Abstract
Objective:
Although hyperuricemia and gout can complicate the course of rheumatoid arthritis (RA), the impact of these factors on outcomes in RA is unclear. We examined associations of coexistent hyperuricemia and gout with RA disease measures, RA treatments, and survival.
Methods:
Participants from a longitudinal RA study were categorized by the presence of gout and serum urate (sUA) status. Groups were compared by baseline patient characteristics, RA disease activity, treatments, and comorbidities. Associations of baseline sUA levels with all-cause and cardiovascular disease (CVD)-related mortality were examined in multivariable survival analyses.
Results:
Of 1,999 participants with RA, 341 (17%) had sUA concentrations >6.8 mg/dl and 121 (6.1%) were diagnosed with gout. There were no significant associations of enrollment sUA or gout with RA disease activity or treatment with the exception that those with gout were more likely to be receiving sulfasalazine and less likely to be receiving NSAIDs. After age-and sex-adjustment, moderate hyperuricemia (sUA >6.8–8 mg/dl) was associated with an increased risk of CVD-related mortality (HR 1.56; 95% CI 1.11–2.21). This association was attenuated and not significant following additional adjustment for comorbidities that more commonly accompanied hyperuricemia. Results corresponding with sUA >8.0 mg/dl were similar, although not reaching statistical significance in any model. There were no associations of baseline sUA with all-cause mortality.
Conclusion:
Our study reports the frequency of hyperuricemia and gout in patients with RA. These results demonstrate strong associations of hyperuricemia with CVD mortality in this population, a risk that appears to be driven by excess comorbidity.
Keywords: rheumatoid arthritis, gout, hyperuricemia, disease activity, mortality
Rheumatoid Arthritis (RA) is a chronic and progressive autoimmune disease that causes both systemic and articular inflammation, primarily of the small joints of the hands and feet. Gout on the other hand, is an inflammatory arthropathy caused by the deposition of articular and periarticular monosodium urate (MSU) crystals occurring in the context of chronic hyperuricemia. Although the coexistence of gout and RA has traditionally been thought to be exceedingly rare (1), the Rochester Epidemiology Project in 2007 reported a 25-year cumulative gout prevalence of more than 5% in patients with RA (2). Further studies have revealed that a significant proportion of RA patients demonstrate evidence of MSU deposition consistent with gout, challenging previous perceptions that gout and RA are mutually exclusive conditions (3).
Apart from the potential misclassification of either condition, the identification of gout in patients with RA may have additional implications. Hyperuricemia, a necessary risk factor for gout, has been associated with cardiovascular and renal disease, suggesting that serum urate (sUA) concentrations might be of prognostic value in patients with RA in addition to those with gout. The pathogenesis of gouty arthritis is relatively well understood with uric acid and urate crystals acting as pro-inflammatory stimulants (4–6). Gout is associated with an approximate two-fold increased risk for cardiovascular disease and mortality in comparison to the general population (7–9). Further, in both gout and non-gout populations, individuals with elevated sUA have an approximate 3-fold increased risk of developing incident cardiovascular disease (10). As in the general population (11, 12), sUA concentrations are strongly correlated with renal dysfunction in RA (13), highlighting the potential of sUA as a biomarker for early detection of renal impairment. Hyperuricemia has also been associated with peripheral vascular disease and appears to be more strongly associated with mortality in patients with RA compared to individuals without RA (14). Together, these studies suggest that both hyperuricemia and gout are more common in RA than previously appreciated and may portend important long-term consequences.
However, the potential influence of hyperuricemia and/or gout on RA disease activity, medication selection, and long-term outcomes remains unknown. Thus, the objectives of this study were: 1) to examine the co-occurrence of gout and hyperuricemia with RA; 2) to examine associations of RA disease activity and treatment based on the presence of comorbid gout or hyperuricemia; and 3) to determine associations of gout and hyperuricemia with mortality in patients with RA. . We hypothesized that RA patients with coexistent hyperuricemia or gout would have more severe RA, require more aggressive therapy reflected in a higher rate of prednisone and/or biologic use, and would suffer from greater mortality.
