Automated evaluation of autoantibodies on human epithelial-2 cells as an approach to standardize cell-based immunofluorescence tests

IntroductionAnalysis of autoantibodies (AAB) by indirect immunofluorescence (IIF) is a basic tool for the serological diagnosis of systemic rheumatic disorders. Automation of AAB IIF reading including pattern recognition may improve intra- and inter-laboratory variability and meet the demand for cost-effective assessment of large numbers of samples.

Comparing automated and visual interpretation, the usefulness for routine laboratory diagnostics was investigated.

Methods: Autoantibody detection by IIF on human epithelial-2 (HEp-2) cells was conducted in a total of 1222 consecutive sera of patients with suspected systemic rheumatic diseases from a university routine laboratory (n=924) and a private referral laboratory (n=298). IIF results from routine diagnostics were compared with a novel automated interpretation system.

Results: Both diagnostic procedures showed a very good agreement in detecting AAB (kappa=0.828) and differentiating respective immunofluorescence patterns.

Only 98 (8.0%) of 1222 sera demonstrated discrepant results in the differentiation of positive from negative samples. The contingency coefficient of Chi-square statistics was 0.646 for the university laboratory cohort with an agreement of 93.0% and 0.695 for the private laboratory cohort with an agreement of 90.6%, P<0.0001, respectively.

Comparing immunofluorescence patterns, 111 (15.3%) sera yielded differing results.

Conclusions: Automated assessment of AAB by IIF on HEp-2 cells using an automated interpretation system is a reliable and robust method for positive/negative differentiation. Employing novel mathematical algorithms, automated interpretation provides reproducible detection of specific immunofluorescence patterns on HEp-2 cells.

Automated interpretation can reduce drawbacks of IIFfor AAB detection in routine diagnostics providing more reliable data for clinicians.

Author: Karl EgererDirk RoggenbuckRico HiemannMax-Georg WeyerThomas BuettnerBoris RadauRosemarie KrauseBarbara LehmannEugen FeistGerd-Rudiger Burmester
Credits/Source: Arthritis Research &Therapy 2010, 12:R40

Published on: 2010-03-09

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