Combining neutrophil and macrophage biomarkers to detect active disease in ANCA vasculitis: a combinatory model of calprotectin and urine CD163
Paula Antón-Pàmpols, Laura Martínez Valenzuela, Loreto Fernández Lorente, María Quero, Francisco Gómez Preciado, Irene Martín Capón, Francisco Morandeira, Joaquín Manrique Escola, Xavier Fulladosa, Josep M. Cruzado, Joan Torrás, Juliana Draibe
Abstract
ABSTRACT Background 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. Methods 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 cohorts (n = 37). We determined the s/uCalprotectin and suCD163 concentration using enzyme-linked immunoassay at the diagnostic or at the remission phase. Receiver operating characteristic (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. Results The concentrations of sCalprotectin and suCD163 were higher in the diagnostic compared with the remission phase (P = .013 and P < .0001). According to the ROC curves, sCalprotectin and suCD163 were accurate biomarkers to discern activity [area under the curve 0.73 (0.59–0.86), P = .015 and 0.88 (0.79–0.97), P < .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 sensitivity, specificity and likelihood ratio of 97%, 90% and 9.7, and 78%, 94% and 13, respectively. Conclusions In patients with ANCA vasculitis, a predictive model combining sCalprotectin, suCD163 and haematuria could be useful in detecting active kidney disease.