Patients and Methods
Study Participants
A total of 1,999 participants enrolled in the multicenter Veterans Affairs Rheumatoid Arthritis (VARA) registry and were included in this study (15). There were an additional 242 VARA participants excluded from the study due to missing covariates. VARA is a longitudinal observational cohort of United States (US) military Veterans with RA, all fulfilling the 1987 American College of Rheumatology (ACR) classification criteria (16). Enrollment was initiated in January of 2003 and for this study patients were followed until death or through December 2015. Rheumatology clinics from Veterans Affairs (VA) medical centers in the following 12 US cities enrolled patients included in this study: Birmingham, Alabama; Brooklyn, New York; Dallas, Texas; Denver, Colorado; Iowa City, Iowa; Jackson, Mississippi; Little Rock, Arkansas; Omaha, Nebraska; Philadelphia, Pennsylvania; Portland, Oregon; Salt Lake City, Utah; and Washington, DC. The registry contains clinical measurements obtained at enrollment and at follow up visits in addition to a biological repository of banked serum from enrollment. Written informed consent prior to enrollment was obtained from all participants. This study was approved by Institutional Review Boards at all participating centers and by the VARA Scientific Ethics Advisory Committee.
Gout Status
Using established links between VARA and the national VA Corporate Data Warehouse (CDW) contained within the VA Informatics and Computing Infrastructure, we examined for the presence of at least one International Classification of Diseases, 9th or 10th edition (ICD9 or ICD10) code for gout during the 12-month period preceding VARA enrollment and extending through study follow-up. Medical records of all individuals with at least one diagnostic code for gout were then reviewed for evidence of MSU deposition confirmed by polarized microscopy, with results detailed in either a laboratory report or rheumatology provider note. In addition to documented crystal confirmation, patients were also considered to have gout if there were two or more gout codes separated by 30 to 365 days in addition to at least one diagnostic code coming from a rheumatologist provider or receipt of at least two prescriptions for urate lowering therapy (allopurinol, febuxostat or probenecid) during observation. Gout cases were classified as either pre-or post-enrollment based on when these diagnoses were given relative to VARA enrollment.
Serum Urate Measurement
Serum urate (sUA) concentrations were measured in a central laboratory using samples collected at enrollment and the VITROS URIC Slide Chemistry method (Ortho Clinical Diagnosis, Raritan, NJ), which uses the uricase reaction. In order to determine if there was a “dose phenomenon” associated with differing severity of hyperuricemia, we categorized patients into three groups: sUA ≤6.8 mg/dl, sUA >6.8 to 8 mg/dl, and sUA >8 mg/dl. Rather than using different definitions of hyperuricemia for men and women, a single sUA threshold of 6.8 mg/dl was used to define hyperuricemia as this is the concentration at which uric acid precipitates into MSU crystals at a physiologic pH irrespective of sex (17). Concentrations >8.0 mg/dl have been used in recent work to define patients with more severe hyperuricemia (18).
Clinical Measurements
Patient characteristics collected at VARA enrollment included age, sex, self-reported race/ethnicity, education, smoking status (never, former, current), body mass index (BMI, kg/m2), and date of RA diagnosis. BMI was calculated from height and weight values in CDW. Enrollment BMI was modeled in categories (< 20, 20 to ≤ 25, >25 to ≤ 30, >30 to ≤ 35, and >35 kg/m2) with the 20 to ≤ 25 kg/m2 group (normal body weight) acting as the reference group. In addition, we recorded medication use and RA classification criteria (e.g. subcutaneous nodules and radiographic changes) at enrollment. At enrollment and at each follow up visit, swollen and tender joint counts (0 to 28 joints), provider and patient global assessments (using 100-mm visual analog scales), erythrocyte sedimentation rate (ESR), and a 10-item Multidimensional Health Assessment Questionnaire (MD-HAQ: range 0 to 3) (19) were obtained. Based on visit data, the Disease Activity Score in 28 joints (DAS 28) (20) was calculated with scores categorized as remission, low, moderate, or high disease activity. Utilizing banked serum from enrollment, a high-sensitivity C-reactive protein (hsCRP) was measured by nephelometry while anti-cyclic citrullinated peptide (anti-CCP) antibody was measured using a second-generation commercial enzyme-linked immunosorbent assay (21).
Comorbidities
Using the Healthcare Cost and Utilization Project Clinical Classifications Software (HCUP-CCS) from the Agency for Healthcare Quality and Research, comorbid conditions were aggregated for the 12 months prior to enrollment from VA national administrative data. The Rheumatic Disease Comorbidity Index (RDCI) was calculated as an overall comorbidity score (22). The RCDI consists of the following comorbid conditions: myocardial infarction (MI) or atherosclerosis, other CVD, stroke, hypertension, chronic kidney disease (CKD), kidney problems, lung disease, diabetes mellitus, cancer, ulcer or stomach problem, depression, and fracture.
