title: Patient and clinical characteristics associated with gout flares in an integrated healthcare system.
abstract: Gout flares have been challenging to identify in retrospective databases due to gout flares not being well documented by diagnosis codes, making it difficult to conduct accurate database studies. Previous studies have used different algorithms, and in this study, we used a computer-based method to identify gout flares. The objectives of this study were to identify gout flares in gout patients newly initiated on urate-lowering therapy and evaluate factors associated with a patient experiencing gout flares after starting drug treatment. This was a retrospective cohort study identifying gout patients newly initiated on a urate-lowering therapy (ULT) during the study time period of January 1, 2007-December 31, 2010. The index date was the first dispensed ULT prescription during the study time period. Patients had to be ≥18 years of age on index date, have no history of prior ULT prescription during 12 months before index date, and were required to have 12 months of continuous membership with drug benefit during pre-/post-index. Electronic chart notes were reviewed to identify gout flares; these reviews helped create a validated computer-based method to further identify patients with gout flares and were categorized into 0 gout flares, 1-2 gout flares, and ≥3 gout flares during the 12 months post-index period. Multivariable logistic regression was used to examine patient and clinical factors associated with gout flares during the 12-month follow-up period. There were 8905 patients identified as the final cohort and 68 % of these patients had one or more gout flares during the 12-month follow-up: 2797 patients (31 %) had 0 gout flares, 4836 (54 %) had 1-2 gout flares, and 1272 patients (14 %) had ≥3 gout flares. Using a multivariate regression analyses, factors independently associated with 1-2 gout flares and ≥3 gout flares versus no gout flares were similar, however, with slight differences, such as younger patients were more likely to have 1-2 gout flares and patients ≥65 years of age had ≥3 gout flares. Factors such as male gender, not attaining sUA goal, having ≥3 comorbidities, diuretics use, no changes in initial ULT dose, and not adhering to ULT all were associated with gout flares versus no gout flares. Using a new method to identify gout flares, we had the opportunity to compare our findings with the previous studies. Our study findings echo other previous studies where older patients, male, diuretics, having a greater number of comorbidities, and non-adherence are more likely to have more gout flares during the first year of newly initiating ULT. There is an unmet need for patients with gout to be educated and managed more closely, especially during the first year.
authors.affiliation: Drug Information Services, Kaiser Permanente SCAL Region, 12254 Bellflower Blvd, Room 106, 1st Floor, Downey, CA, 90242, USA. Nazia.X.Rashid@kp.org.
authors.forename: Nazia
authors.initials: N
authors.lastname: Rashid
authors.affiliation: Southern California Permanente Medical Group, Kaiser Permanente Southern California, Downey, CA, USA.
authors.forename: Gerald D
authors.initials: GD
authors.lastname: Levy
authors.affiliation: Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
authors.forename: Yi-Lin
authors.initials: YL
authors.lastname: Wu
authors.affiliation: Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
authors.forename: Chengyi
authors.initials: C
authors.lastname: Zheng
authors.affiliation: Drug Information Services, Kaiser Permanente SCAL Region, 12254 Bellflower Blvd, Room 106, 1st Floor, Downey, CA, 90242, USA.
authors.forename: River
authors.initials: R
authors.lastname: Koblick
authors.affiliation: Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
authors.forename: T Craig
authors.initials: TC
authors.lastname: Cheetham
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D002140:California; D016009:Chi-Square Distribution; D019033:Delivery of Health Care, Integrated; D018450:Disease Progression; D011307:Drug Prescriptions; D057286:Electronic Health Records; D005260:Female; D006073:Gout / Q000097:blood / Q000175:diagnosis / Q000188:drug therapy*; D006074:Gout Suppressants / Q000009:adverse effects / Q000627:therapeutic use*; D006279:Health Maintenance Organizations; D006801:Humans; D033461:Hyperuricemia / Q000097:blood / Q000175:diagnosis / Q000188:drug therapy*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D012189:Retrospective Studies; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D014527:Uric Acid / Q000097:blood
chemical_list: D015415:Biomarkers; D006074:Gout Suppressants; D014527:Uric Acid
keywords: Adherence; Gout; Gout flares; Serum uric acid goal; Urate-lowering therapy