Determinants of Achieving Serum Urate Goal with Treat-to-Target Urate-Lowering Therapy in Gout.

OBJECTIVE: Using trial data comparing treat-to-target allopurinol and febuxostat in gout, we examined participant characteristics associated with serum urate (SU) goal achievement. METHODS: Participants with gout and SU ≥6.8 mg/dL were randomized to allopurinol or febuxostat, titrated during weeks 0 to 24, and maintained weeks 25 to 48. Participants were considered to achieve SU goal if the mean SU from weeks 36, 42, and 48 was <6.0 mg/dL or <5 mg/dL if tophi were present. Possible determinants of treatment response were preselected and included sociodemographics, comorbidities, diuretic use, health-related quality of life (HRQoL), body mass index, and gout measures. Determinants of SU response were assessed using multivariable logistic regression with additional analyses to account for treatment adherence. RESULTS: Of 764 study participants completing week 48, 618 (81%) achieved SU goal. After multivariable adjustment, factors associated with a greater likelihood of SU goal achievement included older age (adjusted odds ratio [aOR] 1.40 per 10 years), higher education (aOR 2.02), and better HRQoL (aOR 1.17 per 0.1 unit). Factors associated with a lower odds of SU goal achievement included non-White race (aORs 0.32-0.47), higher baseline SU (aOR 0.83 per 1 mg/dL), presence of tophi (aOR 0.29), and the use of diuretics (aOR 0.52). Comorbidities including chronic kidney disease, hypertension, diabetes, and cardiovascular disease were not associated with SU goal achievement. Results were not meaningfully changed in analyses accounting for adherence. CONCLUSIONS: Several patient-level factors were predictive of SU goal achievement among patients with gout who received treat-to-target urate-lowering therapy (ULT). Approaches that accurately predict individual responses to treat-to-target ULT hold promise in facilitating personalized management and improving outcomes in patients with gout.

Health disparities in gout.

PURPOSE OF REVIEW: Gout, the most common type of inflammatory arthritis in the world, is characterized by painful episodes of arthritis linked by asymptomatic intercritical periods of hyperuricemia. Once characterized as a disease of wealthy white men, contemporary evidence demonstrates gout disproportionately afflicts racial/ethnic minorities, Indigenous populations and other underrepresented groups leading to significant health disparities. RECENT FINDINGS: Herein, we review the current literature reporting a higher incidence and prevalence of gout in racial/ethnic minorities and Indigenous populations, in addition to a growing gout burden reported in females. We also examine how these population are more likely to receive suboptimal treatment for flares and chronic phases of gout. Additionally, we examine biologic and social health determinants that may be contributing to these findings. SUMMARY: Racial/ethnic minorities, Indigenous populations, and females have experienced a disproportionate rise in the prevalence and incidence of gout in recent years, are more likely to seek acute medical care and are less likely to receive optimal long-term care for gout with urate lowering therapy. Mechanisms underpinning these findings appear to be multifactorial and include differences in social determinants of care and in some cases may be due to population differences in select biologic factors such as differences in age, sex, genetics.

Cause-Specific Mortality in Patients With Gout in the US Veterans Health Administration: A Matched Cohort Study.

OBJECTIVE: To compare all-cause and cause-specific mortality risk between patients with gout and patients without gout in the Veteran's Health Administration (VHA). METHODS: We performed a matched cohort study, identifying patients with gout in the VHA from January 1999 to September 2015 based on the presence of ≥2 International Classification of Diseases, Ninth Revision codes for gout (274.X). Gout patients were matched up to 1:10 on birth year, sex, and year of VHA enrollment with patients without gout and followed until death or end of study (December 2017). Cause of death was obtained from the National Death Index. Associations of gout with all-cause and cause-specific mortality were examined using multivariable Cox regression. RESULTS: Gout (n = 559,243) and matched non-gout controls (n = 5,428,760) had a mean age of 67 years and were 99% male. There were 246,291 deaths over 4,250,371 patient-years in gout patients and 2,000,000 deaths over 40,441,353 patient-years of follow-up in controls. After matching, gout patients had an increased risk of death (hazard ratio [HR] 1.09 [95% confidence interval (95% CI) 1.08-1.09]), which was no longer present after adjusting for comorbidities (HR 0.98 [95% CI 0.97-0.98]). The strongest association of gout with cause-specific mortality was observed with genitourinary conditions (HR 1.50 [95% CI 1.47-1.54]). Gout patients were at lower risk of death related to neurologic (e.g., Alzheimer's disease and Parkinson's disease) (HR 0.63 [95% CI 0.62-0.65]) and mental health (HR 0.66 [95% CI 0.65-0.68]) conditions. CONCLUSION: A higher risk of death among gout patients in the VHA was related to comorbidity burden. While deaths attributable to neurologic and mental health conditions were less frequent among gout patients, genitourinary conditions were the most overrepresented causes of death.

