Computable phenotype for real-world, data-driven retrospective identification of relapse in ANCA-associated vasculitis.

OBJECTIVE: ANCA-associated vasculitis (AAV) is a relapsing-remitting disease, resulting in incremental tissue injury. The gold-standard relapse definition (Birmingham Vasculitis Activity Score, BVAS>0) is often missing or inaccurate in registry settings, leading to errors in ascertainment of this key outcome. We sought to create a computable phenotype (CP) to automate retrospective identification of relapse using real-world data in the research setting. METHODS: We studied 536 patients with AAV and >6 months follow-up recruited to the Rare Kidney Disease registry (a national longitudinal, multicentre cohort study). We followed five steps: (1) independent encounter adjudication using primary medical records to assign the ground truth, (2) selection of data elements (DEs), (3) CP development using multilevel regression modelling, (4) internal validation and (5) development of additional models to handle missingness. Cut-points were determined by maximising the F1-score. We developed a web application for CP implementation, which outputs an individualised probability of relapse. RESULTS: Development and validation datasets comprised 1209 and 377 encounters, respectively. After classifying encounters with diagnostic histopathology as relapse, we identified five key DEs; DE1: change in ANCA level, DE2: suggestive blood/urine tests, DE3: suggestive imaging, DE4: immunosuppression status, DE5: immunosuppression change. F1-score, sensitivity and specificity were 0.85 (95% CI 0.77 to 0.92), 0.89 (95% CI 0.80 to 0.99) and 0.96 (95% CI 0.93 to 0.99), respectively. Where DE5 was missing, DE2 plus either DE1/DE3 were required to match the accuracy of BVAS. CONCLUSIONS: This CP accurately quantifies the individualised probability of relapse in AAV retrospectively, using objective, readily accessible registry data. This framework could be leveraged for other outcomes and relapsing diseases.

FAIRVASC: A semantic web approach to rare disease registry integration.

Rare disease data is often fragmented within multiple heterogeneous siloed regional disease registries, each containing a small number of cases. These data are particularly sensitive, as low subject counts make the identification of patients more likely, meaning registries are not inclined to share subject level data outside their registries. At the same time access to multiple rare disease datasets is important as it will lead to new research opportunities and analysis over larger cohorts. To enable this, two major challenges must therefore be overcome. The first is to integrate data at a semantic level, so that it is possible to query over registries and return results which are comparable. The second is to enable queries which do not take subject level data from the registries. To meet the first challenge, this paper presents the FAIRVASC ontology to manage data related to the rare disease anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV), which is based on the harmonisation of terms in seven European data registries. It has been built upon a set of key clinical questions developed by a team of experts in vasculitis selected from the registry sites and makes use of several standard classifications, such as Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) and Orphacode. It also presents the method for adding semantic meaning to AAV data across the registries using the declarative Relational to Resource Description Framework Mapping Language (R2RML). To meet the second challenge a federated querying approach is presented for accessing aggregated and pseudonymized data, and which supports analysis of AAV data in a manner which protects patient privacy. For additional security the federated querying approach is augmented with a method for auditing queries (and the uplift process) using the provenance ontology (PROV-O) to track when queries and changes occur and by whom. The main contribution of this work is the successful application of semantic web technologies and federated queries to provide a novel infrastructure that can readily incorporate additional registries, thus providing access to harmonised data relating to unprecedented numbers of patients with rare disease, while also meeting data privacy and security concerns.

Risk Factors for Severe Outcomes in Patients With Systemic Vasculitis and COVID-19: A Binational, Registry-Based Cohort Study.

OBJECTIVE: COVID-19 is a novel infectious disease with a broad spectrum of clinical severity. Patients with systemic vasculitis have an increased risk of serious infections and may be at risk of severe outcomes following COVID-19. We undertook this study to establish the risk factors for severe COVID-19 outcomes in these patients, including the impact of immunosuppressive therapies. METHODS: A multicenter cohort was developed through the participation of centers affiliated with national UK and Ireland vasculitis registries. Clinical characteristics and outcomes are described. Logistic regression was used to evaluate associations between potential risk factors and a severe COVID-19 outcome, defined as a requirement for advanced oxygen therapy, a requirement for invasive ventilation, or death. RESULTS: The cohort included 65 patients with systemic vasculitis who developed COVID-19 (median age 70 years, 49% women), of whom 25 patients (38%) experienced a severe outcome. Most patients (55 of 65 [85%]) had antineutrophil cytoplasmic antibody-associated vasculitis (AAV). Almost all patients required hospitalization (59 of 65 [91%]), 7 patients (11%) were admitted to intensive care, and 18 patients (28%) died. Background glucocorticoid therapy was associated with severe outcomes (adjusted odds ratio [OR] 3.7 [95% confidence interval 1.1-14.9]; P = 0.047), as was comorbid respiratory disease (adjusted OR 7.5 [95% confidence interval 1.9-38.2]; P = 0.006). Vasculitis disease activity and nonglucocorticoid immunosuppressive therapy were not associated with severe outcomes. CONCLUSION: In patients with systemic vasculitis, glucocorticoid use at presentation and comorbid respiratory disease were associated with severe outcomes in COVID-19. These data can inform clinical decision-making relating to the risk of severe COVID-19 in this vulnerable patient group.