Predicting Gout Flares in People Starting Allopurinol Using the Start-Low Go-Slow Dose Escalation Strategy.

OBJECTIVE: The study objective was to determine predictors of gout flare when commencing allopurinol using the "start-low go-slow" dose escalation strategy. METHODS: A post hoc analysis of a 12-month double-blind placebo-controlled noninferiority trial with participants randomized 1:1 to colchicine 0.5 mg daily or placebo for the first six months was undertaken. Multivariate logistic regression models were used to identify independent predictors of gout flares in the first and last six months of the trial. RESULTS: Multivariable analysis revealed a significant association between risk of a gout flare in the first six months and flare in the month before starting allopurinol (odds ratio [OR] 2.65, 95% confidence interval [CI] 1.36-5.17) and allopurinol 100 mg starting dose (OR 3.21, 95% CI 1.41-7.27). The predictors of any gout flares in the last six months of the trial, after stopping colchicine or placebo, were having received colchicine (OR 2.95, 95% CI 1.48-5.86), at least one flare in the month before stopping study drug (OR 5.39, 95% CI 2.21-13.15), and serum urate ≥0.36 mmol/L at month 6 (OR 2.85, 95% CI 1.14-7.12). CONCLUSION: Anti-inflammatory prophylaxis when starting allopurinol using the "start-low go-slow" dose escalation strategy may be best targeted at those who have had a gout flare in the month before starting allopurinol and are commencing allopurinol 100 mg daily. For those with ongoing gout flares during the first six months of starting allopurinol who have not yet achieved serum urate target, a longer period of prophylaxis may be required.

Gout and its management.

Gout is a common and treatable chronic disease of monosodium urate crystal deposition. It is experienced as extremely painful episodes of joint inflammation that impact all aspects of the person's life. This Clinical Perspectives article provides an update on gout diagnosis, medications and strategies to improve the quality of gout care.

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.

Interaction of genetic variation at ADH1B and MLXIPL with alcohol consumption for elevated serum urate level and gout among people of European ethnicity.

BACKGROUND: Alcohol consumption is a risk factor for hyperuricaemia and gout. Multiple single-nucleotide polymorphisms (SNPs) have been identified as associated with both alcohol consumption and serum urate or gout in separate genome-wide association studies (GWAS). This study aimed to identify and characterise interactions between these shared signals of genetic association and alcohol consumption for serum urate level, hyperuricaemia, and gout. METHODS: This research was conducted using the UK Biobank resource. The association of alcohol consumption with serum urate and gout was tested among 458,405 European participants. Candidate SNPs were identified by comparing serum urate, gout, and alcohol consumption GWAS for shared signals of association. Multivariable-adjusted linear and logistic regression analyses were conducted with the inclusion of interaction terms to identify SNP-alcohol consumption interactions for association with serum urate level, hyperuricaemia, and gout. The nature of these interactions was characterised using genotype-stratified association analyses. RESULTS: Alcohol consumption was associated with elevated serum urate and gout. For serum urate level, non-additive interactions were identified between alcohol consumption and rs1229984 at the ADH1B locus (P = 3.0 × 10-44) and rs6460047 at the MLXIPL locus (P = 1.4 × 10-4). ADH1B also demonstrated interaction with alcohol consumption for hyperuricaemia (P = 7.9 × 10-13) and gout (P = 8.2 × 10-9). Beer intake had the most significant interaction with ADH1B for association with serum urate and gout among men, while wine intake had the most significant interaction among women. In the genotype-stratified association analyses, ADH1B and MLXIPL were associated with serum urate level and ADH1B was associated with hyperuricaemia and gout among consumers of alcohol but not non-consumers. CONCLUSIONS: In this large study of European participants, novel interactions with alcohol consumption were identified at ADH1B and MLXIPL for association with serum urate level and at ADH1B for association with hyperuricaemia and gout. The association of ADH1B with serum urate and gout may occur through the modulation of alcohol metabolism rate among consumers of alcohol.

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.

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.

Relationship Between Adalimumab Concentrations, Antidrug Antibodies, and Disease Activity in Rheumatoid Arthritis: A Cross-Sectional Observational Study.

