Electronic health record data for assessing risk of hospitalization for COVID-19: Methodological considerations applied to multiple sclerosis.

INTRODUCTION: During the COVID-19 pandemic, electronic health record (EHR) data has been used to investigate disease severity and risk factors for severe COVID-19 in people with multiple sclerosis (pwMS). Methodological challenges including sampling bias, and residual confounding should be considered when conducting EHR-based studies. We aimed to address these limitations related to the use of EHR data in order to identify risk factors, including the use of disease modifying therapies (DMTs), associated with hospitalization for COVID-19 amongst pwMS. METHODS: We performed a retrospective cohort study including a sample of 47,051 pwMS using a large US-based EHR and claims linked database. Follow-up started at the beginning of the pandemic, February 20th 2020, and continued until September 30th 2020. COVID-19 diagnosis was determined by the presence of ICD-10 diagnostic code for COVID-19, or a positive diagnostic laboratory test, or an ICD-10 diagnostic code for coronaviruses. We used Cox regression modeling to assess the impact of baseline demographics, MS disease history and pre-existing comorbidities on the risk of hospitalization for COVID-19. Then, we identified 5,169 pwMS using ocrelizumab (OCR) and 3,351 pwMS using dimethyl fumarate (DMF) at baseline, and evaluated the distribution of the identified COVID-19 risk factors between the two groups. Finally, we used Cox regression models, adjusted for the identified confounders, to estimate the risk of hospitalization for COVID-19 in pwMS treated with OCR compared to DMF. RESULTS: Among the pwMS cohort, we identified 799 COVID-19 cases (1.7%) which resulted in 182 hospitalizations for COVID-19 (0.4%). Population differences between the pwMS and COVID-19 cohorts were observed. Statistical modeling identified older age, male gender, African-American race, walking with assistance, non-ambulatory status, severe relapse requiring hospitalization in year prior to baseline, and specific comorbidities to be associated with a higher risk of COVID-19 related-hospitalization. Comparing the COVID-19 risk factors between OCR users and DMF users, MS characteristics including ambulatory status and MS subtype were highly imbalanced, likely arising from key differences in the labelled indications for these therapies. Compared to DMF use, in unadjusted (HR 1.58, 95% CI 0.73 - 3.44), adjusted (HR 1.28, 95% CI 0.58 - 2.83), propensity score weighted (HR 1.25, 95% CI 0.56 - 2.80), and doubly robust models (HR 1.29, 95% CI 0.57 - 2.89), no significantly increased risk of hospitalization for COVID-19 was associated with OCR use. CONCLUSION: We observed significant population differences when comparing all pwMS to COVID-19 cases, as well as significant differences in key confounders between OCR and DMF treated patients. In unadjusted analyses we did not observe a statistically significant higher risk of COVID-19 hospitalization in pwMS treated with OCR compared to DMF, with further attenuation of risk when adjusting for the key confounders. This study re-emphasises the importance to appropriately consider both sampling and confounding bias in EHR-based MS research.

Anti-SARS-CoV-2 T-stem cell memory persists in ocrelizumab-treated MS patients.

BACKGROUND: Development of long-lasting anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) T-cell responses in persons with multiple sclerosis (pwMS) treated with ocrelizumab is questioned. OBJECTIVE: Investigate antiviral T-cell responses after infection with SARS-CoV-2 in ocrelizumab-treated pwMS. Control groups included ocrelizumab-treated pwMS without SARS-CoV-2 infection, and non-MS individuals with and without SARS-CoV-2 infection. METHODS: Peripheral blood mononuclear cells were stimulated with SARS-CoV-2 peptide pools and T-cell reactivity was assessed by ELISPOT for interferon (IFN)-γ detection, and by multiparametric fluorescence-activated cell sorting (FACS) analyses for assessment and characterization of T-cell activation. RESULTS: ELISPOT assay against the spike and the N protein of SARS-CoV-2 displayed specific T-cell reactivity in 28/29 (96%) pwMS treated with ocrelizumab and infected by SARS-CoV-2, similar to infected persons without MS. This reactivity was present 1 year after infection and independent from the time of ocrelizumab infusion. FACS analysis following stimulation with SARS-CoV-2 peptide pools showed the presence of activation-induced markers (AIMs) in both CD4+ and CD8+ T-cell subsets in 96% and 92% of these individuals, respectively. Within naïve AIM+ CD4+ and CD8+ T-cells, we detected T memory stem cells, suggesting the acquisition of long-term memory. CONCLUSIONS: B-cell depletion using ocrelizumab does not impair the development of long-lasting anti-SARS-CoV-2 T-cell responses.

Understanding the impacts of COVID-19 pandemic in people with multiple sclerosis treated with ocrelizumab.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to major challenges in the therapeutic management of patients living with multiple sclerosis (PLwMS), particularly regarding the use of disease-modifying therapies. Despite an extraordinary scientific effort to study SARS-CoV-2 in PLwMS, the heterogeneity of COVID-19 manifestations, immunological mechanisms induced by the natural infection or the vaccines, and the extent of protection through the vaccines, major knowledge gaps remain. Here, we describe the scientific evidence generation plan developed by Roche/Genentech to better understand the impact of the COVID-19 pandemic in PLwMS treated with the B-cell depleting monoclonal antibody ocrelizumab.