AB0128 CONSTRUCTION OF THE VETERANS AFFAIRS NATIONAL RHEUMATOID ARTHRITIS DATABASE (VANRAD)
Authors: A. Joseph, J. Yanagida, X. Huang, P. Ranganathan, M. Laurie, H. Xian, S. Eisen
Journal: Annals of the Rheumatic Diseases (2021)

Background: The Department of Veterans Affairs (DVA) provides comprehensive medical care at minimal or no cost to 9 million veterans annually through 170 medical centers and 1074 outpatient clinics across the United States. In 1999, the DVA established a national, fully integrated electronic health record (EHR), which now includes approximately 24 million veterans. However, few studies have used VA EHR data to examine the validity of diagnoses of rheumatoid arthritis (RA). Objectives: Develop a validated, national database (VANRAD) of patients with RA who received VA care since International Classification of Diseases, tenth revision (ICD-10) coding was introduced in 2015. The database will provide infrastructure for retrospective and prospective research to address the ‘real-world’ care of patients with RA. Methods: Patients with the following criteria were identified from the VA EHR as of October 2, 2020: (a) ≥1 ICD-10 diagnosis code of RA; (b) treatment with ≥1 disease-modifying anti-rheumatic drug (DMARD); (c) ≥2 VA rheumatology clinic visits; and (d) ≥1 rheumatoid factor (RF) or anti-cyclic citrullinated peptide (aCCP) antibody test result. From this group, 553 EHRs were randomly selected for review. The ‘gold standard’ for the diagnosis of RA was the treating rheumatologist’s diagnosis, documented in the EHR. Results: 27,482 patients met eligibility criteria. Sociodemographic characteristics were: 85.6% male, mean age of 69.7 years (y) (SD=10.9 y; range=21.9 y to 100.5 y), 76.4% white, 17.0% African American; and mean VA care duration 14.1 y (SD=5.3 y, range=0.04 y to 20.0 y). For patients with ≥1 RF or aCCP test, the positive predictive value (PPV) for RA ranged from 65.3% (aCCP-/RF-) to 95.8% (aCCP+/RF+); rheumatologists’ likelihood of a ‘possible’ diagnosis was higher if the aCCP test result was negative or not available (Table 1). Excluding patients with a second rheumatologic diagnosis did not improve PPV results (data not shown). Table 1. Proportion of patients with a valid RA diagnosis 1 as a function of RF and aCCP laboratory results Test Result aCCP Not Available (0) 2 Negative (-) Positive (+) Total Rheumatoid Factor Not Available (0) (N = 1253) 3 N 427 N 1,159 N 1,586 RA 4 89.7% RA 98.2% RA 93.5% Poss 5 RA 5.9% Poss RA 0.0% Poss RA 3.2% Negative (-) N 810 N 5,308 N 2,005 N 8,123 RA 86.3% RA 65.3% RA 94.5% RA 80.7% Poss RA 3.9% Poss RA 11.9% Poss RA 0.0% Poss RA 5.8% Positive (+) N 2,229 N 2,566 N 12,978 N 17,773 RA 94.6% RA 78.0% RA 95.8% RA 87.6% Poss RA 0.0% Poss RA 8.5% Poss RA 2.1% Poss RA 4.3% Total N 3,039 N 8.301 N 16,142 N 27,482 RA 90.7% RA 76.1% RA 95.9% RA 85.9% Poss RA 1.9% Poss RA 9.2% Poss RA 0.5% Poss RA 4.7% 1 Diagnosis given by the treating rheumatologist. 2 No test results available or test results available but without normal range values. 3 1,253 patients without available or interpretable RF or aCCP excluded from initial cohort. 4 Percent of 553 charts reviewed confirmed as RA. 5 Poss RA = Possible RA. Patients met our inclusion criteria but the treating rheumatologist never made definitive diagnosis of RA or alternative diagnosis (from 553 charts reviewed). The percentage of RA-confirmed patients with one test not available, whose complementary test was negative (RF0/aCCP- or RF-/aCCP0), was greater than of patients for whom both tests were negative (RF-/aCCP-). This suggests our data extraction methods may be incomplete or that unidentified bias may be present and warrants further study. Conclusion: Our methodology for constructing an RA database by selecting patients with ≥2 rheumatology clinic visits, ≥1 ICD-10 diagnosis of RA, and treatment with ≥1 DMARD, has high positive predictive value for RA. Positive RF and aCCP test results were strong predictors of rheumatologists’ diagnostic certainty for an RA diagnosis. Thus, the VANRAD database and the associated EHR provide opportunity for a wide range of retrospective observational and prospective longitudinal studies based on ‘real-world’ patient care. References: [1]Ng B, et al. Arthritis Care Res 2012;64:1490-6; Hanly JG, et al. Open Access Rheumatol 2015;7:69-75. Acknowledgements: This study was sponsored by Bristol Myers Squibb. Disclosure of Interests: Amy Joseph Speakers bureau: Speakers bureau in the distant past., Grant/research support from: Bristol Myers Squibb, Jodi Yanagida: None declared, Xinliang Huang: None declared, Prabha Ranganathan: None declared, Melissa Laurie Shareholder of: Bristol-Myers Squibb, Employee of: I am currently employed by Bristol Myers Squibb., Hong Xian Grant/research support from: Bristol Myers Squibb Co., Seth Eisen Grant/research support from: The effort presented in this Abstract was supported with funds provided by Bristol-Meyers Squibb.