OBJECTIVES: To determine the influence of patient characteristics and disease activity on adalimumab (ADA) concentrations; to assess the relationships between ADA concentrations, the presence of antidrug antibodies (ADAb), and disease activity in rheumatoid arthritis (RA); and to determine the association between cytokine concentrations and ADA concentrations. METHODS: A cross-sectional study of people with RA receiving ADA for at least 4 weeks was undertaken. Disease activity was assessed by the Disease Activity Score in 28 joints (DAS28), with responders defined as DAS28 ≤ 3.2. Serum and plasma were obtained for ADA concentrations and ADAb, and a panel of cytokines were obtained for a subgroup. ADA concentrations were compared between demographic and clinical subgroups using ANOVA. The independent associations between clinical and demographic features were analyzed using a general linear model. Variables significantly associated with ADA concentrations from the univariate analyses were entered into multivariate analyses. RESULTS: Of the 156 participants, 69.2% were female and the mean age was 57.4 (SD 12.7) years. Multivariate analysis revealed that higher C-reactive protein (P < 0.001) and higher weight (P < 0.004) were independently associated with lower ADA concentrations. ADA concentrations were higher in those with DAS28 ≤ 3.2 compared to those with DAS28 > 3.2 (median 10.8 [IQR 6.4-20.8] mg/L vs 7.1 [IQR 1.5-12.6] mg/L, P < 0.001). There was a significant negative correlation between interleukin 6 (IL-6) and ADA concentrations (r = -0.04, P < 0.01). CONCLUSION: ADA concentration correlates negatively with markers of inflammatory disease activity in RA, including IL-6. ADA concentration in the range 5 to 7 mg/L over the dose interval are associated with better disease control.

Moving urate-lowering therapy in gout beyond guideline recommendations.

The 'treat-to target serum urate strategy' when using urate-lowering therapy has been recommended by most specialist rheumatology societies for many years. An alternative "treat-to-avoid-symptoms" in gout has been suggested, albeit without a clear definition of what this means and how it might be implemented in clinical trials or clinical practice. This has hampered efforts to design clinical trials that compare the "treat-to-target [urate]" and "treat-to-avoid-symptoms" strategies in the long-term management of gout. In this review we consider the rationale for the treat-to-target urate strategy when using urate-lowering therapy, potential definitions of a "treat-to-avoid-symptoms" strategy, or perhaps what is not "treat-to-avoid-symptoms", and approaches that might address this uncertainty.

Weight Loss for Patients With Gout and Concomitant Obesity: A Proof-of-Concept Randomized Trial.

OBJECTIVE: Despite scarce evidence, guidelines recommend weight loss as a management strategy for patients with gout. We investigated the effect of an intensive dietary intervention on body weight and clinical measures of gout severity in individuals with obesity and gout. METHODS: We conducted a 16-week randomized nonmasked parallel-group trial in Denmark, randomly assigning (one-to-one) individuals with obesity and gout to a low-energy diet or a control diet. The primary outcome was change in body weight. Key secondary outcomes were changes in serum urate (SU) level and visual analog scale-assessed pain and fatigue. RESULTS: Between December 1, 2018, and June 1, 2019, 61 participants were included in the intention-to-treat population and randomly assigned to the intensive diet group (n = 29) or control diet group (n = 32). Participants had a mean age of 60.3 (SD 9.9) years and mean body mass index of 35.6 (SD 5.0), and 59 (97%) were men. After 16 weeks, there was a significant difference in change in body weight between the diet and control groups (-15.4 vs -7.7 kg; difference -7.7 kg [95% confidence interval -10.7 to -4.7], P < 0.001). Despite results being potentially in favor of a low-energy diet, we could not confirm differences in SU level changes and fatigue between groups. No differences in pain and gout flares were observed between groups. No serious adverse events or deaths occurred during the trial. CONCLUSION: An intensive dietary intervention was safe and effectively lowered body weight in people with obesity and gout, but the weight loss did not directly translate into effects on SU level, fatigue, and pain.

Uptake of the Gout and Crystal Arthritis Network Consensus Statements for Gout Nomenclature.

