Association of C-reactive protein with all-cause and cause-specific mortality in people with gout.

AIMS: To test the association of C-reactive protein (CRP) with all-cause and cause-specific mortality in people with gout. METHODS: This cohort study included 502 participants with gout from the National Health and Nutrition Examination Survey. Multivariate Cox regression analysis, subgroup analysis, and restricted cubic spline (RCS) analyses were utilized to examine the association of CRP levels with all-cause, cardiovascular, and cancer mortality. RESULTS: After adjusting for multiple variables, Cox regression analysis showed that compared with individuals in the lowest tertile of CRP levels, those in the middle and highest tertiles experienced increases in all-cause mortality risk of 74.2% and 149.7%, respectively. Similarly, the cancer mortality risk for individuals in the highest tertile of CRP levels increased by 283.9%. In addition, for each standard deviation increase in CRP, the risks of all-cause and cancer mortality increased by 25.9% and 35.4%, respectively (P < 0.05). Subgroup analyses demonstrated that the association between CRP levels and all-cause mortality remained significant across subgroups of age (≤ 60 and > 60 years), gender (male), presence or absence of hypertension, non-diabetes, cardiovascular disease, non-cardiovascular disease and non-cancer. Furthermore, the association with cancer mortality was significant in subgroups including males, those without hypertension and cancer, and those with or without diabetes. However, the association with cardiovascular mortality was only significant in the non-hypertension subgroup (P < 0.05). Nonlinear association of CRP with all-cause mortality and linear association with cancer mortality were also confirmed (P for nonlinearity = 0.008 and 0.135, respectively). CONCLUSIONS: CRP levels were associated with increased all-cause and cancer mortality among individuals with gout.

Association between low-density lipoprotein cholesterol levels and serum uric acid to serum creatinine ratio in Chinese male gout patients.

This study aimed to evaluate the association between low-density lipoprotein cholesterol (LDL-C) and serum uric acid to serum creatinine (SUA/SCr) ratio in male gout patients at different BMIs. This real-world study included 956 male gout patients aged 18-83 years. We retrospectively analyzed the medical records of Chinese male gout patients from 2017 to 2019. The correlation between LDL-C and SUA/SCr was tested after adjusting for confounding factors. We found a nonlinear relationship between LDL-C and SUA/SCr in the whole study population. Stratification analysis showed that there was actually a nonlinear relationship between LDL-C and SUA/SCr in men with a BMI of 24-28, the inflection point of LDL-C was 1.8 mmol/L, when LDL-C was greater than 1.8 mmol/L, there was a positive correlation between LDL-C levels and SUA/SCr (ß = 0.67, 95% CI 0.35-0.98, P < 0.001). Moreover, LDL-C showed a significant positive correlation with SUA/SCr with a BMI of 28 or greater (ß = 0.30, 95% CI 0.05-0.55, P = 0.019). However, no association was found between LDL-C and SUA/SCr with a BMI of less than 24 (ß = 0.42, 95% CI - 0.03-0.86, P = 0.070). LDL-C levels were associated with SUA/SCr in Chinese male gout patients, but this correlation appeared inconsistent among different BMIs. Our findings suggest that LDL-C levels may be more noteworthy in overweight and/or obese male gout patients.

Creating machine learning models that interpretably link systemic inflammatory index, sex steroid hormones, and dietary antioxidants to identify gout using the SHAP (SHapley Additive exPlanations) method.

