Data-driven subclassification of ANCA-associated vasculitis: model-based clustering of a federated international cohort.

BACKGROUND: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis is a heterogenous autoimmune disease. While traditionally stratified into two conditions, granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA), the subclassification of ANCA-associated vasculitis is subject to continued debate. Here we aim to identify phenotypically distinct subgroups and develop a data-driven subclassification of ANCA-associated vasculitis, using a large real-world dataset. METHODS: In the collaborative data reuse project FAIRVASC (Findable, Accessible, Interoperable, Reusable, Vasculitis), registry records of patients with ANCA-associated vasculitis were retrieved from six European vasculitis registries: the Czech Registry of ANCA-associated vasculitis (Czech Republic), the French Vasculitis Study Group Registry (FVSG; France), the Joint Vasculitis Registry in German-speaking Countries (GeVas; Germany), the Polish Vasculitis Registry (POLVAS; Poland), the Irish Rare Kidney Disease Registry (RKD; Ireland), and the Skåne Vasculitis Cohort (Sweden). We performed model-based clustering of 17 mixed-type clinical variables using a parsimonious mixture of two latent Gaussian variable models. Clinical validation of the optimal cluster solution was made through summary statistics of the clusters' demography, phenotypic and serological characteristics, and outcome. The predictive value of models featuring the cluster affiliations were compared with classifications based on clinical diagnosis and ANCA specificity. People with lived experience were involved throughout the FAIRVASVC project. FINDINGS: A total of 3868 patients diagnosed with ANCA-associated vasculitis between Nov 1, 1966, and March 1, 2023, were included in the study across the six registries (Czech Registry n=371, FVSG n=1780, GeVas n=135, POLVAS n=792, RKD n=439, and Skåne Vasculitis Cohort n=351). There were 2434 (62·9%) patients with GPA and 1434 (37·1%) with MPA. Mean age at diagnosis was 57·2 years (SD 16·4); 2006 (51·9%) of 3867 patients were men and 1861 (48·1%) were women. We identified five clusters, with distinct phenotype, biochemical presentation, and disease outcome. Three clusters were characterised by kidney involvement: one severe kidney cluster (555 [14·3%] of 3868 patients) with high C-reactive protein (CRP) and serum creatinine concentrations, and variable ANCA specificity (SK cluster); one myeloperoxidase (MPO)-ANCA-positive kidney involvement cluster (782 [20·2%]) with limited extrarenal disease (MPO-K cluster); and one proteinase 3 (PR3)-ANCA-positive kidney involvement cluster (683 [17·7%]) with widespread extrarenal disease (PR3-K cluster). Two clusters were characterised by relative absence of kidney involvement: one was a predominantly PR3-ANCA-positive cluster (1202 [31·1%]) with inflammatory multisystem disease (IMS cluster), and one was a cluster (646 [16·7%]) with predominantly ear-nose-throat involvement and low CRP, with mainly younger patients (YR cluster). Compared with models fitted with clinical diagnosis or ANCA status, cluster-assigned models demonstrated improved predictive power with respect to both patient and kidney survival. INTERPRETATION: Our study reinforces the view that ANCA-associated vasculitis is not merely a binary construct. Data-driven subclassification of ANCA-associated vasculitis exhibits higher predictive value than current approaches for key outcomes. FUNDING: European Union's Horizon 2020 research and innovation programme under the European Joint Programme on Rare Diseases.

Data quality and patient characteristics in European ANCA-associated vasculitis registries: data retrieval by federated querying.

