2017 European League Against Rheumatism/American College of Rheumatology classification criteria for adult and juvenile idiopathic inflammatory myopathies and their major subgroups

Ingrid E Lundberg, Anna Tjärnlund, Matteo Bottai, Victoria P Werth, Clarissa Pilkington, Marianne de Visser, Lars Alfredsson, Anthony A Amato, Richard J Barohn, Matthew H Liang, Jasvinder A Singh, Rohit Aggarwal, Snjolaug Arnardottir, Hector Chinoy, Robert G Cooper, Katalin Dankó, Mazen M Dimachkie, Brian M Feldman, Ignacio Garcia-De La Torre, Patrick Gordon, Taichi Hayashi, James D Katz, Hitoshi Kohsaka, Peter A Lachenbruch, Bianca A Lang, Yuhui Li, Chester V Oddis, Marzena Olesinska, Ann M Reed, Lidia Rutkowska-Sak, Helga Sanner, Albert Selva-O'Callaghan, Yeong-Wook Song, Jiri Vencovsky, Steven R Ytterberg, Frederick W Miller, Lisa G Rider, International Myositis Classification Criteria Project consortium, The Euromyositis register and The Juvenile Dermatomyositis Cohort Biomarker Study and Repository (JDRG) (UK and Ireland), Ingrid E Lundberg, Anna Tjärnlund, Matteo Bottai, Victoria P Werth, Clarissa Pilkington, Marianne de Visser, Lars Alfredsson, Anthony A Amato, Richard J Barohn, Matthew H Liang, Jasvinder A Singh, Rohit Aggarwal, Snjolaug Arnardottir, Hector Chinoy, Robert G Cooper, Katalin Dankó, Mazen M Dimachkie, Brian M Feldman, Ignacio Garcia-De La Torre, Patrick Gordon, Taichi Hayashi, James D Katz, Hitoshi Kohsaka, Peter A Lachenbruch, Bianca A Lang, Yuhui Li, Chester V Oddis, Marzena Olesinska, Ann M Reed, Lidia Rutkowska-Sak, Helga Sanner, Albert Selva-O'Callaghan, Yeong-Wook Song, Jiri Vencovsky, Steven R Ytterberg, Frederick W Miller, Lisa G Rider, International Myositis Classification Criteria Project consortium, The Euromyositis register and The Juvenile Dermatomyositis Cohort Biomarker Study and Repository (JDRG) (UK and Ireland)

Abstract

Objective: To develop and validate new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIM) and their major subgroups.

Methods: Candidate variables were assembled from published criteria and expert opinion using consensus methodology. Data were collected from 47 rheumatology, dermatology, neurology and paediatric clinics worldwide. Several statistical methods were used to derive the classification criteria.

Results: Based on data from 976 IIM patients (74% adults; 26% children) and 624 non-IIM patients with mimicking conditions (82% adults; 18% children), new criteria were derived. Each item is assigned a weighted score. The total score corresponds to a probability of having IIM. Subclassification is performed using a classification tree. A probability cut-off of 55%, corresponding to a score of 5.5 (6.7 with muscle biopsy) 'probable IIM', had best sensitivity/specificity (87%/82% without biopsies, 93%/88% with biopsies) and is recommended as a minimum to classify a patient as having IIM. A probability of ≥90%, corresponding to a score of ≥7.5 (≥8.7 with muscle biopsy), corresponds to 'definite IIM'. A probability of <50%, corresponding to a score of <5.3 (<6.5 with muscle biopsy), rules out IIM, leaving a probability of ≥50 to <55% as 'possible IIM'.

Conclusions: The European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria for IIM have been endorsed by international rheumatology, dermatology, neurology and paediatric groups. They employ easily accessible and operationally defined elements, and have been partially validated. They allow classification of 'definite', 'probable' and 'possible' IIM, in addition to the major subgroups of IIM, including juvenile IIM. They generally perform better than existing criteria.

Keywords: autoimmune diseases; dermatomyositis; polymyositis.

Conflict of interest statement

Competing interests: JAS has received research grants from Takeda and Savient and consultant fees from Savient, Takeda, Regeneron, Merz, Iroko, Bioiberica, Crealta and Allergan. JAS serves as the principal investigator for an investigator-initiated study funded by Horizon pharmaceuticals through a grant to DINORA, Inc., a 501 (c)(3) entity. JAS is a member of the executive committee of OMERACT, an organisation that develops outcome measures in rheumatology and receives arms-length funding from 36 companies; a member of the American College of Rheumatology’s (ACR) Annual Meeting Planning Committee (AMPC); Chair of the ACR Meet-the-Professor, Workshop and Study Group Subcommittee; and a member of the Veterans Affairs Rheumatology Field Advisory Committee. HC and RGC’s work in myositis is partly funded by grants from Arthritis Research UK (18474) and the Medical Research Council (MR/N003322/1). JV’s work in myositis is supported by Project (Ministry of Health, Czech Republic) for conceptual development of research organization 00023728.

© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Figures

Figure 1
Figure 1
Probability of having idiopathic inflammatory myopathies (IIM) based on the EULAR/ACR classification criteria for IIM. Each score obtained from the classification criteria corresponds to a probability of having the disease, without muscle biopsy data (A), or with muscle biopsy data (B). Each score and probability of disease display a unique set of sensitivity (blue line) and specificity (red line) measurements for the classification criteria not including muscle biopsy data (C) or including muscle biopsy data (D). The most optimal point of accuracy should be stated in publications and be appropriate to the intended purpose, with the recommendation of using a minimum of 55% probability (score of 5.5 without biopsies; 6.7 with biopsies) for classifying a case as IIM (“probable IIM”) (dotted line). “Definite IIM” corresponds to a probability of at least 90% (score of 7.5 without biopsies; 8.7 with biopsies).
Figure 1
Figure 1
Probability of having idiopathic inflammatory myopathies (IIM) based on the EULAR/ACR classification criteria for IIM. Each score obtained from the classification criteria corresponds to a probability of having the disease, without muscle biopsy data (A), or with muscle biopsy data (B). Each score and probability of disease display a unique set of sensitivity (blue line) and specificity (red line) measurements for the classification criteria not including muscle biopsy data (C) or including muscle biopsy data (D). The most optimal point of accuracy should be stated in publications and be appropriate to the intended purpose, with the recommendation of using a minimum of 55% probability (score of 5.5 without biopsies; 6.7 with biopsies) for classifying a case as IIM (“probable IIM”) (dotted line). “Definite IIM” corresponds to a probability of at least 90% (score of 7.5 without biopsies; 8.7 with biopsies).
Figure 1
Figure 1
Probability of having idiopathic inflammatory myopathies (IIM) based on the EULAR/ACR classification criteria for IIM. Each score obtained from the classification criteria corresponds to a probability of having the disease, without muscle biopsy data (A), or with muscle biopsy data (B). Each score and probability of disease display a unique set of sensitivity (blue line) and specificity (red line) measurements for the classification criteria not including muscle biopsy data (C) or including muscle biopsy data (D). The most optimal point of accuracy should be stated in publications and be appropriate to the intended purpose, with the recommendation of using a minimum of 55% probability (score of 5.5 without biopsies; 6.7 with biopsies) for classifying a case as IIM (“probable IIM”) (dotted line). “Definite IIM” corresponds to a probability of at least 90% (score of 7.5 without biopsies; 8.7 with biopsies).
Figure 1
Figure 1
Probability of having idiopathic inflammatory myopathies (IIM) based on the EULAR/ACR classification criteria for IIM. Each score obtained from the classification criteria corresponds to a probability of having the disease, without muscle biopsy data (A), or with muscle biopsy data (B). Each score and probability of disease display a unique set of sensitivity (blue line) and specificity (red line) measurements for the classification criteria not including muscle biopsy data (C) or including muscle biopsy data (D). The most optimal point of accuracy should be stated in publications and be appropriate to the intended purpose, with the recommendation of using a minimum of 55% probability (score of 5.5 without biopsies; 6.7 with biopsies) for classifying a case as IIM (“probable IIM”) (dotted line). “Definite IIM” corresponds to a probability of at least 90% (score of 7.5 without biopsies; 8.7 with biopsies).
Figure 2
Figure 2
Classification tree for subgroups of idiopathic inflammatory myopathies (IIM). A patient must first meet the EULAR/ACR classification criteria for IIM (probability of IIM ≥55%). The patient can then be sub-classified using the classification tree. The subgroup of PM patients includes patients with immune-mediated necrotizing myopathy (IMNM). For IBM classification one of the following, *Finger flexor weakness and response to treatment: not improved, or **Muscle biopsy: rimmed vacuoles, is required for diagnosis. ***Juvenile myositis other than JDM was developed based on expert opinion. IMNM and hypomyopathic DM were too few to allow sub-classification. PM, polymyositis; IMNM, immune-mediated necrotizing myopathy; IBM, inclusion body myositis; ADM, amyopathic dermatomyositis; DM, dermatomyositis; JDM, juvenile dermatomyositis.

Source: PubMed

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