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Developing and Refining New Candidate Criteria for Systemic Lupus Erythematosus Classification: An International Collaboration
Author(s) -
Tedeschi Sara K.,
Johnson Sindhu R.,
Boumpas Dimitrios,
Daikh David,
Dörner Thomas,
Jayne David,
Kamen Diane,
Lerstrøm Kirsten,
Mosca Marta,
RamseyGoldman Rosalind,
Sinnette Corine,
Wofsy David,
Smolen Josef S.,
Naden Raymond P.,
Aringer Martin,
Costenbader Karen H.
Publication year - 2018
Publication title -
arthritis care and research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.032
H-Index - 163
eISSN - 2151-4658
pISSN - 2151-464X
DOI - 10.1002/acr.23317
Subject(s) - rheumatism , anti nuclear antibody , delphi method , delphi , medicine , computer science , autoantibody , artificial intelligence , immunology , antibody , operating system
Objective To define candidate criteria within multiphase development of systemic lupus erythematosus ( SLE ) classification criteria, jointly supported by the American College of Rheumatology and the European League Against Rheumatism. Prior steps included item generation and reduction by Delphi exercise, further narrowed to 21 items in a nominal group technique exercise. Our objectives were to apply an evidence‐based approach to the 21 candidate criteria, and to develop hierarchical organization of criteria within domains. Methods A literature review identified the sensitivity and specificity of the 21 candidate criteria. Data on the performance of antinuclear antibody ( ANA ) as an entry criterion and operating characteristics of the candidate criteria in early SLE patients were evaluated. Candidate criteria were hierarchically organized into clinical and immunologic domains, and definitions were refined in an iterative process. Results Based on the data, consensus was reached to use a positive ANA of ≥1:80 titer ( HE p‐2 cells immunofluorescence) as an entry criterion and to have 7 clinical and 3 immunologic domains, with hierarchical organization of criteria within domains. Definitions of the candidate criteria were specified. Conclusion Using a data‐driven process, consensus was reached on new, refined criteria definitions and organization based on operating characteristics. This work will be followed by a multicriteria decision analysis exercise to weight criteria and to identify a threshold score for classification on a continuous probability scale.