Background: The relationship between systemic inflammatory index (SII), sex steroid hormones, dietary antioxidants (DA), and gout has not been determined. We aim to develop a reliable and interpretable machine learning (ML) model that links SII, sex steroid hormones, and DA to gout identification. Methods: The dataset we used to study the relationship between SII, sex steroid hormones, DA, and gout was from the National Health and Nutrition Examination Survey (NHANES). Six ML models were developed to identify gout by SII, sex steroid hormones, and DA. The seven performance discriminative features of each model were summarized, and the eXtreme Gradient Boosting (XGBoost) model with the best overall performance was selected to identify gout. We used the SHapley Additive exPlanation (SHAP) method to explain the XGBoost model and its decision-making process. Results: An initial survey of 20,146 participants resulted in 8,550 being included in the study. Selecting the best performing XGBoost model associated with SII, sex steroid hormones, and DA to identify gout (male: AUC: 0.795, 95% CI: 0.746- 0.843, accuracy: 98.7%; female: AUC: 0.822, 95% CI: 0.754- 0.883, accuracy: 99.2%). In the male group, The SHAP values showed that the lower feature values of lutein + zeaxanthin (LZ), vitamin C (VitC), lycopene, zinc, total testosterone (TT), vitamin E (VitE), and vitamin A (VitA), the greater the positive effect on the model output. In the female group, SHAP values showed that lower feature values of E2, zinc, lycopene, LZ, TT, and selenium had a greater positive effect on model output. Conclusion: The interpretable XGBoost model demonstrated accuracy, efficiency, and robustness in identifying associations between SII, sex steroid hormones, DA, and gout in participants. Decreased TT in males and decreased E2 in females may be associated with gout, and increased DA intake and decreased SII may reduce the potential risk of gout.

Comparison of the therapeutic effects of febuxostat combined with a low-purine diet and allopurinol combined with a low-purine diet on the improvement of gout patients.

OBJECTIVE: To compare the clinical efficacy of febuxostat combined with a low-purine diet versus allopurinol combined with a low-purine diet in the treatment of gout. METHODS: In this prospective controlled trial, 98 gout patients admitted to our hospital from February 2021 to December 2022 were enrolled as study subjects. Patients were randomly assigned to the study group (febuxostat combined with a low-purine diet) and the control group (allopurinol combined with a low-purine diet), with 49 patients in each group. The therapeutic effect was evaluated based on joint function and serum uric acid levels after treatment, and classified into three levels: markedly effective, effective, and ineffective. The levels of inflammatory factors, including tumor necrosis factor-a (TNF-a), cytokine interleukin-1beta (IL-1ß), and interleukin (IL)-18 (IL-18), were collected. The Numeric Rating Scale (NRS) was used to assess the degree of pain in patients. Clinical indicators before and 6 months after treatment were compared between the two groups. RESULTS: There was no statistically significant difference in age and gender between the two groups. After 6 months of treatment, the effective rate in the study group (48 cases, 97.96%) was higher than that in the control group (42 cases, 85.71%), with a statistically significant difference (p = .027). At the same time, the study group had significantly lower levels of serum uric acid (162.39 µmol/L ± 17.23 µmol/L vs. S198.32 µmol/L ± 18.34 µmol/L, p < .001), creatinine (87.39 mmol/L ± 9.76 mmol/L vs. 92.18 mmol/L ± 9.27 mmol/L, p = .014), total cholesterol (3.65 mmol/L ± 0.65 mmol/L vs. 4.76 mmol/L ± 0.73 mmol/L, p < .001), and triglycerides (1.76 mmol/L ± 0.32 mmol/L vs. 2.28 mmol/L ± 0.41 mmol/L, p < .001) compared to the control group, with statistically significant differences (p < .05). After treatment, the levels of inflammatory factors and degree of pain in the study group were significantly lower than those in the control group (all p < .05). During the treatment process, the incidence of adverse reactions in the study group (2 cases, 4.08%) was lower than that in the control group (9 cases, 18.37%), with a statistically significant difference (p = .025). CONCLUSION: Febuxostat combined with a low-purine diet can reduce inflammatory factors and alleviate the degree of pain in gout patients, significantly improving their clinical symptoms.

Serum urate change among gout patients treated with sodium-glucose cotransporter type 2 inhibitors vs. sulfonylurea: A comparative effectiveness analysis.