Associations Between Low Serum Urate, Body Composition, and Mortality.

OBJECTIVE: Controversy remains as to whether low serum urate or uric acid (UA) levels contribute to adverse outcomes. We evaluated the relation between low serum UA levels and sarcopenia and assessed whether sarcopenia confounds associations between these low levels and mortality. METHODS: We utilized data from the National Health and Nutrition Examination Survey (1999-2006). Participants with available whole-body dual x-ray absorptiometry body composition measurements and serum UA concentrations were included. Body composition assessments included body mass index (BMI), waist circumference, maximum lifetime BMI, and age-, sex-, and race-specific appendicular lean mass index (ALMI) and fat mass index (FMI) Z scores. We also calculated Z scores for ALMI relative to FMI (ALMIFMI ). We evaluated associations between serum UA levels and body composition using logistic regression and assessed associations between serum UA levels and mortality before and after adjusting for differences in body composition using Cox proportional hazards regression. RESULTS: Among the 13,979 participants, low serum UA concentrations (<2.5 mg/dl in women, <3.5 mg/dl in men) were associated with low lean mass (ALMI and ALMIFMI Z scores), underweight BMI (<18.5 kg/m2 ), and higher rates of weight loss. The proportion of patients with low ALMI Z scores was 29% in the low serum UA group and 16% in the normal serum UA group (P = 0.001). Low serum UA levels were associated with increased mortality before we adjusted for body composition (hazard ratio 1.61 [95% confidence interval 1.14-2.28]; P = 0.008) but was attenuated and not significant after adjustment for body composition and weight loss (hazard ratio 1.30 [95% confidence interval 0.92-1.85], P = 0.13). CONCLUSION: Sarcopenia and weight loss are more common among patients with low serum UA concentrations. Differences in body composition may help to explain associations between low levels of serum UA and higher mortality.

Environmental Triggers of Hyperuricemia and Gout.

Gout is the most prevalent type of inflammatory arthritis worldwide and environmental factors contribute to hyperuricemia and risk for gout flare. Causes of hyperuricemia include increased purine consumption from meat, alcohol, and high fructose corn syrup as well as medications such as cyclosporine, low-dose aspirin, or diuretics. Triggers for gout flares include increased purine consumption and medication use such as urate lowering therapy and diuretics. Environmental exposures including lead exposure, particulate matter exposure, temperature fluctuations, and physiologic stress have been found to trigger flares. In the right clinical scenario, these factors should be considered when treating gout patients.

Comparative Effectiveness of Allopurinol and Febuxostat in Gout Management.

BACKGROUND: The relative efficacy and safety of allopurinol and febuxostat when used according to current guidelines for the treatment of hyperuricemia are unknown. This double-blind noninferiority trial examined these issues. METHODS: Participants with gout and hyperuricemia (with at least 33% having stage 3 chronic kidney disease) were randomly assigned to allopurinol or febuxostat in this 72-week trial, with doses titrated to target serum urate. The trial had three phases: titration (weeks 0 to 24), maintenance (weeks 25 to 48), and observation (weeks 49 to 72). Allopurinol and febuxostat were initiated at daily doses of 100 and 40 mg, with maximum titration to 800 and 120 mg, respectively. Antiinflammatory prophylaxis was given during phases 1 and 2. The primary end point was the proportion of patients experiencing one or more flares during phase 3, with a prespecified noninferiority margin of less than 8 percentage points between allopurinol and febuxostat. Secondary end points included efficacy in patients with chronic kidney disease, proportion achieving target serum urate levels, and serious adverse events. RESULTS: This study included 940 participants; 20.1% withdrew, with similar proportions in treatment arms. During phase 3, 36.5% of allopurinol-treated participants had one flare or more compared with 43.5% of febuxostat-treated participants (P<0.001 for noninferiority). Overall, 80% of participants achieved mean target urates during phase 2 with no differences by treatment. There were no treatment differences (including cardiovascular events) in serious adverse events. CONCLUSIONS: Allopurinol and febuxostat achieved serum urate goals in patients with gout; allopurinol was noninferior to febuxostat in controlling flares. Similar outcomes were noted in participants with stage 3 chronic kidney disease. (Funded by the Cooperative Studies Program of the Department of Veterans Affairs Office of Research and Development; ClinicalTrials.gov identifier, NCT02579096.).

Comparison of Rates of Lower Extremity Amputation in Patients With and Without Gout in the US Department of Veterans Affairs Health System.

Importance: Cardiometabolic and other risk factors could render patients with gout more likely to undergo lower extremity amputation (LEA). Objective: To examine the rate of and factors associated with LEA in patients with gout. Design, Setting, and Participants: In this matched cohort study using national administrative data, multivariable Cox proportional hazards regression models were used to examine the associations of gout with LEA. In analyses limited to patients with gout, attributes of serum urate control and treatment with urate-lowering therapy were examined as factors associated with LEA. This study included patients who used US Department of Veterans Affairs services from January 1, 2000, to July 31, 2015. Patients with gout were identified using diagnostic codes and matched with up to 10 controls by age, sex, and year of benefit enrollment. Data analysis was performed from January 26, 2021, to September 3, 2021. Exposures: Gout classification served as the primary independent variable of interest. In analyses limited to patients with gout, factors associated with serum urate control and urate-lowering therapy were examined. Main Outcomes and Measures: Overall LEA, as well as toe, transmetatarsal, below-the-knee, and above-the-knee amputation. Results: This cohort study included 5 924 918 patients, 556 521 with gout (mean [SD] age, 67 [12] years; 550 963 (99.0%) male; 88 853 [16.0%] Black non-Hispanic; 16 981 [4.3%] Hispanic/Latinx; 345 818 [62.1%] White non-Hispanic; 80 929 [14.5%] with race and ethnicity data missing; and 23 940 [4.3%] classified as other) and 5 368 397 without gout (mean [SD] age, 67 [12] years; 5 314 344 [99.0%] male; 558 464 [10.4%] Black non-Hispanic; 204 291 [3.0%] Hispanic/Latinx; 3 188 504 [59.4%] White non-Hispanic; 1 257 739 [23.4%)] with race and ethnicity data missing; and 159 399 [3.0%] classified as other). Compared with patients without gout, patients with gout were more likely to undergo amputation, an increased rate that remained after adjustment (adjusted hazard ratio, 1.20; 95% CI, 1.16-1.24) and was highest for below-the-knee amputation (adjusted hazard ratio, 1.59; 95% CI, 1.39-1.81). In those with gout, poor serum urate control (mean >7 mg/dL during the preceding year) was associated with a 25% to 37% increase in the rate of amputation. In contrast, treatment with urate-lowering therapy was not associated with the LEA rate. Conclusions and Relevance: In this matched cohort study, patients with gout were more likely to undergo LEA. This increase was independent of other comorbidities that have been associated with amputation, including diabetes and peripheral vascular disease. Serum urate control was independently associated with the LEA rate, suggesting the possibility that lower extremity amputation may be preventable in some patients.

Development of a lupus nephritis suboptimal response prediction tool using renal histopathological and clinical laboratory variables at the time of diagnosis.

