Combining neutrophil and macrophage biomarkers to detect active disease in ANCA vasculitis: a combinatory model of calprotectin and urine CD163


 
 
 CD163 and calprotectin have been proposed as biomarkers of active renal vasculitis. This study aimed to determine whether the combination of serum/urine calprotectin (s/uCalprotectin) and urinary soluble CD163 (suCD163) increases their individual performance as activity biomarkers.
 
 
 
 We included 138 patients diagnosed with ANCA vasculitis (n = 52 diagnostic phase, n = 86 remission). The study population was divided into the inception (n = 101) and the validation cohort (n = 37). We determined the s/uCalprotectin and suCD163 concentration using ELISA at the diagnostic or at the remission phase. ROC curves were conducted to assess the biomarkers’ classificatory values. We elaborated a combinatorial biomarker model in the inception cohort. The ideal cutoffs were used in the validation cohort to confirm the model's accuracy in the distinction between active disease and remission. We added the classical ANCA vasculitis activity biomarkers to the model to increase the classificatory performance.
 
 
 
 sCalprotectin and suCD163’s concentration was higher in the diagnostic compared to the remission phase, P = 0 013 and P < 0,0001. According to the ROC curves, sCalprotectin and suCD163 were accurate biomarkers to discern activity [AUC 0,73 (0,59–0 806), P = 0 015 and 0,88 (0,79–0,97), P < 0,0001]. The combinatory model with the best performance in terms of sensitivity, specificity, and likelihood ratio included sCalprotectin, suCD163, and haematuria. Regarding the inception and the validation cohort, we obtained a sensibility, specificity, and a likelihood ratio of 97%, 90%, and 9,7 and 78%, 94%, and 13, respectively.
 
 
 
 In patients with ANCA vasculitis, a predictive model combining sCalprotectin, suCD163, and haematuria could be useful in detecting active kidney disease.