OBJECTIVE: To investigate the serum urate (SU) change among gout patients initiating SGLT2i, and to compare with sulfonylurea, the second-most widely used glucose-lowering medication after metformin. METHODS: We conducted a cohort study of patients with gout and baseline SU >6 mg/dL who had SU measured within 90 days before and after SGLT2i or sulfonylurea initiation. Using multivariable linear regression, we compared SU change among SGLT2i initiators between those with and without diabetes and then compared SU change between SGLT2i and sulfonylurea. RESULTS: We identified 28 patients with gout initiating SGLT2i (including 16 with diabetes) and 28 patients initiating sulfonylurea (all with diabetes). Among SGLT2i initiators, the mean within-group SU change was -1.8 (95 % CI, -2.4 to -1.1) mg/dL, including -1.2 (-1.8 to -0.6) mg/dL and -2.5 (-3.6 to -1.3) mg/dL among patients with and without diabetes, respectively, with an adjusted difference between those with and without diabetes of -1.4 (-2.4 to -0.5) mg/dL. The SU did not change after initiating sulfonylurea (+0.3 [-0.3 to 1.0] mg/dL). The adjusted SU change difference between SGLT2i vs. sulfonylurea initiation was -1.8 (-2.7 to -0.9) mg/dL in all patients. The SU reduction persisted regardless of urate-lowering therapy or diuretic use and the presence of diabetes, chronic kidney disease, or heart failure. CONCLUSION: Among patients with gout, SGLT2i was associated with a notable reduction in SU compared with sulfonylurea, with a larger reduction among patients without diabetes. With their proven cardiovascular-kidney-metabolic benefits, adding SGLT2i to current gout management could provide streamlined benefits for gout and its comorbidities.

Large-scale cross-ancestry genome-wide meta-analysis of serum urate.

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.

What Is Allopurinol Failure and What Should We Do About It?

Allopurinol is the most widely used urate-lowering medication worldwide. However, allopurinol failure is frequently observed in clinical practice. In this review, we provide a framework for assessing allopurinol failure, which includes failure of allopurinol to control serum urate concentrations, failure of allopurinol to control clinical symptoms, and failure of allopurinol due to an adverse drug reaction. Understanding the causes of allopurinol failure underpins the approach required to turn failure into success in gout management.

Comparative Risk of Gout Flares When Initiating or Escalating Various Urate-Lowering Therapy: A Systematic Review With Network Meta-Analysis.

OBJECTIVE: We systematically examined comparative gout flare risk after initiation or escalation of different urate-lowering therapies (ULTs), comparative flare risk with and without concomitant flare prophylaxis, adverse event rates associated with flare prophylaxis, and optimal duration of flare prophylaxis. METHODS: We searched the Medline, Embase, Web of Science, and Cochrane databases and clinical trial registries from inception to November 2021 for trials investigating adults with gout initiating or escalating ULT. We performed random effects network meta-analyses and calculated risk ratios (RRs) between treatments. Bias was assessed using the revised Cochrane risk-of-bias tool. RESULTS: We identified 3,775 records, of which 29 publications (27 trials) were included. When compared to placebo plus prophylaxis, the RR of flares ranged from 1.08 (95% confidence interval [CI] 0.87-1.33) for febuxostat 40 mg plus prophylaxis to RR 2.65 [95% CI 1.58-4.45] for febuxostat 80 mg plus lesinurad 400 mg plus prophylaxis. Compared to ULT alone, the RR of flares was lower for ULT plus rilonacept 160 mg (RR 0.35 [95% CI 0.25-0.50]), ULT plus rilonacept 80 mg (RR 0.43 [95% CI 0.31-0.60]) and ULT plus colchicine (RR 0.50 [95% CI 0.35-0.72]). There was limited evidence for other flare prophylaxis and on prophylaxis harms and optimal duration. Primarily because of missing outcome data and bias in the selection of reported results, 71.4% and 63.4% of studies were assessed as high risk of bias for flares and adverse events, respectively. CONCLUSION: The RR of flares when introducing ULT varies depending on ULT drug and dosing strategies. There were limited data on ULT escalation. Flare prophylaxis with colchicine and rilonacept reduces flare incidence. More research is required on the harms and optimal duration of prophylaxis.

Serum Urate and Recurrent Gout.

