ABSTRACT
Introduction: The AbC-19™ lateral flow immunoassay (LFIA) performance was evaluated on plasma samples from a SARS-CoV-2 vaccination cohort, WHO international standards for anti-SARS-CoV-2 IgG (human), individuals ≥2 weeks from infection of RT-PCR confirmed SARS-CoV-2 genetic variants, as well as microorganism serology. Methods: Pre-vaccination to three weeks post-booster samples were collected from a cohort of 111 patients (including clinically extremely vulnerable patients) from Northern Ireland. All patients received Oxford-AstraZeneca COVID-19 vaccination for the first and second dose, and Pfizer-BioNTech for the third (first booster). WHO international standards, 15 samples from 2 variants of concern (Delta and Omicron) and cross-reactivity with plasma samples from other microorganism infections were also assessed on AbC-19™. Results: All 80 (100%) participants sampled post-booster had high positive IgG responses, compared to 38/95 (40%) participants at 6 months post-first vaccination. WHO standard results correlated with information from corresponding biological data sheets, and antibodies to all genetic variants were detected by LFIA. No cross-reactivity was found with exception of one (of five) Dengue virus samples. Conclusion: These findings suggest BNT162b2 booster vaccination enhanced humoral immunity to SARS-CoV-2 from pre-booster levels, and that this antibody response was detectable by the LFIA. In combination with cross-reactivity, standards and genetic variant results would suggest LFIA may be a cost-effective measure to assess SARS-CoV-2 antibody status.
ABSTRACT
Background: Real-world data (RWD) are an important complement to randomized, controlled and registry datasets in defining a disease course longitudinally. There is growing interest in understanding the insidious progression in multiple sclerosis (MS) that can occur despite aggressive relapse prevention, as well as how diversity and comorbidities impact multiple sclerosis (MS) patients, particularly in the era of the coronavirus (COVID19) pandemic. Objectives: We aim to derive RWD from a diverse cohort of approximately 4,000 MS patients in Northern California to pair with biomarkers from the Sutter-wide Precision Medicine Biobank - a longitudinal biorepository with a healthy aging comparator cohort. This pilot of 34 patients evaluates the integration of several data sources to extract key information about disease course. From the EHR, we use a combination of text processing, automated data element extraction, manual chart curation, and patientand physician-targeted questionnaires to form a real-world dataset of interpretable outcome metrics. Methods: This is an ambidirectional cohort study of subjects at least 18 years old, with a defining diagnosis of MS from at least one hospitalization or two outpatient encounters. Data elements including demographics, medication orders and comorbidities were directly extracted from the EHR. MRI reports in text format were stored in an Epic Clarity database, and neurology notes were mined for terms indicating stability versus worsening. Manual curation was used to transform prose clinician notes into tabularformat outcome scores. Results: We curated 9930 total encounters, 136 brain MRI reports and 137 spine MRI reports. We found 7.5 years (+/- 3.3) of data per patient in this pilot of 34 patients. 79% of patients were female, 21% male;68% white, 26% black and 6% other/not disclosed. The most common disease-modifying therapies used were natalizumab, dimethyl fumarate and glatiramer acetate. 68% of patients had at least one comorbidity, 35% specifically had hypertension. Using automated and manual data methods, we were able to compile metrics of clinical and radiographic worsening versus stability from information in the EHR. Conclusions: Our methods may be used to generate interpretable data on a system-wide scale from the comprehensive, longitudinal data of an EHR. These RWD can be paired with biospecimens, research assessments, and other datasets to add to the diversity of data on MS natural history and medication response.