OBJECTIVE: Lupus nephritis (LN) is an immune complex-mediated glomerular and tubulointerstitial disease in patients with SLE. Prediction of outcomes at the onset of LN diagnosis can guide decisions regarding intensity of monitoring and therapy for treatment success. Currently, no machine learning model of outcomes exists. Several outcomes modelling works have used univariate or linear modelling but were limited by the disease heterogeneity. We hypothesised that a combination of renal pathology results and routine clinical laboratory data could be used to develop and to cross-validate a clinically meaningful machine learning early decision support tool that predicts LN outcomes at approximately 1 year. METHODS: To address this hypothesis, patients with LN from a prospective longitudinal registry at the Medical University of South Carolina enrolled between 2003 and 2017 were identified if they had renal biopsies with International Society of Nephrology/Renal Pathology Society pathological classification. Clinical laboratory values at the time of diagnosis and outcome variables at approximately 1 year were recorded. Machine learning models were developed and cross-validated to predict suboptimal response. RESULTS: Five machine learning models predicted suboptimal response status in 10 times cross-validation with receiver operating characteristics area under the curve values >0.78. The most predictive variables were interstitial inflammation, interstitial fibrosis, activity score and chronicity score from renal pathology and urine protein-to-creatinine ratio, white blood cell count and haemoglobin from the clinical laboratories. A web-based tool was created for clinicians to enter these baseline clinical laboratory and histopathology variables to produce a probability score of suboptimal response. CONCLUSION: Given the heterogeneity of disease presentation in LN, it is important that risk prediction models incorporate several data elements. This report provides for the first time a clinical proof-of-concept tool that uses the five most predictive models and simplifies understanding of them through a web-based application.

Incidence, Prevalence, and Burden of Gout in the Veterans Health Administration.

OBJECTIVE: To determine the prevalence, incidence, and burden of gout in the Veterans Health Administration (VHA) from 2005 to 2014. METHODS: We used national VHA data from January 1999 to December 2014 to determine the annual incidence and prevalence of gout in the VHA. Gout burden to the VHA was determined by the proportion of patients with an encounter related to gout. Rates of urate-lowering therapy (ULT) and opiate use were determined annually. Characteristics of those with and without gout were compared using 2014 data. RESULTS: From 2005 to 2014, gout prevalence in the VHA increased from 4.2% to 5.8%, while disease incidence ranged from 5.8 to 7.4 cases per 1,000 patient-years. Gout prevalence was highest among men, older patients, and non-Hispanic black patients. During 2014, 4.0% of all inpatient or outpatient encounters and 1.3% of hospitalizations were gout related. Administration of ULT remained stable over the 10-year period, with 46% of gout patients receiving ULT in 2014. In contrast, 16.4% of prevalent gout patients were receiving a weak opioid in 2014, nearly doubling the prescription rate of weak opioids in 2005, while the use of stronger opioids did not change significantly over this period. Patients with gout had greater comorbidity and health care utilization than patients without gout. CONCLUSION: The burden posed by gout in the VHA is considerable and increased between 2005 and 2014. While the use of ULT has remained stable, the use of opioid therapy has increased among patients with gout.

Evaluation of the bacterial burden of gel nails, standard nail polish, and natural nails on the hands of health care workers.

BACKGROUND: Acrylic nails harbor more bacteria than natural nails, and wear is not recommended for health care workers (HCWs). Little is known about the new and popular gel nail products. This study sought to evaluate the bacterial burden of gel nails, standard nail polish, and natural nails on the hands of HCWs. METHODS: The study was conducted at 3 health centers. Nails on the dominant hand of 88 HCWs were painted with gel polish and standard polish. Cultures were obtained on days 1, 7, and 14 of wear and before and after hand hygiene with alcohol hand gel. RESULTS: A total of 741 cultures were obtained. Bacterial burden increased over time for all nail types (P ≤ .0001). Reductions in the bacterial burden of natural nails and standard polish, but not gel polish, (P = .001, P = .0028, and P = .98, respectively) were seen after hand hygiene. All 3 nail types become more contaminated with bacteria over time. Standard polish and natural nails may be more amenable to hand hygiene than gel polish. CONCLUSIONS: This study did not show an increased number of microorganisms on nails with gel polish; however, gel nails may be more difficult to clean using alcohol hand gel.