Survival Outcomes
Cardiovascular-related and all-cause mortality were identified using the National Death Index (NDI) (National Center for Health Statistics, US Department of Health and Human Services). NDI is a centralized database of death record information that reflects state vital statistics office records. The database is maintained by the US Centers for Disease Control and Prevention and is matched to the VA data by the Veterans Health Administration Suicide Data Repository. These records include date of death and cause of death as recorded by ICD-10 codes. Cardiovascular mortality was defined as any death attributed to an ICD-10 code within Chapter IX (I00-I99).
Statistical Analyses
Baseline characteristics were compared by gout and sUA categories using one-way ANOVA, Kruskal-Wallis, Wilcoxon rank sum, or student’s t-tests for continuous variables while categorical values were examined using Pearson chi-square tests or Fisher’s exact tests, as appropriate.
Crude mortality rates and corresponding 95% confidence intervals (95% CIs) were calculated for all-cause and CVD-related deaths. The association of baseline sUA concentration with all-cause mortality was examined graphically using cumulative incidence plots and then by using a series of sequential Cox models. Model A included only age and sex as covariates. An intermediate model, Model B, again included age and sex as covariates in addition to race (white vs. non-white), smoking status at enrollment, BMI, RDCI score, CKD at enrollment, DAS28 category, and prednisone use. A fully-adjusted model, Model C, included all of the covariates included in model B in addition to gout, the latter modeled as a time-varying covariate as some of these cases developed during follow up. Using the same covariates and multiple models, associations with CVD-related mortality were examined using competing-risks regression in order to account for the potential masking of associations between risk factors and specific causes of death (23). The selection of covariates included in multivariable analyses of all-cause and CVD-related morality was informed by prior work from this cohort (24, 25). Complete case analysis was performed with exclusion of participants with missing covariates from the final model. All models were adjusted for clustering within VA site and all analyses were conducted using Stata, version 15.1.
Results
Participant characteristics.
Of 1,999 participants with RA and complete data available, there were 341 (17%) with sUA concentrations >6.8 mg/dl at enrollment. The overall mean (±SD) sUA concentration was 5.48 (1.73) mg/dl, 5.57 (1.72) mg/dl among men with RA and 4.60 (1.56) mg/dl among women with RA. Of these, 120 (6.0% of total) had sUA concentrations >8.0 mg/dl. At enrollment, 86 patients (4.3%) carried a diagnosis of gout. Of the remaining 1,913 participants who were gout free at enrollment, an additional 35 (1.8%) developed incident gout during follow up, resulting in a cumulative gout incidence of 6.1%. Medical record review demonstrated evidence of MSU crystal confirmation from a diagnostic aspirate in 41 (34%) of the 121 gout cases. Of those with crystal confirmed gout, most (63%) were also positive for anti-CCP antibody.
Factors associated with baseline sUA and gout status
Compared to patients with normal sUA concentrations at enrollment, RA patients with hyperuricemia were older (p=0.014), more frequently male (p<0.001), and had higher BMI values (p<0.001) (Table 1). Likewise, RA patients with hyperuricemia had a greater comorbidity burden as demonstrated by higher RDCI scores (p<0.001) and a higher prevalence of both hypertension (p<0.001) and CKD (p<0.001). Similar to results following stratification by baseline sUA status, RA participants with a history of gout at enrollment were older (p=0.001) and more frequently male (p=0.006) than participants without gout (Table 2). Similar to those with hyperuricemia, gout was associated with a greater comorbidity including a higher prevalence of both hypertension (p<0.001) and CKD (p<0.001). In contrast to results stratified by sUA status, patients with gout were substantially more likely to be diabetic (38% vs. 20%; p<0.001) when compared with those without a baseline gout diagnosis.
