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Abstract Number: 202

Analysis Of Non-Steroidal Anti-Inflammatory Drug Burden Among Rheumatoid Arthritis Patients Using The Dougados Algorithm

E Alemao1, L Xie2, R Wong1, G Lltalien1 and O Baser3, 1Bristol-Myers Squibb, Princeton, NJ, 2SATinMED Research, Ann Arbor, MI, 3STATinMED Research and University of Michigan, Ann Arbor, MI

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: nonsteroidal antiinflammatory drugs (NSAIDs) and rheumatoid arthritis (RA)

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Session Information

Title: Health Services Research, Quality Measures and Quality of Care-Rheumatoid Arthritis

Session Type: Abstract Submissions (ACR)

Background/Purpose: Non-steroidal anti-inflammatory drugs (NSAIDs) are used to alleviate RA pain symptoms, but they may be associated with adverse events. Previous studies examining clinical and economic outcomes associated with NSAID use in RA have not implemented a systematic algorithm for NSAID use, which would more precisely define the NSAID burden. This study evaluated the correlation between the NSAID intake score developed by Dougados et al.1 and other traditional measures of NSAID burden. In addition, clinical and economic outcomes in patients with high versus low NSAID scores were compared. Methods: A retrospective analysis was performed on RA incidence populations using National Medicare claims data (01/01/2006–12/31/2010) with a 12-month baseline and 24-month follow-up period. Patients had to have at least two RA diagnoses at least 60 days apart between January 1, 2007 and December 31, 2009. The date of the first RA diagnosis was designated as the index date. High, middle and low cohorts were created based on the distribution of the NSAID intake score.1 The correlation between NSAID score and traditional measures was determined by univariate analysis. Clinical and economic outcomes during follow-up were compared with a generalized linear model (GLM). Results: Approximately 19% (n=10,313) of 52,973 incident patients with RA used NSAIDs during the baseline period. Dougados NSAID score correlated with percentage of days with at least one NSAID intake (0.69 [p<0.05]) and number of NSAID tablets (0.59 [p<0.05]). At baseline, 36.34% of patients had a low NSAID score (≤10% follow-up time on diclofenac 150 mg or equivalent), 58.33% had a medium NSAID score (11–90% time on diclofenac 150 mg or equivalent) and 5.32% had a high NSAID score (>90% time on diclofenac 150 mg or equivalent). Compared with the high NSAID cohort, the low NSAID cohort were older (mean age 75.9 vs 74.4 years, p<0.05), had higher Charlson Comorbidity Index scores (3.2 vs 2.8, p=0.05), and higher rates of chronic kidney disease (CKD) (11.39 vs 6.38%, p<0.05), chronic obstructive pulmonary disease (22.9 vs 18.94%, p<0.05), and respiratory disorders (57.54 vs 52.28%, p<0.05). Prior to baseline adjustments, patients in the low NSAID cohort had fewer gastrointestinal perforation cases (0.53 vs 1.28%, p<0.05), and lower per patient per year (PPPY) total costs ($26,235 vs $30,078, p<0.05) and outpatient pharmacy costs ($4,347 vs $6,547, p<0.05) than patients in the high NSAID cohort. After adjusting for baseline differences in demographic and clinical characteristics with the GLM, patients in the high NSAID cohort had a higher risk for CKD (20.23 vs 17.31%, p<0.05), higher PPPY inpatient costs ($13,187 vs $10,652, p<0.05) and higher PPPY outpatient pharmacy costs ($4,605 vs $3,515, p<0.05) during the follow-up period.

Conclusion: The Dougados NSAID algorithm, developed to evaluate NSAID burden in spondyloarthritis, is also applicable to the RA patient population. Medicare patients with RA with high NSAID scores had a higher probability of CKD and higher average in/outpatient costs. Therapies that reduce NSAID burden in elderly patients may protect those with RA from CKD and help reduce cost.

Reference: 1. Dougados M, et al. Ann Rheum Dis 2011;70:249–51.


Disclosure:

E. Alemao,

Bristol-Myers Squibb,

1,

Bristol-Myers Squibb,

3;

L. Xie,

Baistol-Myers Squibb,

5;

R. Wong,

Bristol-Myers Squibb,

1,

Bristol-Myers Squibb,

3;

G. Lltalien,

Bristol-Myers Squibb,

1,

Bristol-Myers Squibb,

3,

SimplySmiles (www.simplysmiles.org),

6;

O. Baser,

Bristol-Myers Squibb,

5.

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