Validity and reliability of serologic immunophenotyping of multiple blood group systems by ORTHO Sera with fully automated procedure

The increase of immunization against blood group antigens has reinforced the need for automated extensive blood typing. The aim of this study was to assess both the validity and reliability of red blood cell (RBC) automated agglutination technology in testing for antigens of Kidd (Jk), Duffy (Fy), and MNS (Ss) blood systems. ORTHO Sera (Ortho Clinical Diagnostics, Raritan, NJ) anti-Jk^a, anti-Jk^b, Anti-Fy^a, anti-Fy^b, anti-S, and anti-s reagents were each tested on RBC samples previously typed. Replicates were performed on three separate testing sessions with three consecutive repetitions within each session, thus obtaining 486 test results. Accuracy was assessed by aggregate analysis of sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). Reliability was estimated by a cross-classified mixed-effect logistic model. All reagents tested yielded optimal accuracy (100% for sensitivity and specificity, and 1.00 for AUC), except for anti-S, for which performance was slightly lower (98%, 100%, and 0.99, respectively), owing to misclassification of one sample in a single replicate. Anomalous automated measurements were recorded in 38 of 486 tests (7.8%), which then needed additional manual interpretation. Different sessions and samples were the major contributors to measurement failures (38% and 18%, separately). Order of repetitions and antigen specificity across replicates did not contribute to the risk of failures, although weak evidence of enhanced risk (p < 0.10) was observed with Jk testing. Automated RBC typing with ORTHO Sera reagents against antigens in the Kidd, Duffy, and MNS blood group systems displayed nearly 100 percent accuracy. However, a sizable number of replicates needed additional ad hoc interpretation, thus suggesting that the reliability could still be improved. Automated agglutination technology represents a viable option for phenotyping large volumes of samples. Immunohematology 2018;34:140–147.