biostudies-literatureWallace ZSNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNIAID NIH HHSNIAMS NIH HHSSanofi371-377https://www.ebi.ac.uk/biostudies/studies/S-EPMC8992468biostudies-literatureUnknown4(4)<h4>Objective</h4>Immunoglobulin-G4-related disease (IgG4-RD) is a systemic autoimmune disease that can affect nearly any organ, but its epidemiology remains poorly understood. Validated algorithms to identify cases in claims data will enable studies to describe IgG4-RD epidemiology in the general population.<h4>Methods</h4>Potential claims-based algorithms were developed by IgG4-RD experts using a combination of International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes, dispensed medications, and procedure codes for immunoglobulin G (IgG) subclass testing. Algorithms were tested using Medicare Parts A, B, and D linked to medical records (2007-2017). Classification of cases as IgG4-RD was determined using theACR open rheumatologyDerivation and Validation of Algorithms to Identify Patients With Immunoglobulin-G4-Related Disease Using Administrative Claims Data.PMC8992468UM1 AI144295K23 AR073334K23AR073334Choi HKStone JHFu XZhang YPerugino CAWallace ZSCook CfalseDerivation and Validation of Algorithms to Identify Patients With Immunoglobulin-G4-Related Disease Using Administrative Claims Data.<h4>Objective</h4>Immunoglobulin-G4-related disease (IgG4-RD) is a systemic autoimmune disease that can affect nearly any organ, but its epidemiology remains poorly understood. Validated algorithms to identify cases in claims data will enable studies to describe IgG4-RD epidemiology in the general population.<h4>Methods</h4>Potential claims-based algorithms were developed by IgG4-RD experts using a combination of International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes, dispensed medications, and procedure codes for immunoglobulin G (IgG) subclass testing. Algorithms were tested using Medicare Parts A, B, and D linked to medical records (2007-2017). Classification of cases as IgG4-RD was determined using the2022-01-01T00:00:00Z2022 Apr2025-04-19T13:01:39.185Z2025-04-19T13:01:39.185ZS-EPMC89924683508014910.1002/acr2.11405