Lead Investigator: Michael Wiese, University of South Australia
Title of Proposal Research: Individualisation of gout flare prophylaxis when initiating urate-lowering therapy
Vivli Data Request: 6464
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Gout is the most common form of inflammatory arthritis, affecting approximately 1.6–6.8% of the Australian population. It occurs when the serum urate (SU) concentration in the blood exceeds the level of saturation, causing the urate salts to solidify and form monosodium urate crystals which deposit in the joints and soft tissues of susceptible individuals. The interaction between these crystals and the immune system results in an acute inflammatory response, known as a ‘gout flare’. Although self-limiting, gout flares cause immense pain, have considerable impact on quality of life and can reoccur frequently. Despite the perceived episodic nature of this disease, gout is a chronic condition and if left untreated can result in tophi (chronic collections of inflammatory tissue around the monosodium urate crystals), chronic gouty arthritis, gouty bone erosion and permanent disability. To improve the quality of life for people with gout and with the associated health care costs, hospitalizations and overall economic burden set to rise, it is important to focus on optimising management.
The long-term management of gout involves the use of urate-lowering therapy (ULT) to reduce SU concentrations, thus allowing for crystal dissolution and eventual flare cessation. However, after commencing ULT, some patients may experience a temporary rise in gout flares which may last up to 6-12 months. The inability to predict who will flare when commencing therapy, or when they will flare, has prompted the recommendation that gout flare prophylaxis be considered for a minimum of 6-months in all patients. Despite the common use of prophylaxis in clinical practice, few studies have investigated the efficacy and safety of this approach. Using the diverse range of data commonly collected in clinical trials (e.g. data on patient characteristics, laboratory data, disease classification, pharmacokinetic, concomitant medicines, etc), we hypothesize it will be possible to identify patients likely to experience ULT-induced gout flares. Being able to predict flares will enable clinicians to make more informed decisions regarding whether to give a patient flare prophylaxis and for how long, thereby improving the risk versus benefit ratio for patients and contributing to the quality use of medicines.
This research will be conducted using participant-level data meta-analysis. Available data from gout patients initiating ULT will be analysed to identify and validate predictors of ULT-induced gout flares and investigate the safety and efficacy of gout flare prophylaxis. This will be performed using cox-proportional hazard / time-to-event modelling. This type of modelling allows for multiple covariates to be tested into the model, both individually and simultaneously in order to investigate if they influence the rate of flares.
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