title: Evaluation and construction of diagnostic criteria for inclusion body myositis.
abstract: OBJECTIVE
  To use patient data to evaluate and construct diagnostic criteria for inclusion body myositis (IBM), a progressive disease of skeletal muscle.
  
  
  METHODS
  The literature was reviewed to identify all previously proposed IBM diagnostic criteria. These criteria were applied through medical records review to 200 patients diagnosed as having IBM and 171 patients diagnosed as having a muscle disease other than IBM by neuromuscular specialists at 2 institutions, and to a validating set of 66 additional patients with IBM from 2 other institutions. Machine learning techniques were used for unbiased construction of diagnostic criteria.
  
  
  RESULTS
  Twenty-four previously proposed IBM diagnostic categories were identified. Twelve categories all performed with high (≥97%) specificity but varied substantially in their sensitivities (11%-84%). The best performing category was European Neuromuscular Centre 2013 probable (sensitivity of 84%). Specialized pathologic features and newly introduced strength criteria (comparative knee extension/hip flexion strength) performed poorly. Unbiased data-directed analysis of 20 features in 371 patients resulted in construction of higher-performing data-derived diagnostic criteria (90% sensitivity and 96% specificity).
  
  
  CONCLUSIONS
  Published expert consensus-derived IBM diagnostic categories have uniformly high specificity but wide-ranging sensitivities. High-performing IBM diagnostic category criteria can be developed directly from principled unbiased analysis of patient data.
  
  
  METHODS
  This study provides Class II evidence that published expert consensus-derived IBM diagnostic categories accurately distinguish IBM from other muscle disease with high specificity but wide-ranging sensitivities.
authors: From the Departments of Neurology (T.E.L., A.L.M.), Neuroscience (T.E.L.), and Medicine (A.L.M.), Johns Hopkins University School of Medicine and Johns Hopkins Bayview Myositis Center, Baltimore, MD; Department of Neurology (A.A.A., S.A.G.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Department of Neurology (M.D.W.), University of Washington, Seattle; Department of Neurology (M.N.), Australian Neuromuscular Research Institute, University of Western Australia; and Children's Hospital Informatics Program (S.A.G.), Boston Children's Hospital and Harvard-MIT Division of Health Sciences and Technology, Boston, MA. tlloyd4@jhmi.edu sagreenberg@partners.org.
authors: Thomas E
authors: TE
authors: Lloyd
authors: From the Departments of Neurology (T.E.L., A.L.M.), Neuroscience (T.E.L.), and Medicine (A.L.M.), Johns Hopkins University School of Medicine and Johns Hopkins Bayview Myositis Center, Baltimore, MD; Department of Neurology (A.A.A., S.A.G.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Department of Neurology (M.D.W.), University of Washington, Seattle; Department of Neurology (M.N.), Australian Neuromuscular Research Institute, University of Western Australia; and Children's Hospital Informatics Program (S.A.G.), Boston Children's Hospital and Harvard-MIT Division of Health Sciences and Technology, Boston, MA.
authors: Andrew L
authors: AL
authors: Mammen
authors: From the Departments of Neurology (T.E.L., A.L.M.), Neuroscience (T.E.L.), and Medicine (A.L.M.), Johns Hopkins University School of Medicine and Johns Hopkins Bayview Myositis Center, Baltimore, MD; Department of Neurology (A.A.A., S.A.G.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Department of Neurology (M.D.W.), University of Washington, Seattle; Department of Neurology (M.N.), Australian Neuromuscular Research Institute, University of Western Australia; and Children's Hospital Informatics Program (S.A.G.), Boston Children's Hospital and Harvard-MIT Division of Health Sciences and Technology, Boston, MA.
authors: Anthony A
authors: AA
authors: Amato
authors: From the Departments of Neurology (T.E.L., A.L.M.), Neuroscience (T.E.L.), and Medicine (A.L.M.), Johns Hopkins University School of Medicine and Johns Hopkins Bayview Myositis Center, Baltimore, MD; Department of Neurology (A.A.A., S.A.G.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Department of Neurology (M.D.W.), University of Washington, Seattle; Department of Neurology (M.N.), Australian Neuromuscular Research Institute, University of Western Australia; and Children's Hospital Informatics Program (S.A.G.), Boston Children's Hospital and Harvard-MIT Division of Health Sciences and Technology, Boston, MA.
authors: Michael D
authors: MD
authors: Weiss
authors: From the Departments of Neurology (T.E.L., A.L.M.), Neuroscience (T.E.L.), and Medicine (A.L.M.), Johns Hopkins University School of Medicine and Johns Hopkins Bayview Myositis Center, Baltimore, MD; Department of Neurology (A.A.A., S.A.G.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Department of Neurology (M.D.W.), University of Washington, Seattle; Department of Neurology (M.N.), Australian Neuromuscular Research Institute, University of Western Australia; and Children's Hospital Informatics Program (S.A.G.), Boston Children's Hospital and Harvard-MIT Division of Health Sciences and Technology, Boston, MA.
authors: Merrilee
authors: M
authors: Needham
authors: From the Departments of Neurology (T.E.L., A.L.M.), Neuroscience (T.E.L.), and Medicine (A.L.M.), Johns Hopkins University School of Medicine and Johns Hopkins Bayview Myositis Center, Baltimore, MD; Department of Neurology (A.A.A., S.A.G.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Department of Neurology (M.D.W.), University of Washington, Seattle; Department of Neurology (M.N.), Australian Neuromuscular Research Institute, University of Western Australia; and Children's Hospital Informatics Program (S.A.G.), Boston Children's Hospital and Harvard-MIT Division of Health Sciences and Technology, Boston, MA. tlloyd4@jhmi.edu sagreenberg@partners.org.
authors: Steven A
authors: SA
authors: Greenberg
mesh_terms: D000328:Adult; D001185:Artificial Intelligence / Q000592:standards*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018979:Myositis, Inclusion Body / Q000175:diagnosis* / Q000453:epidemiology*; D012189:Retrospective Studies