#6470 patient survival in an associated vasculitis cohort – data from a refferal center

Abstract Background and Aims Patients with ANCA associated vasculitis (AAV) have variable survival rates depending on disease activity, complications and sometimes the choice of treatment. Still today there are a lot of differencies between various cohorts regardless of similarities in clinical presentation, serology or histology. Understanding risk factors for various outcomes in cohorts from different geographical areas might help build better and more uniform prediction models. We present data on patient survival from our refferal center. Method This study included 106 consecutive AAV patients with biopsy proven renal involvement in the period from 2007-2017. We analyzed clinical, laboratory and pathohistological data as predictors for death of the patients. Survival univariate analysis was performed using Kaplan-Meier method and log-rank (Mantel-Cox) test. Variables that had p<0,1 in univariate analysis were alongside age and gender included in multivariate Cox proportional hazard model. Results The study included 106 AAV patients with renal involvement: 66 (61,1%) MPA, 20 (18,5%) GPA, 20 (18,5%) RLV. There were 14 (13%) PR3-ANCA positive patients, 57 (52,8%) MPO ANCA positive, 5 (4,6%) PR3-ANCA+MPO-ANCA and 32 (29,6%) ANCA negative patients. Average SCr was 316,5 μmol/l (IQR 207,0-548,5), 24-hour proteinuria median was 1,7g/24h (IQR 0,8-2,8). Histologicaly (Berden classification) 43 (39,8%) patients had crescentic, 19 (17,6%) focal, 34 (31,5%) mixed and 12 (11,1%) sclerotic class. Follow up time was 1 to 127 months with median 21 months (IQR = 7 - 44) and medium follow up time of 28,6 months (SD = 26,6). All the patients recieved the same induction treatment (cyclophosphamide and glucocorticoids +/- acute haemodialysis and plasma exchange treatment) and remission maintenance treatment (azathioprine). During the follow up 21 patient (19,8%) died. Out of those 13 were females. Main causes of death were either infections or cardiovascular diseases. In follow up period patient survival was 83,9-81,2-79-74,7% at 12-24-36-60 months. There were no differences in survival rates between clinical, histological or serological phenotypes. In univariate analysis significant predictors for death of patients were: age (>68 years; p = 0,002), anaemia (Haemoglobin <96 g/l; p = 0,001), increased CRP levels (CRP > 63mg/l; p = 0,001), lower serum C3 levels (p = 0,001), BVAS > 18 (p = 0,003) and the need for dialysis (p = 0,06). In multivariate analysis however significant predictors for the death of patients were age (HR = 1,059, 95% CI = 1,001-1,120; p = 0,046), anaemia (HR = 0,952, 95% CI = 0,908-0,998; p = 0,040) and BVAS (HR = 1,093, 95% CI = 1,030-1,159; p = 0,003). Interestingly in additional analysis PLEX was, alongside acute haemodialysis, significant predictor in combined ESRD/death outcome (as well as for ESRD and relapse rate) but not for death alone. Conclusion In our data disease activity as defined by BVAS and anaemia alongside the patient age are predictors for the patient survival. Anaemia is not included either in BVAS or in other disease activity scores or prediction models. Considering its potential impact on multiple organ functions perhaps anaemia levels should be included either in BVAS or perhaps in VDI though anaemia itself is mostly not autoimmune phenomenon in AAV patients. Also in our cohort PLEX wasn't a significant predictor for patient survival.