Table 1:
Demographics and comorbidity by serum urate (sUA) concentration at the time of VARA enrollment*
| Total (n=1999) | sUA ≤ 6.8 mg/dl (n=1658) | sUA > 6.8 to ≤ 8.0 mg/dl (n = 221) | sUA > 8.0 mg/dl (n = 120) | P-value | |
|---|---|---|---|---|---|
| Age, years, mean (SD) | 64 (11) | 64 (11) | 66 (10) | 66 (10) | 0.014 |
| Male sex, % | 90 | 89 | 96 | 96 | <0.001 |
| Caucasian, % | 78 | 78 | 76 | 76 | 0.877 |
| ≥ High school education, % | 86 | 86 | 84 | 89 | 0.563 |
| Smoking, % | 0.052 | ||||
| Never | 20 | 20 | 19 | 19 | |
| Former | 54 | 53 | 57 | 62 | |
| Current | 27 | 28 | 24 | 19 | |
| BMI category, kg/m2, % | <0.001 | ||||
| < 20 | 4 | 5 | 3 | 2 | |
| 20 to 25 | 24 | 25 | 20 | 13 | |
| > 25 to 30 | 37 | 38 | 36 | 35 | |
| > 30 to 35 | 23 | 22 | 24 | 31 | |
| > 35 | 12 | 10 | 17 | 19 | |
| RDCI score, mean (SD) | 1.9 (1.5) | 1.9 (1.5) | 2.1 (1.5) | 2.4 (1.5) | <0.001 |
| MI or atherosclerosis, % | 3 | 3 | 3 | 3 | 0.948 |
| Other cardiovascular disease, % | 26 | 25 | 33 | 38 | <0.001 |
| Hypertension, % | 56 | 54 | 66 | 76 | <0.001 |
| Chronic kidney disease, % | 5 | 3 | 10 | 15 | <0.001 |
| Diabetes mellitus | 21 | 21 | 19 | 23 | 0.662 |
VARA = Veterans Affairs Rheumatoid Arthritis registry; SD = standard deviation; MI = body mass index; RDCI = Rheumatic Disease Comorbidity Index; MI = myocardial infarction
Table 2:
Demographics and comorbidity by gout diagnosis at VARA enrollment*
| RA patients without gout (n=1913) | RA patients with gout (n=86) | P-value | |
|---|---|---|---|
| Age, years, mean (SD) | 64 (11) | 68 (10) | 0.001 |
| Male sex, % | 90 | 99 | 0.006 |
| Caucasian, % | 78 | 73 | 0.325 |
| ≥ High school education, % | 86 | 88 | 0.566 |
| Smoking, % | 0.398 | ||
| Never | 20 | 19 | |
| Former | 54 | 60 | |
| Current | 27 | 21 | |
| BMI category, kg/m2, % | 0.065 | ||
| < 20 | 5 | 1 | |
| 20 to 25 | 24 | 16 | |
| > 25 to 30 | 37 | 45 | |
| > 30 to 35 | 23 | 20 | |
| > 35 | 11 | 17 | |
| RDCI score, mean (SD) | 1.9 (1.5) | 2.2 (1.5) | 0.136 |
| MI or atherosclerosis, % | 3 | 7 | 0.021 |
| Other cardiovascular disease, % | 26 | 34 | 0.111 |
| Hypertension, % | 55 | 74 | <0.001 |
| Chronic kidney disease, % | 4 | 16 | <0.001 |
| Diabetes mellitus | 20 | 38 | <0.001 |
VARA = Veterans Affairs Rheumatoid Arthritis registry; SD = standard deviation; MI = body mass index; RDCI = Rheumatic Disease Comorbidity Index; MI = myocardial infarction
Unadjusted associations of RA-related factors with baseline sUA concentration and gout status
There were no associations of baseline sUA status with simultaneously collected measures of RA disease activity or severity (Table 3). In regards to RA treatments used at the time of enrollment, there were no significant differences across sUA groups. The use of gout-related medications (colchicine or urate lowering therapies) was more frequent in RA patients with hyperuricemia, particularly in those with marked hyperuricemia, compared to those with normal sUA concentrations at enrollment. Compared to those without gout at enrollment, those with gout were slightly more likely to be using sulfasalazine (p=0.007) and less likely to be using a non-steroidal anti-inflammatory drug (NSAID) (p=0.011) (Table 3). Other measures of RA disease activity or severity and RA-related medication use did not differ significantly based on the presence of baseline gout. As expected the use of colchicine and urate lowering therapy any time during observation was substantially more frequent among RA patients with comorbid gout.
