RT Journal Article
SR Electronic
T1 EULAR/ACR classification criteria for adult and juvenile idiopathic inflammatory myopathies and their major subgroups: a methodology report
JF RMD Open
JO RMD Open
FD EULAR
SP e000507
DO 10.1136/rmdopen-2017-000507
VO 3
IS 2
A1 Bottai, Matteo
A1 Tjärnlund, Anna
A1 Santoni, Giola
A1 Werth, Victoria P
A1 Pilkington, Clarissa
A1 de Visser, Marianne
A1 Alfredsson, Lars
A1 Amato, Anthony A
A1 Barohn, Richard J
A1 Liang, Matthew H
A1 Singh, Jasvinder A
A1 Aggarwal, Rohit
A1 Arnardottir, Snjolaug
A1 Chinoy, Hector
A1 Cooper, Robert G
A1 Danko, Katalin
A1 Dimachkie, Mazen M
A1 Feldman, Brian M
A1 García-De La Torre, Ignacio
A1 Gordon, Patrick
A1 Hayashi, Taichi
A1 Katz, James D
A1 Kohsaka, Hitoshi
A1 Lachenbruch, Peter A
A1 Lang, Bianca A
A1 Li, Yuhui
A1 Oddis, Chester V
A1 Olesinka, Marzena
A1 Reed, Ann M
A1 Rutkowska-Sak, Lidia
A1 Sanner, Helga
A1 Selva-O’Callaghan, Albert
A1 Wook Song, Yeong
A1 Vencovsky, Jiri
A1 Ytterberg, Steven R
A1 Miller, Frederick W
A1 Rider, Lisa G
A1 Lundberg, Ingrid E
A1 ,
YR 2017
UL http://rmdopen.bmj.com/content/3/2/e000507.abstract
AB Objective To describe the methodology used to develop new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIMs) and their major subgroups.Methods An international, multidisciplinary group of myositis experts produced a set of 93 potentially relevant variables to be tested for inclusion in the criteria. Rheumatology, dermatology, neurology and paediatric clinics worldwide collected data on 976 IIM cases (74% adults, 26% children) and 624 non-IIM comparator cases with mimicking conditions (82% adults, 18% children). The participating clinicians classified each case as IIM or non-IIM. Generally, the classification of any given patient was based on few variables, leaving remaining variables unmeasured. We investigated the strength of the association between all variables and between these and the disease status as determined by the physician. We considered three approaches: (1) a probability-score approach, (2) a sum-of-items approach criteria and (3) a classification-tree approach.Results The approaches yielded several candidate models that were scrutinised with respect to statistical performance and clinical relevance. The probability-score approach showed superior statistical performance and clinical practicability and was therefore preferred over the others. We developed a classification tree for subclassification of patients with IIM. A calculator for electronic devices, such as computers and smartphones, facilitates the use of the European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria.Conclusions The new EULAR/ACR classification criteria provide a patient’s probability of having IIM for use in clinical and research settings. The probability is based on a score obtained by summing the weights associated with a set of criteria items.