Importance: Approximately 12 million adults in the US have a history of gout, but whether serum urate levels can help predict recurrence is unclear. Objective: To assess associations of a single serum urate measurement with subsequent risk of acute gout flares and subsequent risk of hospitalizations for gout among patients in the UK with a history of gout. Design, Setting, and Participants: This retrospective study included patients with a history of gout identified from the UK between 2006 and 2010 who were followed up through Primary Care Linked Data medical record linkage until 2017 and through the Hospital Episode Statistics database until 2020. Exposures: Serum urate levels at enrollment. Main Outcome and Measure: Rate of recurrent acute gout, ascertained by hospitalization, outpatient, and prescription/procedure records, and adjusted rate ratios using negative binomial regressions. Results: Among 3613 patients with gout (mean age, 60 years; 3104 [86%] men), 1773 gout flares occurred over a mean follow-up of 8.3 years. Of these, 1679 acute gout flares (95%) occurred in people with baseline serum urate greater than or equal to 6 mg/dL and 1731 (98%) occurred in people with baseline serum urate greater than or equal to 5 mg/dL. Rates of acute gout flares per 1000 person-years were 10.6 for participants with baseline urate levels less than 6 mg/dL, 40.1 for levels of 6.0 to 6.9 mg/dL, 82.0 for levels of 7.0 to 7.9 mg/dL, 101.3 for levels of 8.0 to 8.9 mg/dL, 125.3 for urate levels of 9.0 to 9.9 mg/dL, and 132.8 for levels greater than or equal to 10 mg/dL. Rate ratio of flares were 1.0, 3.37, 6.93, 8.67, 10.81, and 11.42, respectively, over 10 years (1.61 [1.54-1.68] per mg/dL). Rates of hospitalization per 1000 person-years during follow-up were 0.18 for those with baseline serum urate less than 6 mg/dL, 0.97 for serum urate of 6.0 to 6.9 mg/dL, 1.8 for serum urate of 7.0 to 7.9 mg/dL, 2.2 for serum urate of 8.0 to 8.9 mg/dL, 6.7 for serum urate of 9.0 to 9.9 mg/dL, and 9.7 for serum urate greater than or equal to 10 mg/dL. Rate ratios of hospitalization for gout, adjusting for age, sex, and race were 1.0, 4.70, 8.94, 10.37, 33.92, and 45.29, respectively (1.87 [1.57-2.23] per mg/dL). Conclusions and Relevance: In this retrospective study of patients with a history of gout, serum urate levels at baseline were associated with the risk of subsequent gout flares and rates of hospitalization for recurrent gout. These findings support using a baseline serum urate level to assess risk of recurrent gout over nearly 10 years of follow-up.

The development and evaluation of dose-prediction tools for allopurinol therapy (Easy-Allo tools).

AIMS: Dose escalation at the initiation of allopurinol therapy can be protracted and resource intensive. Tools to predict the allopurinol doses required to achieve target serum urate concentrations would facilitate the implementation of more efficient dose-escalation strategies. The aim of this research was to develop and externally evaluate allopurinol dosing tools, one for use when the pre-urate-lowering therapy serum urate is known (Easy-Allo1) and one for when it is not known (Easy-Allo2). METHODS: A revised population pharmacokinetic-pharmacodynamic model was developed using data from 653 people with gout. Maintenance doses to achieve the serum urate target of <0.36 mmol L-1 in >80% of individuals were simulated and evaluated against external data. The predicted and observed allopurinol doses were compared using the mean prediction error (MPE) and root mean square error (RMSE). The proportion of Easy-Allo predicted doses within 100 mg of the observed was quantified. RESULTS: Allopurinol doses were predicted by total body weight, baseline urate, ethnicity and creatinine clearance. Easy-Allo1 produced unbiased and suitably precise dose predictions (MPE 2 mg day-1 95% confidence interval [CI] -13-17, RMSE 91%, 90% within 100 mg of the observed dose). Easy-Allo2 was positively biased by about 70 mg day-1 and slightly less precise (MPE 70 mg day-1 95% CI 52-88, RMSE 131%, 71% within 100 mg of the observed dose). CONCLUSIONS: The Easy-Allo tools provide a guide to the allopurinol maintenance dose requirement to achieve the serum urate target of <0.36 mmol L-1 and will aid in the development of novel dose-escalation strategies for allopurinol therapy.