Table 3:
RA disease characteristics by serum urate and gout status at VARA enrollment*
| Baseline Serum Urate (sUA) | Baseline Gout Status | ||||||
|---|---|---|---|---|---|---|---|
| sUA ≤ 6.8 mg/dl | sUA > 6.8 to ≤ 8.0 mg/dl | sUA > 8.0 mg/dl | p-value | Non-gout | Gout | p-value | |
| Disease Activity / Severity | |||||||
| Dis. duration, years, mean (SD) | 12 (11) | 13 (12) | 12 (11) | 0.253 | 12 (11) | 11 (12) | 0.293 |
| Anti-CCP positive, % | 77 | 82 | 77 | 0.235 | 78 | 72 | 0.178 |
| Subcutaneous nodules, % | 29 | 36 | 35 | 0.063 | 30 | 24 | 0.235 |
| Radiographic changes, % | 54 | 55 | 54 | 0.957 | 54 | 51 | 0.515 |
| MD-HAQ, mean (SD) | 0.9 (0.6) | 0.8 (0.6) | 0.9 (0.6) | 0.134 | 0.9 (0.6) | 1.0 (0.6) | 0.099 |
| ESR, mm/hr, mean (SD) | 26 (23) | 25 (20) | 29 (25) | 0.254 | 26 (23) | 27 (23) | 0.758 |
| hsCRP, mg/dl, mean (SD) | 1.2 (2.0) | 1.2 (1.7) | 1.1 (1.6) | 0.384 | 1.2 (1.9) | 1.5 (2.5) | 0.055 |
| DAS28 category, % | 0.773 | 0.777 | |||||
| Remission (< 2.6) | 23 | 24 | 22 | 23 | 24 | ||
| Low (≥2.6 to ≤3.2) | 15 | 16 | 13 | 15 | 15 | ||
| Moderate (>3.2 to ≤5.1) | 39 | 41 | 45 | 40 | 43 | ||
| High (>5.1) | 23 | 19 | 21 | 22 | 17 | ||
| Treatments* | |||||||
| Methotrexate, % | 54 | 61 | 51 | 0.121 | 54 | 63 | 0.126 |
| Leflunomide, % | 12 | 10 | 6 | 0.072 | 12 | 7 | 0.191 |
| Sulfasalazine, % | 16 | 11 | 12 | 0.111 | 14 | 25 | 0.007 |
| Hydroxychloroquine, % | 35 | 39 | 36 | 0.630 | 36 | 30 | 0.291 |
| Prednisone, % | 42 | 46 | 42 | 0.549 | 42 | 49 | 0.208 |
| Biologic therapy, % | 29 | 30 | 37 | 0.172 | 29 | 24 | 0.313 |
| NSAID, % | 36 | 29 | 31 | 0.057 | 35 | 22 | 0.011 |
| Colchicine, % | 7 | 11 | 15 | 0.002 | 6 | 58 | <0.001 |
| Allopurinol, % | 7 | 10 | 22 | <0.001 | 5 | 85 | <0.001 |
| Febuxostat, % | 0.1 | 0.5 | 2.5 | 0.002 | 0.1 | 4.7 | <0.001 |
| Any urate lowering therapy, % | 7 | 10 | 23 | <0.001 | 5 | 85 | <0.001 |
Medications reflect baseline use with exception of gout-related medications (colchicine, allopurinol, febuxostat or other urate lowering medications) that reflect ever use during observation; VARA = Veterans Affairs Rheumatoid Arthritis registry; SD = standard deviation; CCP = cyclic citrullinated peptide; MD-HAQ = Multidimensional Health Assessment Questionnaire; ESR = erythrocyte sedimentation rate; hsCRP = high sensitivity C-reactive protein; DAS28 = 28-joint Disease Activity Score; NSAID = non-steroidal anti-inflammatory drug
Associations of baseline sUA with mortality
Over a total observation period of 11,471 person-years, there were 598 deaths resulting in a crude mortality rate of 5.21 deaths per 100 person-years. CVD accounted for 187 (31%) of these deaths resulting in a crude CVD mortality rate of 1.63 deaths per 100 person-years.
Unadjusted cumulative incidence curves of all-cause and CVD-related mortality, based on sUA category, are shown in Figure 1. Compared to those with normal sUA concentrations at enrollment, RA patients with moderate hyperuricemia (sUA >6.8 mg/dl to 8 mg/dl) demonstrated a significant increased risk of CVD-related mortality in an age-and sex-adjusted model (Model A: HR 1.56; 95% CI 1.11, 2.21) (Table 4). This association was slightly attenuated and no longer reached statistical significance in the intermediate (Model B: HR 1.45; 95% CI 0.95, 2.23) and fully adjusted model (Model C: HR 1.46; 95% CI 0.96, 2.22). Those with marked hyperuricemia (sUA >8 mg/d) demonstrated a CVD mortality risk that was similar to those with moderate hyperuricemia in an age-and sex-adjusted model (Model A: HR 1.69; 95% CI 0.82, 3.51), although this association did not achieve statistical significance (p=0.156). This trend towards significance was further attenuated and remained non-significant in the intermediate (Model B: HR 1.38; 95% CI 0.55, 3.49) and fully adjusted (Model C: HR 1.36; 95% CI 0.52, 3.54) models. There were no associations of baseline sUA with all-cause mortality regardless of the model examined (Table 4).
