Incidence, prevalence, mortality and chronic renal damage of anti-neutrophil cytoplasmic antibody-associated glomerulonephritis in a 20-year population-based cohort

Background. True population-based clinical and outcomes data are lacking for anti-neutrophil cytoplasmic autoantibody (ANCA)-associated glomerulonephritis (AAGN). Therefore we aimed to estimate the incidence, prevalence and mortality of AAGN, as well as the relationship between the grade of chronic renal damage at presentation and renal and non-renal outcomes. Methods. Patients with AAGN were identiﬁed among a population-based incident cohort of 57 Olmsted County residents diagnosed with ANCA-associated vasculitis (AAV) in 1996–2015. Incidence rates were age and sex adjusted to the 2010 US white population. Age- and sex-adjusted prevalence was calculated for 1 January 2015. Survival rates were compared with expected rates in the Minnesota population. Chronic renal damage was assessed by chronicity score (CS) on biopsies performed at diagnosis. Results. Thirty-four (60%) patients had AAGN. Of these, 65% had microscopic polyangiitis (MPA) and 74% were myeloperoxidase (MPO)-ANCA positive. The annual incidence of AAGN was 2.0/100 000 population [95% conﬁdence interval (CI) 1.3–2.7] and the overall prevalence was 35/100 000 (95% CI 24–47). Mortality for AAGN was increased (P < 0.001), whereas mortality for AAV without glomerulonephritis did not differ from the general population. Minimal to mild CS predicted recovery of renal function at 1 year; clinical diagnosis (granulomatosis with polyangiitis versus MPA) and ANCA speciﬁcity (proteinase 3 versus MPO) did not. This observation was replicated in an independent cohort of 38 newly diagnosed AAGN patients seen at our centre over the 1999–2014 period. Conclusions. The annual incidence and prevalence of AAGN in Minnesota are 2.0/100 000 and 35/100000, respectively. Mortality is worse compared with AAV patients without glomerulonephritis. More advanced renal damage at diagnosis pre-dicts less renal recovery. ABSTRACT Background. Guiding patients with advanced chronic kidney disease (CKD) through advance care planning about future treatment obliges an assessment of prognosis. A patient-speciﬁc integrated model to predict mortality could inform shared decision-making for patients with CKD. Methods. Patients with Stages 4 and 5 CKD from Massachusetts (749) and West Virginia (437) were prospec-tively evaluated for clinical parameters, functional status [Karnofsky Performance Score (KPS)] and their provider’s response to the Surprise Question (SQ). A predictive model for 12-month mortality was derived with the Massachusetts cohort and then validated externally on the West Virginia cohort. Logistic regression was used to create the model, and the c-sta-tistic and Hosmer–Lemeshow statistic were used to assess model discrimination and calibration, respectively. Results. In the derivation cohort, the SQ, KPS and age were most predictive of 12-month mortality with odds ratios (ORs) [95% conﬁdence interval (CI)] of 3.29 (1.87–5.78) for a ‘No’ response to the SQ, 2.09 (95% CI 1.19–3.66) for fair KPS and 1.41 (95% CI 1.15–1.74) per 10-year increase in age. The c-statistic for the 12-month mortality model for the derivation cohort was 0.80 (95% CI 0.75–0.84) and for the validation cohort was 0.74 (95% CI 0.66–0.83). Conclusions. Our integrated prognostic model for 12-month mortality in patients with advanced CKD had good discrimination and calibration. This model provides prognostic information to aid nephrologists in identifying and counseling advanced CKD patients with poor prognosis who are facing the decision to initiate dialysis or pursue medical management without dialysis.