Estimation of adherence to urate-lowering therapy in people living with gout using Australia's Pharmaceutical Benefits Scheme and patient-reported dosing.

AIMS: The aim of this study was to estimate adherence to urate-lowering therapy (ULT), predominately allopurinol, from Australia's Pharmaceutical Benefits Scheme (PBS) claims database in association with (1) patient-reported doses and (2) World Health Organization's (WHO) defined daily doses (DDD), namely, allopurinol (400 mg/day) or febuxostat (80 mg/day). METHODS: Proportion of days covered (PDC) was calculated in 108 Gout App (Gout APP) trial participants with at least two recorded ULT dispensings in an approximately 12-month period before provision of intervention or control apps. Adherence was defined as PDC ≥80%. We measured the correlation between the two methods of calculating PDC using a Wilcoxon signed rank test. Agreement between ULT-taking status (self-reports) and ULT-dispensed status (PBS records) was tested with Cohen's kappa (κ), and positive and negative percent agreement. RESULTS: Allopurinol was prescribed in 93.5% of participants taking ULT. Their self-reported mean daily dose (SD) was 291 (167) mg/day. Mean PDC (SD) for allopurinol was 83% (21%) calculated using self-reported dose, and 63% (24%) using WHO's DDD. Sixty-three percent of allopurinol users were identified as adherent (PDC ≥80%) using self-reported dose. There was good agreement between self-reported ULT use and PBS dispensing claims (κ = 0.708, P < .001; positive percent agreement = 90%, negative percent agreement = 82%). CONCLUSIONS: Participant-reported allopurinol daily doses, in addition to PBS dispensing claims, may enhance confidence in estimating PDC and adherence compared to using DDD. This approach improves adherence estimations from pharmaceutical claims datasets for medications where daily doses vary between individuals or where there is a wide therapeutic dose range.

Trends in Prevalence of Gout Among US Asian Adults, 2011-2018.

Importance: Gout disparities among Black individuals in the US have recently been explained by socioclinical factors; however, no information is available among Asian individuals living in Western countries, despite their disproportionately worsening metabolic health. Objective: To determine the prevalence of gout and serum urate concentrations according to race and ethnicity and to explore the association of social determinants of health and clinical factors. Design, Setting, and Participants: This is a population-based, cross-sectional analysis. Data from a nationally representative sample of US adults were obtained from the National Health and Nutrition Examination Survey (NHANES) (2011-2018) in which Asian race data were collected (primary). Data from the UK Biobank (2006-2021) were used for replication of the Asian vs White differences. Data analysis was performed from December 2021 to September 2022. Main Outcomes and Measures: Race-specific gout prevalence and serum urate levels. Results: A total of 22 621 participants from NHANES (2011-2018) were included in the analysis (mean [SD] age, 49.8 [17.8] years; 10 948 male participants [48.4%]). In 2017 to 2018, gout affected 12.1 million US individuals, with its crude prevalence increasing from 3.6% (95% CI, 2.8%-4.5%) in 2011 to 2012 to 5.1% (95% CI, 4.2%-5.9%) in 2017 to 2018 (P for trend = .03); this trend was no longer significant after age adjustment (P for trend = .06) or excluding Asian individuals (P for trend = .11). During the same period, age- and sex-adjusted prevalence among Asian Americans doubled from 3.3% (95% CI, 2.1%-4.5%) to 6.6% (95% CI, 4.4%-8.8%) (P for trend = .007) to numerically exceed all other racial and ethnic groups in 2017 to 2018, with age- and sex-adjusted odds ratio (ORs) of 1.61 (95% CI, 1.03-2.51) and a socioclinical factor-adjusted multivariable OR of 2.62 (95% CI, 1.59-4.33) for Asian vs White individuals. The latest age- and sex-adjusted gout prevalence among US individuals aged 65 years and older was 10.0% among White individuals and 14.8% among Asian individuals (including 23.6% of Asian men). Serum urate concentrations also increased between 2011 and 2018 among US Asian individuals (P for trend = .009). The Asian vs White disparity was also present in the UK Biobank. Conclusions and Relevance: The findings of this study suggest that the prevalence of gout among Asian individuals numerically surpassed that for all other racial and ethnic groups in 2017 to 2018. This Asian vs White disparity did not appear to be associated with socioclinical factors.