Figure 1. Serum Urate Concentration and Survival.
Cumulative Incidence curves demonstrating associations of baseline serum urate (sUA) category with all-cause mortality (upper panel) and cardiovascular mortality (lower panel); sUA categories defined as ≤6.8 mg/dl (normo-uricemic); >6.8 to 8.0 mg/dl (hyperuricemia); and >8.0 mg/dl (marked hyperuricemia).
Table 4:
Multivariable associations of baseline serum urate (sUA) category with all-cause and cardiovascular disease (CVD) related mortality*
| All-Cause | CVD | ||||
|---|---|---|---|---|---|
| HR (95% CI) | p-value | HR (95% CI) | p-value | ||
| Model A | sUA ≤ 6.8 mg/dl | Ref. | ---- | Ref. | ---- |
| sUA >6.8 to 8 mg/dl | 1.10 (0.89, 1.35) | 0.378 | 1.56 (1.11, 2.21) | 0.011 | |
| sUA >8 mg/dl | 1.26 (0.93, 1.69) | 0.131 | 1.69 (0.82, 3.51) | 0.156 | |
| Model B | sUA ≤ 6.8 mg/dl | Ref. | ---- | Ref. | ---- |
| sUA >6.8 to 8 mg/dl | 1.06 (0.90, 1.26) | 0.496 | 1.45 (0.95, 2.23) | 0.086 | |
| sUA >8 mg/dl | 1.15 (0.89, 1.49) | 0.282 | 1.38 (0.55, 3.49) | 0.494 | |
| Model C | sUA ≤ 6.8 mg/dl | Ref. | ---- | Ref. | ---- |
| sUA >6.8 to 8 mg/dl | 1.06 (0.89, 1.26) | 0.502 | 1.46 (0.96, 2.22) | 0.074 | |
| sUA >8 mg/dl | 1.15 (0.90, 1.47) | 0.263 | 1.36 (0.52, 3.54) | 0.526 | |
Model A covariates = age and sex; Model B covariates = age, sex, race, smoking status, body mass index, Rheumatic Disease Comorbidity Index, chronic kidney disease, 28-joint disease activity score category and prednisone use; Model C covariates include those in Model B + gout; significant associations shown in bold.
Associations of covariates included in the fully adjusted model (Model C) are shown in Table 5. As previously reported in this population (24, 25), factors associated with higher mortality risk included older age, male sex (all-cause), white race, smoking (all-cause), low BMI (all-cause), comorbidity burden, CKD, higher RA disease activity, and prednisone use. Although not associated with all-cause mortality (HR 1.03; 95% CI 0.72, 1.48), there was a non-significant trend towards an association between a gout diagnosis and CVD death (HR 1.67; 95% CI 0.85, 3.26). Associations of gout with survival were similar in magnitude and also non-significant in models adjusted only for age and sex (data not shown).
Table 5:
Associations of covariates with all-cause and cardiovascular mortality in full model (Model C)
| All-Cause | Cardiovascular | |||
|---|---|---|---|---|
| HR (95% CI) | P value | HR (95% CI) | P value | |
| Age | 1.08 (1.06, 1.09) | <0.001 | 1.05 (1.03, 1.08) | <0.001 |
| Male Sex | 1.56 (1.10, 2.22) | 0.013 | 1.23 (0.67, 2.24) | 0.507 |
| White | 1.38 (1.18, 1.60) | <0.001 | 1.66 (1.16, 2.36) | 0.005 |
| Tobacco use at enrollment | ||||
| Never | Ref. | Ref. | Ref. | Ref. |
| Former | 1.25 (1.08, 1.45) | 0.003 | 1.08 (0.55, 2.12) | 0.833 |
| Current | 2.12 (1.75, 2.57) | <0.001 | 1.42 (0.77, 2.62) | 0.258 |
| BMI, kg/m2 | ||||
| <20 | 1.86 (1.48, 2.34) | <0.001 | 1.59 (0.91, 2.77) | 0.103 |
| 20–25 | Ref. | Ref. | Ref. | Ref. |
| >25 to ≤ 30 | 0.84 (0.72, 0.99) | 0.037 | 0.73 (0.50, 1.07) | 0.109 |
| >30 to ≤35 | 0.67 (0.60, 0.74) | <0.001 | 0.85 (0.68, 1.06) | 0.156 |
| >35 | 0.85 (0.62, 1.16) | 0.307 | 0.92 (0.46, 1.85) | 0.815 |
| RDCI score | 1.24 (1.17, 1.32) | <0.001 | 1.19 (1.10, 1.28) | <0.001 |
| Chronic kidney disease | 1.71 (1.41, 2.08) | <0.001 | 2.17 (1.78, 2.65) | <0.001 |
| DAS28 | ||||
| Remission | Ref. | Ref. | Ref. | Ref. |
| Low | 1.33 (1.09, 1.64) | 0.006 | 1.31 (0.94, 1.82) | 0.111 |
| Moderate | 1.61 (1.39, 1.86) | <0.001 | 1.65 (1.21, 2.26) | 0.002 |
| High | 1.89 (1.46, 2.43) | <0.001 | 1.71 (1.15, 2.56) | 0.008 |
| Prednisone use | 1.21 (1.04, 1.41) | 0.016 | 1.25 (1.04, 1.50) | 0.019 |
| Gout | 1.03 (0.72, 1.48) | 0.876 | 1.67 (0.85, 3.26) | 0.136 |
BMI = body mass index; RDCI = Rheumatic Disease Comorbidity Index; DAS28 = 28-joint Disease Activity Score; significant associations shown in bold.
Discussion
Historically, the co-occurrence of gout and RA has been subject to limited investigation. Prior to 2014, only 55 cases of coexistent disease had been summarized in the literature (2, 26). The current study is, therefore, among the largest to date assessing concurrent gout and RA with the identification of 86 participants with prevalent gout at the time of registry enrollment and an additional 35 who developed incident gout during follow up. Furthermore, 17% of RA participants were found to have sUA concentrations >6.8 mg/dl. It is noteworthy that the frequency of hyperuricemia and gout in this study of predominantly male (90%) US veterans is similar to recent estimates from the US general population, where investigators recently observed a gout prevalence of 5.9% and a prevalence of hyperuricemia (sUA >7.0 mg/dl) of 20% among adult men (27). Likewise, the mean sUA concentration among men observed in our study (5.6 mg/dl) was similar to that observed in the general population of adult men (6.0 mg/dl). Taken together, these results counter the notion that RA or its treatment provides meaningful protection against the development of hyperuricemia leading to gout.
Previous reports have proposed that glucocorticoids and NSAIDs commonly used in RA could potentially mask the inflammatory manifestations of gout (2), offered as an explanation for earlier conclusions that gout was only rarely diagnosed in the context of established RA (1). In our study, compared to RA patients with gout, gout-free participants were significantly more likely to be using NSAIDs at enrollment. Avoidance of these medications in gout patients may relate to a higher prevalence of CKD. It is also possible that NSAID use could have masked clinical symptoms (and prevented the diagnosis) of gout in a limited number of hyperuricemic RA patients. It has also been proposed that select pro-inflammatory cytokines in RA might exert uricosuric effects and therefore reduce the likelihood of developing overt gout (28). Counter to our study hypothesis, we observed no differences in the use of therapies that might impact cytokine concentrations (e.g. methotrexate, prednisone or biologic therapies) based on sUA or gout status at the time of enrollment into this RA registry.
Likewise, we found no associations of hyperuricemia or gout with measures of RA disease activity or severity. Although both uric acid and monosodium urate crystals have been shown to act as potent immuno-stimulants (4–6), it is possible that the nearly universal use of DMARDs and/or other potent anti-inflammatory treatments in RA obfuscated this association. Consistent with observations from other populations, RA patients with hyperuricemia at the time of registry enrollment demonstrated a significantly greater comorbidity burden than normouricemic RA patients, particularly in terms of hypertension and CKD. It is important to note that compared to reports from other gout populations (29), the prevalence of CKD among gout sufferers or those with marked hyperuricemia (15–16%) were lower in this study. These lower estimates likely reflect the use of diagnostic codes for CKD classification, an approach that although highly specific, suffers from limited sensitivity (30). Recognizing this limitation, our observation is in line with the previously reported finding that sUA concentration acts as a predictor of renal dysfunction in the context of RA (13) in addition to being a marker of other comorbid conditions.
