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.
- Klíčová slova
- Classification, Epidemiology, Outcome Assessment, Health Care, Vasculitis,
- MeSH
- ANCA-asociované vaskulitidy * diagnóza MeSH
- dospělí MeSH
- fenotyp * MeSH
- lidé středního věku MeSH
- lidé MeSH
- longitudinální studie MeSH
- recidiva * MeSH
- registrace MeSH
- retrospektivní studie MeSH
- senioři MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
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.
- Klíčová slova
- epidemiology, granulomatosis with polyangiitis, quality indicators, health care, systemic vasculitis,
- MeSH
- ANCA-asociované vaskulitidy * farmakoterapie epidemiologie komplikace MeSH
- granulomatóza s polyangiitidou * farmakoterapie epidemiologie komplikace MeSH
- lidé MeSH
- mikroskopická polyangiitida * farmakoterapie epidemiologie MeSH
- protilátky proti cytoplazmě neutrofilů MeSH
- registrace MeSH
- správnost dat MeSH
- ukládání a vyhledávání informací MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- Názvy látek
- protilátky proti cytoplazmě neutrofilů MeSH
SIGNIFICANCE STATEMENT: Most patients with anti-glomerular basement membrane (GBM) disease present with rapidly progressive glomerulonephritis, and more than half develop ESKD. Currently, no tools are available to aid in the prognostication or management of this rare disease. In one of the largest assembled cohorts of patients with anti-GBM disease (with 174 patients included in the final analysis), the authors demonstrated that the renal risk score for ANCA-associated vasculitis is transferable to anti-GBM disease and the renal histology is strongly predictive of renal survival and recovery. Stratifying patients according to the percentage of normal glomeruli in the kidney biopsy and the need for RRT at the time of diagnosis improves outcome prediction. Such stratification may assist in the management of anti-GBM disease. BACKGROUND: Prospective randomized trials investigating treatments and outcomes in anti-glomerular basement membrane (anti-GBM) disease are sparse, and validated tools to aid prognostication or management are lacking. METHODS: In a retrospective, multicenter, international cohort study, we investigated clinical and histologic parameters predicting kidney outcome and sought to identify patients who benefit from rescue immunosuppressive therapy. We also explored applying the concept of the renal risk score (RRS), currently used to predict renal outcomes in ANCA-associated vasculitis, to anti-GBM disease. RESULTS: The final analysis included 174 patients (out of a total of 191). Using Cox and Kaplan-Meier methods, we found that the RRS was a strong predictor for ESKD. The 36-month renal survival was 100%, 62.4%, and 20.7% in the low-risk, moderate-risk, and high-risk groups, respectively. The need for renal replacement therapy (RRT) at diagnosis and the percentage of normal glomeruli in the biopsy were independent predictors of ESKD. The best predictor for renal recovery was the percentage of normal glomeruli, with a cut point of 10% normal glomeruli providing good stratification. A model with the predictors RRT and normal glomeruli ( N ) achieved superior discrimination for significant differences in renal survival. Dividing patients into four risk groups led to a 36-month renal survival of 96.4% (no RRT, N ≥10%), 74.0% (no RRT, N <10%), 42.3% (RRT, N ≥10%), and 14.1% (RRT, N <10%), respectively. CONCLUSIONS: These findings demonstrate that the RRS concept is transferrable to anti-GBM disease. Stratifying patients according to the need for RRT at diagnosis and renal histology improves prediction, highlighting the importance of normal glomeruli. Such stratification may assist in the management of anti-GBM disease. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/JASN/2023_02_27_JASN0000000000000060.mp3.
- MeSH
- ANCA-asociované vaskulitidy * MeSH
- antirenální glomerulonefritida * MeSH
- hodnocení rizik MeSH
- kohortové studie MeSH
- ledviny MeSH
- lidé MeSH
- náhrada funkce ledvin MeSH
- prospektivní studie MeSH
- retrospektivní studie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH