Derivation and Validation of Algorithms to Identify Patients With Immunoglobulin‐G4‐Related 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.

Incidence, prevalence and mortality of IgG4-related disease in the USA: a claims-based analysis of commercially insured adults

“…Additionally, in order to meet the IgG4-RD cohort inclusion criteria, patients must be prescribed medications (eg, glucocorticoids, azathioprine, rituximab) commonly used to treat IgG4-RD (±365 days of the earliest IgG4-RD ICD-9/10 code), have IgG subclass tests performed at least twice (at any time) and have no ICD-9 or ICD-10 codes associated with immune deficiency or inflammatory bowel disease. In a previous study, this algorithm was found to have a positive predictive value (PPV) of 81% and a sensitivity of 58% 12. In validation analyses, the manifestations of IgG4-RD in the assembled cohort reflected those often seen in IgG4-RD cohorts, including sialadenitis, pancreatobiliary disease and renal involvement 12…”

“…In a previous study, this algorithm was found to have a positive predictive value (PPV) of 81% and a sensitivity of 58% 12. In validation analyses, the manifestations of IgG4-RD in the assembled cohort reflected those often seen in IgG4-RD cohorts, including sialadenitis, pancreatobiliary disease and renal involvement 12…”

“…In addition, since the algorithm we used to identify cases only includes patients who received treatment (eg, patients with mild salivary gland disease or surgical resection of a lesion would be excluded) and who have at least two claims for serum IgG4 laboratory tests (eg, patients with a normal baseline IgG4 concentration in whom repeat tests may not be performed are excluded). Because specific ICD-9 or ICD-10 codes for IgG4-RD are unavailable, including treatment and repeat IgG subclass concentration measurements were essential to the validated algorithm to improve its performance 12. To facilitate future studies of the epidemiology of IgG4-RD, ICD-11 should include a code specific for IgG4-RD.…”

“…The details of the derivation and validation of the IgG4-RD case-finding algorithm have been previously described 12. Briefly, the algorithm requires that ICD-9 or ICD-10 codes associated with at least two specific manifestations of IgG4-RD or two codes used to commonly bill for an IgG4-RD encounter be used at least 30 days apart.…”

“…For the main analysis, the number of observed cases was adjusted based on the PPV and sensitivity of the IgG4-RD case definition using the following equation: adjusted cases=PPV×observed cases/sensitivity. However, given that the sensitivity and PPV of the case identification algorithm was validated in a Medicare population12 and may differ in this population of commercially insured patients, standardised incidence rate and point prevalence estimates without this adjustment are also reported (see online supplemental material).…”