The relevance of sUA concentration acting as a biomarker of comorbidity burden was further borne out in survival analyses. Compared to normouricemic registrants, RA patients with hyperuricemia were 60 to 70% more likely to suffer from cardiovascular mortality after accounting for differences in age and sex. This risk reached statistical significance only in those with moderate hyperuricemia (sUA >6.8 to 8 mg/dl), and not in those with marked hyperuricemia, likely owing to smaller numbers. The risk of CVD mortality attributable to moderate and marked hyperuricemia were attenuated and no longer significant after accounting for comorbidity burden (reflected in RCDI score), with CKD and BMI acting as the strongest confounders of these relationships. Although limited in power with just 121 cases identified, we observed non-significant trends suggesting an increased risk of CVD mortality attributable to gout even after accounting for baseline sUA concentration and other confounders, consistent with results from the Multiple Risk Factor Intervention Trial that demonstrated associations between gout and the risk of acute MI independent of hyperuricemia (31).
Different hypotheses have been suggested to explain potential links between sUA concentration, gout, and CVD risk. These have included the presence of shared risk factors, the impact of systemic inflammation on endothelial dysfunction and accelerated atherosclerosis, and/or the direct interaction of uric acid with diverse metabolic pathways implicated in CVD (32, 33). While residual confounding is always a concern in understanding causal relationships in observational studies, results from this study underscore the possible value of identifying hyperuricemia in the context of RA given its striking associations with comorbid conditions such as hypertension and renal impairment that, in turn, act as potentially modifiable predictors of CVD-related survival.
Our study has several strengths, including the unique and well-characterized RA study population available, links of this registry with national VA and vital status data, and the availability of biobanked serum samples that allowed for standardized sUA measurement. “Enriched” with patients characterized by gout risk (e.g. older men with comorbid diseases), the VA population is perhaps uniquely suited to address the study hypotheses posed. However, we recognize that these results may not be readily generalizable to other RA patient populations. Despite having access to a large “at risk” population, statistical power was limited for select analyses including those focused on RA patients with marked hyperuricemia or mortality risk specific to gout. Although the registry leveraged in this report includes longitudinal follow-up, most (71%) of the patients with gout were diagnosed prior to RA registry enrollment, which precluded efforts to identify risk factors for the development of new-onset gout. Recognizing that all of the study participants satisfied validated classification criteria for RA and were under regular rheumatology care, we used a relatively stringent definition of gout to minimize possible misclassification. More than one-third of gout patients identified in this study underwent diagnostic aspirations (considered the gold standard for diagnosis). Of these crystal confirmed cases, seropositivity for anti-CCP antibody (63%) was only slightly lower than that of the overall study population with gout (72%), suggesting that misclassification was likely infrequent.
With serum samples available only from the time of registry enrollment, analyses of sUA concentrations were limited to a single point in time. Larger studies that incorporate longitudinal sUA measurements in RA patients could prove to be informative in the future. Such studies would provide much needed insight into whether changes in sUA over time, including those related to urate lowering therapy, might influence RA disease activity, benefit survival or prevent the development of relevant comorbid conditions that frequently afflict patients.
In conclusion, our observations confirm that hyperuricemia and gout coexist with RA in a select number of patients. Moreover, our findings demonstrate strong associations of hyperuricemia with CVD mortality in this population, a risk that appears to be driven primarily by excess comorbidity.
Significance and Innovations.
One of the largest studies to date examining coexistent rheumatoid arthritis (RA) and gout (n=121 coexistent cases).
The frequency of gout (6.1%) and hyperuricemia (17%) in this population approach prevalence rates in the general population.
Hyperuricemia or gout are associated with a higher comorbidity burden in patients with RA.
Moderate hyperuricemia is associated with increased cardiovascular mortality, a risk that is attributable to increased comorbidity.
Acknowledgements:
Vital status data for this work was obtained from the Center of Excellence for Suicide Prevention, Joint Department of Veterans Affairs (VA) and Department of Defense (DoD) Suicide Data Repository – National Death Index (NDI).
Funding: Support for this work was provided by the University of Nebraska, College of Medicine Enhanced Medical Education Track (AC), Veterans Affairs (VA CSR&D Merit Award (TRM; CX000896), Rheumatology Research Foundation Scientist Development Award (TRM, BRE), the National Institutes of Health / National Institute of General Medical Sciences (TRM and BRE; U54GM115458), and Specialty Care Center of Innovation, Veterans Health Administration and Department of Veterans Affairs, Health Services Research and Development (GWC).
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