OBJECTIVE: In 2019, the Gout and Crystal Arthritis Network (G-CAN) published consensus statements for the nomenclature of disease elements and states in gout. The aim of this study was to determine adherence to the G-CAN consensus nomenclature statements since publication. METHODS: American College of Rheumatology and EULAR conference abstracts were searched using online databases for the keywords 'gout,' 'urate,' 'uric acid,' 'hyperuricaemia,' 'tophus,' and/or 'tophi' before and after publication of the consensus statements (January 1, 2016 to December 31, 2017 and January 1, 2020 to December 31, 2021, respectively). Abstracts were manually searched for labels used to reference gout disease elements and states. Use of the G-CAN-agreed labels, as well as alternatives, were compared between the two time periods. RESULTS: There were 988 abstracts included in the analysis: 596 in 2016 to 2017 and 392 in 2020 to 2021. Use of the agreed labels 'urate' and 'gout flare' increased between the two periods. There were 219 of 383 abstracts (57.2%) with the agreed label 'urate' in 2016 to 2017 compared with 164 of 232 (70.7%) in 2020 to 2021 (P = 0.001). There were 60 of 175 abstracts (34.3%) with the agreed label 'gout flare' in 2016 to 2017 compared with 57 of 109 (52.3%) in 2020 to 2021 (P = 0.003). Consistent with the G-CAN statement, use of the label 'chronic gout' reduced between the two time periods. There were 29 of 596 abstracts (4.9%) in 2016 to 2017 that used the label 'chronic gout' compared with 8 of 392 abstracts (2.0%) in 2020 to 2021 (P = 0.02). CONCLUSION: Use of G-CAN-agreed gout labels has increased, but gout nomenclature remains imprecise. Additional efforts are needed to ensure consistent use of agreed nomenclature for gout in the scientific literature.

Colchicine: the good, the bad, the ugly and how to minimize the risks.

Colchicine has an important role in managing various conditions, including gout, familial Mediterranean fever, amyloidosis, Behçet's syndrome, recurrent pericarditis and calcium pyrophosphate deposition disease. The adverse effect profile of colchicine is well understood. However, due to its narrow therapeutic index, colchicine has been associated with overdose and fatalities. When ingested in toxic amounts, the mainstay of management is supportive care. Strategies to minimize the risk of colchicine poisoning can focus on three broad causes: unauthorized access, intentional overdose and inappropriate dosing. Culturally safe and appropriate education about storage and appropriate use of colchicine is essential to minimize the risk of overdose.

Rheumatoid interstitial lung disease in Canterbury, Aotearoa New Zealand - A retrospective cohort study.

BACKGROUND: Rheumatoid arthritis associated interstitial lung disease (RA-ILD), is an important extra-articular manifestation of rheumatoid arthritis (RA). The frequency, risk factors, and prognosis of RA-ILD are incompletely understood. AIMS: To determine the prevalence and incidence, clinical characteristics and risk factors for development, and outcomes of persons with RA-ILD in the population of the Canterbury District Health Board (CDHB) catchment area. METHODS: Individuals aged ≥ 18 years with RA, resident in the CDHB catchment area between 1 January 2006 and 31 December 2008 (Period One), and 1 January 2011 to 31 December 2013 (Period Two) were identified by medical record review and followed until 30 June 2019. Individuals with RA-ILD as defined by pre-specified criteria were identified. The association between demographic and clinical characteristics and RA-ILD development and mortality was examined using Cox-proportional hazards models. RESULTS: The prevalence of RA-ILD per 100,000 was 10.97 (95 % CI 7.53,14.42) for Period One, and 14.74 (95 % CI 10.84,18.63) for Period Two. Among individuals evaluated for risk factors for RA-ILD development, the estimated cumulative incidence of ILD at 10 years was 4.47 % (95 % CI 3.14, 6.14). After adjusting for age, rheumatoid factor positivity (HR 3.73, 95 % CI, 1.32,10.56), extra-articular manifestations other than RA-ILD (HR 4.48, 95 % CI 2.36,8.48), and subcutaneous rheumatoid nodules (HR 4.66, 95 % CI 2.34, 9.26) were associated with increased risk of developing RA-ILD. The standardised mortality ratio for RA-ILD was 3.90 (95 % CI 2.55,5.72) compared to the general population. Extent of ILD on CT chest was associated with mortality (HR for >20% vs. < 20 % 4.47, 95 % CI 1.67,11.96). CONCLUSIONS: Clinically evident RA-ILD occurred in approximately 5 % of individuals with RA. Mortality was increased almost fourfold compared to the general population. Radiologic extent was the most important prognostic factor.

The statistical challenge of analysing changes in dual energy computed tomography (DECT) urate volumes in people with gout.

