{"doi":"10.1002/acr2.11405","title":"Derivation and Validation of Algorithms to Identify Patients With Immunoglobulin‐<scp>G4‐Related</scp> Disease Using Administrative Claims Data","abstract":"OBJECTIVE: 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. METHODS: 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 the American College of Rheumatology (ACR) and European League Against Rheumatism (EULAR) classification criteria for IgG4-RD. We estimated the positive predictive value (PPV) of each algorithm; sensitivity was determined using a cohort of patients with IgG4-RD also enrolled in Medicare Parts A, B, and D during the study period. RESULTS: We identified seven algorithms that used a combination of ICD-9 and ICD-10 codes, medication prescriptions, and/or IgG subclass tests to identify patients with IgG4-RD. The PPV of algorithms in the derivation cohort ranged from 57% to 100%, and sensitivity ranged from 0% to 58%. The best performing algorithm in the validation cohort had a PPV of 81% and a sensitivity of 58%. Typical IgG4-RD manifestations were observed in the cohort (n = 36) assembled by this algorithm, including 50% with sialadenitis, 64% with pancreatic disease, 31% with renal disease, and 59% with an elevated IgG4 concentration. CONCLUSION: We derived and validated a well-performing algorithm to identify IgG4-RD cases with typical manifestations of the disease. The claims-based algorithm can be used in research studies of IgG4-RD.","journal":"ACR Open Rheumatology","year":2022,"id":280587,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9103,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":236762,"name":"Xiaoqing Fu","orcid":"0009-0007-8267-8761","position":1,"is_corresponding":false},{"id":687300,"name":"Claire Cook","orcid":null,"position":2,"is_corresponding":false},{"id":282411,"name":"Cory A. Perugino","orcid":"0000-0002-0812-4353","position":3,"is_corresponding":false},{"id":254684,"name":"Yuqing Zhang","orcid":"0000-0001-7638-0888","position":4,"is_corresponding":false},{"id":25215,"name":"John H. Stone","orcid":"0000-0001-6588-9435","position":5,"is_corresponding":false},{"id":236763,"name":"Hyon K. Choi","orcid":"0000-0002-2862-0442","position":6,"is_corresponding":false},{"id":236765,"name":"Zachary S. Wallace","orcid":"0000-0003-4708-7038","position":0,"is_corresponding":true}],"reference_count":12,"raw_metadata":null,"created_at":"2026-07-19T00:29:03.247347Z","pmid":"35080149","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}