Up-regulation of HSPA1A and HSPA1B in the blood of tophi patients and its clinical significance.

OBJECTIVE: Poorly treated gout can cause tophi, which can lead to serious and potentially fatal complications. This study aimed to find the potential diagnostic value of blood levels of HSPA1A and HSPA1B for tophi patients. METHODS: 58 tophi patients and 61 healthy controls were enrolled in this study, and the whole venous blood samples of all subjects were collected for microarray analysis to identify differentially expressed genes associated with tophi. Meanwhile, KEGG and GO analysis were used to filtrate the enriched different expression genes. The mRNA expression levels of HSPA1A, as well as HSPA1B, were measured by the RT-qPCR method, the correlation between which and the severity of the disease were analyzed. Finally, the receiver operating characteristics curve (ROC) analysis has been performed to the diagnostic value of HSPA1A as well as HSPA1B. RESULTS: Bioinformatic analysis results suggested that both HSPA1A and HSPA1B are abnormally expressed in tophi. Then, it was observed that HSPA1A and HSPA1B were dramatically increased in the blood samples of tophi patients compared with healthy controls and were further linked with the severity of tophi. Moreover, the area under the curve (AUC) of HSPA1A for the diagnosis of ACI was 0.8999 (95% confidence interval (CI), 0.8338 to 0.9661) while of HSPA1B was 0.9093 (95% confidence interval (CI), 0.8550 to 0.9635), suggesting that blood level of HSPA1A, as well as HSPA1B, are sensitive markers to distinguish tophi patients from the healthy people. CONCLUSION: HSPA1A and HSPA1B were over-expressed in the blood of tophi patients and may be potential diagnostic markers for tophi.

Model-based cost-effectiveness analyses comparing combinations of urate lowering therapy and anti-inflammatory treatment in gout patients.

OBJECTIVES: To assess the cost-effectiveness of various combinations of urate lowering therapy (ULT) and anti-inflammatory treatment in the management of newly diagnosed gout patients, from the Dutch societal perspective. METHODS: A probabilistic patient-level simulation estimating costs and quality-adjusted life years (QALYs) comparing gout and hyperuricemia treatment strategies was performed. ULT options febuxostat, allopurinol and no ULT were considered. Flare treatments naproxen, colchicine, prednisone, and anakinra were considered. A Markov Model was constructed to simulate gout disease. Health states were no flare, and severe pain, mild pain, moderate pain, or no pain in the presence of a flare. Model input was derived from patient level clinical trial data, meta-analyses or from previously published health-economic evaluations. The results of probabilistic sensitivity analyses were presented using incremental cost-effectiveness ratios (ICERs), and summarized using cost-effectiveness acceptability curves (CEACs). Scenario analyses were performed. RESULTS: The ICER for allopurinol versus no ULT was €1,381, when combined with naproxen. Febuxostat yielded the highest utility, but also the highest costs (€4,385 vs. €4,063 for allopurinol), resulting in an ICER of €25,173 when compared to allopurinol. No ULT was not cost-effective, yielding the lowest utility. For the gout flare medications, comparable effects on utility were achieved. Combined with febuxostat, naproxen was the cheapest option (€4,404), and anakinra the most expensive (€4,651). The ICER of anakinra compared to naproxen was €818,504. Colchicine and prednisone were dominated by naproxen. CONCLUSION: Allopurinol and febuxostat were both cost-effective compared to No ULT. Febuxostat was cost-effective in comparison with allopurinol at higher willingness-to-pay thresholds. For treating gout flares, colchicine, naproxen and prednisone offered comparable health economic implications, although naproxen was the favoured option.