Hyperuricemia is an independent risk factor for renal function decline. Patients treated with ULT who achieved sUA < 6 mg/dl on ULT showed a 37% reduction in outcome events.

Patients who achieve an American College of Rheumatology target sUA below 6 mg/dL during ULT have higher rates of eGFR improvement, especially in CKD Stages 2 and 3.

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BackgroundSerological markers have been investigated for the identification of RA. Current diagnostic criteria recommend conducting tests for anti-citrullinated peptide antibodies (ACPA) and rheumatoid factor (RF) prior to reaching the RA diagnosis. However, there is a lack of information about how these tests are utilized in a managed care setting.ObjectivesTo describe the frequency of ACPA/RF tests at the time of RA diagnosis and at follow-up, as well as to compare baseline characteristics between patients who received ACPA/RF tests and those who did not.MethodsA cohort study was conducted using adult patients newly diagnosed with RA within a US integrated healthcare delivery system from 1 January 2007 to 31 December 2014. Individuals were followed from their first RA diagnosis (index date) until 30 June 2015. Patients were required to have two ICD-9 codes of 714.x, treatment with a DMARD, and continuous eligibility for 12 months prior to the index date (baseline period). At baseline, data were collected on co-morbid conditions, laboratory test results and dispensed medications. Descriptive statistics and multivariable logistic regression analyses were conducted to describe ACPA/RF testing patterns and to investigate baseline patient characteristics associated with ACPA/RF testing.ResultsA total of 7444 patients with newly diagnosed RA were identified. Mean (SD) age was 55.6 (15.0) years, 75% were female, 69% of patients received corticosteroid treatment and 22% had other autoimmune diseases at baseline. Overall, 83% had both ACPA and RF tests at baseline while 10% and 2% had only an RF or an ACPA test, respectively. Baseline ACPA and RF testing rates were increased over time (p<0.001) and both ACPA and RF testing rates were >90% from 2012 onwards (Table). At baseline, 34% of patients had positive ACPA and RF test results, 30% had negative ACPA and RF results, 6% had only ACPA-positive and 21% had only RF-positive results. During follow-up, 20% of patients repeated their ACPA tests; 11% had a repeat test within 1 year of baseline. Patients with a higher Elixhauser index (odds ratio [OR]=0.72, 95% CI 0.62, 0.95) were less likely to receive ACPA tests at baseline, whereas patients receiving NSAIDs (OR=1.45, 95% CI 1.25, 1.69) or corticosteroids (OR=1.23, 95% CI 1.07, 1.43) were more likely to receive baseline ACPA tests. Patients who had other autoimmune conditions were more likely to repeat their ACPA tests during follow-up.Table 1.Baseline ACPA and RF testing rates by index yearIndex yearNew RA patients, total NBaseline ACPA test, N (%)Baseline RF test, N (%)20071095740 (67.6)919 (83.9)2008926703 (75.9)856 (92.4)2009921782 (84.9)870 (94.4)2010914796 (87.1)870 (95.2)2011885812 (91.8)856 (96.7)2012921847 (92.0)880 (95.5)2013919841 (91.5)876 (95.3)2014863829 (96.1)833 (96.5)Total74446350 (85.3)6960 (93.5)ConclusionsACPA and RF testing rates in patients with RA have increased over time, with 96% of patients with newly diagnosed RA receiving both tests at the time of RA diagnosis in 2014. However, there may be still ...

BackgroundClinical pathway analysis is the process of characterizing clinical activities in patients’ (pts) care. Little is known about the clinical pathways that pts with rheumatoid arthritis (RA) follow after their diagnosis, and how treatment patterns differ between such pathways.ObjectivesTo identify and characterize distinct clinical pathways in the management of incident RA pts and evaluate differences in treatment patterns.MethodsA retrospective cohort study was conducted in RA pts identified using electronic medical records of the Kaiser Permanente Southern California health plan. Between 01/01/2007 and 31/12/2015, we identified adult pts (aged ≥18 years) who had at least two RA diagnoses within a 12-month period, a disease-modifying antirheumatic drug (DMARD) prescription and laboratory test for anti-citrullinated peptide antibody. Latent class analysis (LCA) method was applied to identify ≥2 heterogeneous care pathways. RA-specific healthcare utilization during the first year following the RA diagnosis was used as a marker of underlying latent classes. We characterized the latent classes based on the distribution of markers, co-morbidities and RA treatment patterns including switch, augmentation and discontinuation of DMARDs. Chi-square and F-tests were used to evaluate differences between the classes.ResultsWe identified 2843 incident RA pts. LCA indicated five latent classes representing mutually exclusive pathways of managing pts with RA. Pts in Class 1 (low disease activity-low progression) had lowest RA office visits and labs to detectinflammation with the highest DMARD discontinuation. Pts in Class 2 (lowdisease activity-moderate progression) were characterized by higher lab, imaging and DMARD augmentation. Class 3 (moderate disease activity with pain) was characterized by highest use of NSAIDs across any class. Pts in Class 4(high disease activity-moderate progression) were characterized by above-average RA office visits and the highest corticosteroid use. Class 5(high disease activity-high progression) had pts with the highest number of RAoffice visits, biologic DMARD use, DMARD augmentation, DMARD switching and the lowest initial treatment discontinuation.Classification factors Class 1 n=367 Class 2 n=1105 Class 3 n=516 Class 4 n=616 Class 5 n=239 Total N=2843 Age, years (mean)*545656605056Co-morbidities, n (mean)*0.70.90.71.00.60.8Female, %*767880727476Medicare/Medicaid, %*223026371028Switch to new DMARD, %*2598136Augment initial DMARD, %*71637368029Discontinue initial DMARD, %*73493130641Mean predicted utilization of select markers RA office visits, mean count357896Traditional DMARD fills, mean count346655Biologic DMARD fills, mean count<0.010.010.020.046.50.56NSAID fills, mean count114<0.521Corticosteroid fills, mean count112432CT scans, %91319281717MRI, %5815131611RF lab, %22217191517ESR lab, %299888939785CRP lab, %77466657561*Difference between classes are statistically significant; p<0.05ConclusionsWe identified five distinct classes/care pathways; these could be used to identify care gap...