BACKGROUND: Dual energy computed tomography (DECT) allows direct visualization of monosodium urate crystal deposition in gout. However, DECT urate volume data are often highly skewed (mostly small volumes with the remainder considerably larger), making statistical analyses challenging in longitudinal research. The aim of this study was to explore the ability of various analysis methods to normalise DECT urate volume data and determine change in DECT urate volumes over time. METHODS: Simulated datasets containing baseline and year 1 DECT urate volumes for 100 people with gout were created from two randomised controlled trials. Five methods were used to transform the DECT urate volume data prior to analysis: log-transformation, Box-Cox transformation, log(X-(min(X)-1)) transformation; inverse hyperbolic sine transformation, and rank order. Linear regression analyses were undertaken to determine the change in DECT urate volume between baseline and year 1. Cohen's d were calculated as a measure of effect size for each data treatment method. These analyses were then tested in a validation clinical trial dataset containing baseline and year 1 DECT urate volumes from 91 people with gout. RESULTS: No data treatment method successfully normalised the distribution of DECT urate volumes. For both simulated and validation data sets, significant reductions in DECT urate volumes were observed between baseline and Year 1 across all data treatment methods and there were no significant differences in Cohen's d effect sizes. CONCLUSIONS: Normalising highly skewed DECT urate volume data is challenging. Adopting commonly used transformation techniques may not significantly improve the ability to determine differences in measures of central tendency when comparing the change in DECT urate volumes over time.

The Tophus Impact Questionnaire (TIQ-20): responsiveness to change during urate-lowering therapy.

OBJECTIVES: In 2015, the 20-item Tophus Impact Questionnaire (TIQ-20) was developed as a tophus-specific patient reported outcome measure. The aim of this study was to determine whether TIQ-20 scores change during urate-lowering therapy. METHODS: We analysed data from a two-year clinical trial of allopurinol dose escalation using a treat-to-target serum urate approach. For participants with tophaceous gout, the longest diameter of up to three index tophi was measured using Vernier calipers and the TIQ-20 was recorded at study visits. Participants at the one site were invited into a dual energy CT (DECT) sub-study. Participants were included in this analysis if they had tophaceous gout and TIQ-20 scores available at baseline, Year 1, and Year 2 (n = 58, 39 with DECT data). Data were analysed using mixed model approach to repeated measures. RESULTS: Improvements were observed in all tophus measures over the two-year period. The mean (SD) TIQ-20 scores reduced over two years from 3.59 (1.77)-2.46 (1.73), P< 0.0001, and the mean (95%CI) TIQ-20 change over the two years was -1.13 (-1.54, -0.71). Effect size (Cohen's d) for the change in the sum of the index tophi diameter over two years was 0.68, for DECT urate volume was 0.50, and for the TIQ-20 was 0.71. CONCLUSION: For people with tophaceous gout treated with allopurinol using a treat to target serum urate approach, improvements in TIQ-20 occur, as well as improvements in physical and imaging tophus measures. These findings demonstrate that the TIQ-20 is a responsive patient-reported instrument of tophus impact.

Comparative effectiveness of pharmacological interventions for hand osteoarthritis: a systematic review and network meta-analysis of randomised trials.

OBJECTIVE: To explore the comparative effectiveness of pharmacological interventions for hand osteoarthritis (OA). METHODS: We systematically searched Embase, MEDLINE, and the Cochrane Central Register of Controlled Trials from inception until 26 December 2021, for randomised trials of pharmacological interventions for people with hand OA. Two reviewers independently extracted study data and assessed the risk of bias. We calculated the effect sizes for pain (standardised mean differences) using Bayesian random effects models for network meta-analysis (NMA) and pairwise meta-analysis. Based on a pre-specified protocol, we prospectively registered the study at PROSPERO, CRD42021215393. RESULTS: We included 72 trials with 7609 participants. 65 trials (n=5957) were eligible for the quantitative synthesis, investigating 29 pharmacological interventions. Oral non-steroidal anti-inflammatory drugs (NSAIDs) and oral glucocorticoids' NMA effect sizes were -0.18 (95% credible interval -0.36 to 0.02) and -0.54 (-0.83 to -0.24), respectively, compared with placebo, and the result was consistent when limiting evidence to the pairwise meta-analysis of trials without high risk of bias. Intra-articular hyaluronate, intra-articular glucocorticoids, hydroxychloroquine, and topical NSAIDs' NMA effect sizes were 0.22 (-0.08 to 0.51), 0.25 (0.00 to 0.51), -0.01 (-0.19 to 0.18), and -0.14 (-0.33 to 0.08), respectively, compared with placebo. Oral NSAIDs were inferior to oral glucocorticoids with an NMA effect size of 0.36 (0.01 to 0.72). No intervention was superior to placebo when stratifying for thumb and finger OA. CONCLUSION: Oral NSAIDs and glucocorticoids are apparently effective pharmacological interventions in hand OA. Intra-articular therapies and topical NSAIDs were not superior to placebo.