Missed opportunities for treatment of inflammatory arthritis and factors associated with non-treatment: An observational cohort study in United States Veterans with rheumatoid arthritis, psoriatic arthritis, or ankylosing spondylitis.

OBJECTIVE: To identify factors associated with non-treatment with biologic and non-biologic disease modifying anti-rheumatic drugs (DMARDs) during the 12 months after initial inflammatory arthritis (IA) diagnosis. METHODS: We identified Veterans with incident IA diagnosed in 2007-2019. We assessed time to treatment with Kaplan-Meier curves. We identified associations between non-treatment and factors relating to patients, providers, and the health system with multivariate Generalized Estimation Equation (GEE) log-Poisson. Subgroup analyses included IA subtypes (rheumatoid arthritis [RA], psoriatic arthritis [PsA], and ankylosing spondylitis [AS]) and timeframes of the initial IA diagnosis (2007-11, 2012-15, and 2016-19). RESULTS: Of 18,318 study patients, 40.7 % did not receive treatment within 12 months after diagnosis. In all patients, factors associated with non-treatment included Black race (hazard ratio, 95 % confidence interval: 1.13, 1.08-1.19), Hispanic ethnicity (1.14, 1.07-1.22), Charlson Comorbidity Index ≥2, (1.15, 1.11-1.20), and opiate use (1.09, 1.05-1.13). Factors associated with higher frequency of DMARD treatment included married status (0.86, 0.81-0.91); erosion in joint imaging report (HR: 0.86, 0.81-0.91); female diagnosing provider (0.90, CI: 0.85-0.96), gender concordance between patient and provider (0.91, CI: 0.86-0.97), and diagnosing provider specialty of rheumatology (0.53, CI: 0.49-0.56). CONCLUSION: A high proportion of Veterans with IA were not treated with a biologic or non-biologic DMARD within one year after their initial diagnosis. A wide range of factors were associated with non-treatment of IA that may represent missed opportunities for improving the quality of care through early initiation of DMARDs.

Identifying Patients With Axial Spondyloarthritis in Large Datasets: Expanding Possibilities for Observational Research.

OBJECTIVE: Observational research of axial spondyloarthritis (axSpA) is limited by a lack of methods for identifying diverse axSpA phenotypes in large datasets. Algorithms were previously designed to identify a broad spectrum of patients with axSpA, including patients not identifiable with diagnosis codes. The study objective was to estimate the performance of axSpA identification methods in the general Veterans Affairs (VA) population. METHODS: A patient sample with known axSpA status (n = 300) was established with chart review. For feasibility, this sample was enriched with veterans with axSpA risk factors. Algorithm performance outcomes included sensitivities, positive predictive values (PPV), and F1 scores (an overall performance metric combining sensitivity and PPV). Performance was estimated with unweighted outcomes for the axSpA-enriched sample and inverse probability weighted (IPW) outcomes for the general VA population. These outcomes were also assessed for traditional identification methods using diagnosis codes for the ankylosing spondylitis (AS) subtype of axSpA. RESULTS: The mean age was 54.7 and 92% were male. Unweighted F1 scores (0.59-0.74) were higher than IPW F1 scores (0.48-0.65). The full algorithm had the best overall performance (F1IPW 0.65). The Early Algorithm was the most inclusive (sensitivityIPW 0.90, PPVIPW 0.38). The traditional method using ≥ 2 AS diagnosis codes from rheumatology had the highest PPV (PPVIPW 0.84, sensitivityIPW 0.34). CONCLUSION: The axSpA identification methods demonstrated a range of performance attributes in the general VA population that may be appropriate for various types of studies. The novel identification algorithms may expand the scope of research by enabling identification of more diverse axSpA populations.

Treatment Patterns with Disease-Modifying Antirheumatic Drugs in U.S. Veterans with Newly Diagnosed Rheumatoid Arthritis, Psoriatic Arthritis, or Ankylosing Spondylitis.

