title: Automated evaluation of autoantibodies on human epithelial-2 cells as an approach to standardize cell-based immunofluorescence tests.
abstract: BACKGROUND
  Analysis of autoantibodies (AAB) by indirect immunofluorescence (IIF) is a basic tool for the serological diagnosis of systemic rheumatic disorders. Automation of autoantibody 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 coefficients of chi-square statistics were 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 IIF for AAB detection in routine diagnostics providing more reliable data for clinicians.
authors.affiliation: Department of Rheumatology and Clinical Immunology, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany. karl.egerer@charite.de
authors.forename: Karl
authors.initials: K
authors.lastname: Egerer
authors.forename: Dirk
authors.initials: D
authors.lastname: Roggenbuck
authors.forename: Rico
authors.initials: R
authors.lastname: Hiemann
authors.forename: Max-Georg
authors.initials: MG
authors.lastname: Weyer
authors.forename: Thomas
authors.initials: T
authors.lastname: Büttner
authors.forename: Boris
authors.initials: B
authors.lastname: Radau
authors.forename: Rosemarie
authors.initials: R
authors.lastname: Krause
authors.forename: Barbara
authors.initials: B
authors.lastname: Lehmann
authors.forename: Eugen
authors.initials: E
authors.lastname: Feist
authors.forename: Gerd-Rüdiger
authors.initials: GR
authors.lastname: Burmester
mesh_terms: D001323:Autoantibodies / Q000097:blood*; D002460:Cell Line; D001330:Electronic Data Processing; D019084:Fluorescent Antibody Technique, Indirect / Q000379:methods*; D056945:Hep G2 Cells / Q000276:immunology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015588:Observer Variation; D015203:Reproducibility of Results; D012216:Rheumatic Diseases / Q000097:blood / Q000175:diagnosis* / Q000276:immunology; D012698:Serologic Tests / Q000191:economics / Q000379:methods
chemical_list: D001323:Autoantibodies