Comparison of time to clinically meaningful improvement in quality of life in neurological disorders in patients treated with natalizumab versus ocrelizumab

Aim: To assess time to improvement in Quality of Life in Neurological Disorders (Neuro-QoL) domains for patients treated with natalizumab versus ocrelizumab. Methods: Patients enrolled in the MS PATHS network who initiated treatment with either natalizumab or ocrelizumab rated the Neuro-QoL domains of physical function, symptoms, emotional health, cognitive function and social ability. Results: Time to clinically meaningful improvement was significantly shorter with natalizumab versus ocrelizumab for cognitive function (event time ratio [95% CI]: 0.37 [0.24-0.57]; p < 0.001), sleep disturbance (0.45 [0.28-0.72]; p = 0.001), social role participation (0.37 [0.21-0.66]; p = 0.001) and social role satisfaction (0.5 [0.31-0.8]; p = 0.004). Conclusion: Natalizumab had shorter time to clinically meaningful improvement in cognitive, sleep, and social role Neuro-QoL domains versus ocrelizumab.

Immunoglobulin G immune response to SARS-CoV-2 vaccination in people living with multiple sclerosis within Multiple Sclerosis Partners Advancing Technology and Health Solutions

BACKGROUND

The impact of multiple sclerosis (MS) disease-modifying therapies (DMTs) on SARS-CoV-2 vaccination response is uncertain.

METHODS

Post-SARS-CoV-2 vaccination blood samples across multiple DMTs were tested for SARS-CoV-2 immunoglobulin G (IgG) response.

RESULTS

Three hundred twenty-two people with MS were included; 91.9% received an mRNA vaccine. Post-vaccination reactive IgG rates (IgG index > 1) were 40% for anti-CD20 (32/80 patients); 41% for sphingosine 1-phosphate receptor modulators (S1PRM, 16/39); and 100% for all other classes, including the no DMT group.

CONCLUSION

Anti-CD20 therapies and S1PRMs reduce IgG response to SARS-CoV-2 vaccination; IgG response is preserved with other DMTs.

Harnessing Real-World Data to Inform Decision-Making: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS)

Background: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) is the first example of a learning health system in multiple sclerosis (MS). This paper describes the initial implementation of MS PATHS and initial patient characteristics.

Methods: MS PATHS is an ongoing initiative conducted in 10 healthcare institutions in three countries, each contributing standardized information acquired during routine care. Institutional participation required the following: active MS patient census of ≥500, at least one Siemens 3T magnetic resonance imaging scanner, and willingness to standardize patient assessments, share standardized data for research, and offer universal enrolment to capture a representative sample. The eligible participants have diagnosis of MS, including clinically isolated syndrome, and consent for sharing pseudonymized data for research. MS PATHS incorporates a self-administered patient assessment tool, the Multiple Sclerosis Performance Test, to collect a structured history, patient-reported outcomes, and quantitative testing of cognition, vision, dexterity, and walking speed. Brain magnetic resonance imaging is acquired using standardized acquisition sequences on Siemens 3T scanners. Quantitative measures of brain volume and lesion load are obtained. Using a separate consent, the patients contribute DNA, RNA, and serum for future research. The clinicians retain complete autonomy in using MS PATHS data in patient care. A shared governance model ensures transparent data and sample access for research.

Results: As of August 5, 2019, MS PATHS enrolment included participants (n = 16,568) with broad ranges of disease subtypes, duration, and severity. Overall, 14,643 (88.4%) participants contributed data at one or more time points. The average patient contributed 15.6 person-months of follow-up (95% CI: 15.5–15.8); overall, 166,158 person-months of follow-up have been accumulated. Those with relapsing–remitting MS demonstrated more demographic heterogeneity than the participants in six randomized phase 3 MS treatment trials. Across sites, a significant variation was observed in the follow-up frequency and the patterns of disease-modifying therapy use.

Conclusions: Through digital health technology, it is feasible to collect standardized, quantitative, and interpretable data from each patient in busy MS practices, facilitating the merger of research and patient care. This approach holds promise for data-driven clinical decisions and accelerated systematic learning.