OBJECTIVES: This study aims to describe the data structure and harmonisation process, explore data quality and define characteristics, treatment, and outcomes of patients across six federated antineutrophil cytoplasmic antibody-associated vasculitis (AAV) registries. METHODS: Through creation of the vasculitis-specific Findable, Accessible, Interoperable, Reusable, VASCulitis ontology, we harmonised the registries and enabled semantic interoperability. We assessed data quality across the domains of uniqueness, consistency, completeness and correctness. Aggregated data were retrieved using the semantic query language SPARQL Protocol and Resource Description Framework Query Language (SPARQL) and outcome rates were assessed through random effects meta-analysis. RESULTS: A total of 5282 cases of AAV were identified. Uniqueness and data-type consistency were 100% across all assessed variables. Completeness and correctness varied from 49%-100% to 60%-100%, respectively. There were 2754 (52.1%) cases classified as granulomatosis with polyangiitis (GPA), 1580 (29.9%) as microscopic polyangiitis and 937 (17.7%) as eosinophilic GPA. The pattern of organ involvement included: lung in 3281 (65.1%), ear-nose-throat in 2860 (56.7%) and kidney in 2534 (50.2%). Intravenous cyclophosphamide was used as remission induction therapy in 982 (50.7%), rituximab in 505 (17.7%) and pulsed intravenous glucocorticoid use was highly variable (11%-91%). Overall mortality and incidence rates of end-stage kidney disease were 28.8 (95% CI 19.7 to 42.2) and 24.8 (95% CI 19.7 to 31.1) per 1000 patient-years, respectively. CONCLUSIONS: In the largest reported AAV cohort-study, we federated patient registries using semantic web technologies and highlighted concerns about data quality. The comparison of patient characteristics, treatment and outcomes was hampered by heterogeneous recruitment settings.

Evaluation of single-stage vision models for pose estimation of surgical instruments.

PURPOSE: Multiple applications in open surgical environments may benefit from adoption of markerless computer vision depending on associated speed and accuracy requirements. The current work evaluates vision models for 6-degree of freedom pose estimation of surgical instruments in RGB scenes. Potential use cases are discussed based on observed performance. METHODS: Convolutional neural nets were developed with simulated training data for 6-degree of freedom pose estimation of a representative surgical instrument in RGB scenes. Trained models were evaluated with simulated and real-world scenes. Real-world scenes were produced by using a robotic manipulator to procedurally generate a wide range of object poses. RESULTS: CNNs trained in simulation transferred to real-world evaluation scenes with a mild decrease in pose accuracy. Model performance was sensitive to input image resolution and orientation prediction format. The model with highest accuracy demonstrated mean in-plane translation error of 13 mm and mean long axis orientation error of 5[Formula: see text] in simulated evaluation scenes. Similar errors of 29 mm and 8[Formula: see text] were observed in real-world scenes. CONCLUSION: 6-DoF pose estimators can predict object pose in RGB scenes with real-time inference speed. Observed pose accuracy suggests that applications such as coarse-grained guidance, surgical skill evaluation, or instrument tracking for tray optimization may benefit from markerless pose estimation.

The Sound of Interconnectivity; The European Vasculitis Society 2022 Report.

The first European Vasculitis Society (EUVAS) meeting report was published in 2017. Herein, we report on developments in the past 5 years which were greatly influenced by the pandemic. The adaptability to engage virtually, at this critical time in society, embodies the importance of networks and underscores the role of global collaborations. We outline state-of-the-art webinar topics, updates on developments in the last 5 years, and proposals for agendas going forward. A host of newly reported clinical trials is shaping practice on steroid minimization, maintenance strategies, and the role of newer therapies. To guide longer-term strategies, a longitudinal 10-year study investigating relapse, comorbidity, malignancy, and survival rates is at an advanced stage. Disease assessment studies are refining classification criteria to differentiate forms of vasculitis more fully. A large international validation study on the histologic classification of anti-neutrophil cytoplasmic antibody (ANCA) glomerulonephritis, recruiting new multicenter sites and comparing results with the Kidney Risk Score, has been conducted. Eosinophilic granulomatosis with polyangiitis (EGPA) genomics offers potential pathogenic subset and therapeutic insights. Among biomarkers, ANCA testing is favoring immunoassay as the preferred method for diagnostic evaluation. Consolidated development of European registries is progressing with an integrated framework to analyze large clinical data sets on an unprecedented scale.