BACKGROUND: Delays in treatment for inflammatory arthritis (IA) are associated with unfavorable outcomes, including impaired quality of life, irreversible joint damage, and disability. OBJECTIVE: To characterize treatment initiation patterns in veterans with newly diagnosed rheumatoid arthritis (RA), psoriatic arthritis (PsA), or ankylosing spondylitis (AS). METHODS: ICD-9/10-CM codes and natural language processing were used to identify incident cases of RA, PsA, or AS between January 1, 2007, and December 31, 2015, in patients enrolled in the Veterans Health Administration. Patterns of treatment initiation and nontreatment with disease-modifying antirheumatic drugs (DMARDs) were assessed in the 12-month follow-up period after the incident diagnosis. Outcomes included the percentage of veterans treated with a DMARD, the mean time to the initial DMARD after diagnosis, and the percentage of veterans who accessed rheumatology care before DMARD initiation. To assess outcomes over time, veterans were grouped by year of initial IA diagnosis. Additionally, outcomes were compared between nonbiologic and biologic DMARDs and among IA subtypes (RA, PsA, and AS). Groups were statistically compared with 95% confidence intervals. RESULTS: The population consisted of 12,118 IA veterans (9,711 RA, 1,472 PsA, and 935 AS), with 91.3% males and a mean age of 63.7 years. The percentage of veterans treated with ≥ 1 DMARD (nonbiologic or biologic) during the 12-month follow-up period increased from 48.8% in 2007 to 66.4% in 2015. In veterans diagnosed with IA in 2015, DMARD treatment was more common for PsA patients (72.9%) and RA patients (68.6%) than for AS patients (28.9%). In the subset treated with a DMARD within 12 months after diagnosis, the mean time to the initial DMARD after diagnosis did not change throughout the observation period (35.5 days for RA, 43.9 days for PsA, and 59.5 days for AS). Rheumatology specialty care was accessed by 87.4% of veterans treated with a nonbiologic DMARD and 92.2% of veterans treated with a biologic DMARD, in patients diagnosed in 2015. CONCLUSIONS: DMARD treatment rates during the initial 12 months after diagnosis increased between 2007 and 2015, but nontreatment remained common, particularly in veterans with AS. The time to treatment after diagnosis was stable over time; it was shortest for RA, intermediate for PsA, and longest for AS. DMARD treatment was uncommon in veterans who did not access rheumatology specialty care. DISCLOSURES: AbbVie Pharmaceuticals and Marriott Daughters Foundation funded this study via investigator-initiated grants. Data analyses were completed by investigators independent of AbbVie and Marriott Daughters Foundation. Walker, Clewell, and Douglas are employed by, and stockholders in, Abbvie. Halwani reports grants from BMS, Kyowa Hakko Kirin, Seattle Genetics, Roche-Genentech, Miragen, Immunedesign, Takeda, Amgen, Pharmacyclics, and Abbvie. The other authors have nothing to disclose.

Cohort identification of axial spondyloarthritis in a large healthcare dataset: current and future methods.

BACKGROUND: Big data research is important for studying uncommon diseases in real-world settings. Most big data studies in axial spondyloarthritis (axSpA) have been limited to populations identified with billing codes for ankylosing spondylitis (AS). axSpA is a more inclusive concept, and reliance on AS codes does not produce a comprehensive axSpA study population. The first objective was to describe our process for establishing an appropriate sample of patients with and without axSpA for developing accurate axSpA identification methods. The second objective was to determine the classification performance of AS billing codes against the chart-reviewed axSpA reference standard. METHODS: Veteran Health Affairs clinical and administrative data, between January 2005 and June 2015, were used to randomly select patients with clinical phenotypes that represented high, moderate, and low likelihoods of an axSpA diagnosis. With chart review, the sampled patients were classified as Yes axSpA, No axSpA or Uncertain axSpA, and these classification assignments were used as the reference standard for determining the positive predictive value (PPV) and sensitivity of AS ICD-9 codes for axSpA. RESULTS: Six hundred patients were classified as Yes axSpA (26.8%), No axSpA (68.3%), or Uncertain axSpA (4.8%). The PPV and sensitivity of an AS ICD-9 code for axSpA were 83.3% and 57.3%, respectively. CONCLUSIONS: Standard methods of identifying axSpA patients in a large dataset lacked sensitivity. An appropriate sample of patients with and without axSpA was established and characterized for developing novel axSpA identification methods that are anticipated to enable previously impractical big data research.

Adalimumab and Non-Arteritic Anterior Ischaemic Optic Neuropathy: A Case Report.

Sequential anterior ischaemic optic neuropathy was observed in a patient treated with a tumour necrosis factor α (TNF) inhibitor, adalimumab, for ankylosing spondylitis. He developed decreased visual acuity in the right eye after 17 months of treatment. Findings showed right optic disc oedema with haemorrhages and visual field defect. Adalimumab was discontinued and vision stabilised. After restarting adalimumab, he developed optic neuropathy in the left eye. Findings showed optic disc oedema, with haemorrhages and visual field changes in the left eye. Adalimumab may be associated with optic neuropathy; providers prescribing TNF inhibitors should be aware of optic neuropathy as a potential complication.