

This analysis evaluates disability parameters and patient reported outcomes in patients with RRMS at risk for SPMS and SPMS to:

– compare clinical parameters including magnetic resonance imaging (MRI), quality of life and socioeconomic aspects of patients with SPMS to patients at risk for SPMS

– characterize patients in the transition phase from RRMS to SPMS

– evaluate performance of the novel progression questionnaire (MSProDiscuss) in clinical routine

Methods

PANGAEA 2.0 EVOLUTION is part of the non-interventional real-world study PANGAEA 2.0 including approximately 2,500 RRMS patients. Additionally up to 1,000 patients diagnosed with SPMS or on risk for SPMS are currently being recruited and will be prospectively followed independently of treatment for up to 2 years. Diagnosis for risk for SPMS is made by the physician after a comprehensive evaluation of the patient's symptoms including for example relapses, fatigue, progression or impact on quality of life as there are no standard criteria for the transition state for RRMS to SPMS. Routine clinical measurements including EDSS, relapse rate, MRI and cognition measurements, quality of life (EQ-5D, MSIS-29) and socioeconomic conditions (MS-HRS, WPAI) as well as observational parameters from the physician’s perspective (UKNDS, CGI) are collected at 6-month intervals.

Results

Real world data of approximately 400 patients will be shown. Profiles of patients with different progression states will be compared and assessed for differences. MRI findings will be correlated with clinical and patient reported outcomes. Status of disease progression will be correlated with quality of life and socioeconomic measures collected within this study.

Conclusions

PANGAEA2.0 EVOLUTION allows to compare SPMS patient profiles with RRMS patients at risk for SPMS in a real world setting. By combining clinical and non-clinical parameters a clearer picture can be generated for the establishment of standard early diagnosis criteria and therapy of SPMS patients.