GOUT: risk factors and treatment in general practice

BACKGROUND In the Netherlands, 90% of the patients with gout are managed by general practitioners (GPs) but most research has been done in secondary care. In primary care there are many questions on the clinical relevance of long-term uric acid lowering treatment of gout. It is also unclear whether factors such as diet, overweight and use of medication might be associated with gout attack frequency. Finally, gout has been shown to be strongly associated with cardiovascular diseases and renal insufficiency, but whether gout should serve as a risk factor for the future development of such diseases is not yet known. OBJECTIVES We will use the Integrated Primary Care Information (IPCI) database that includes GPs’ registries of 1.5 million people in the Netherlands in general practices, as well as a prospective gout patient cohort study in general practice. GP registry Database 1. Are use, and type of, antihypertensive medication, acetylsalicylics, hypertension, renal insufficiency, one or more cardiovascular diseases associated with development of gout in patients in general practice? 2. To what degree is the presence of gout in patients in general practice an additional risk factor for future cardiovascular diseases and cardiovascular mortality, over a follow-up period up to 15 years, in patients that are not known with these diseases at the time of the first gout attack? 3. To what degree is the presence of gout in patients in general practice an additional risk factor for future renal insufficiency? 4. Is treatment with allopurinol associated with a decrease of future cardiovascular events and /or renal insufficiency in patients with gout diagnosed by the GP? Patient cohort study 5. What is the frequency of self-reported gout attacks of patients in general practice and with what factors (e.g. lifestyle factors, food intake, medication usage) does this frequency associate? 6. Does treatment with allopurinol decrease self-reported gout attack frequency and/or tophi in a cohort of patients with gout diagnosed by the general practitioner? STUDY DESIGN AND PATIENTS GP registry Database In this GP registry database study, all adult patients in the IPCI database with at least one registered gout episode between 2001 and 2015 will be included. We aim to include 12,000 patients. Patient cohort study Adult patients with a recent gout attack in the IPCI database (2013/2014/2015) will be invited to participate. We aim to include 1300 patients for this prospective study. OUTCOMES GP registry Database From the IPCI database we will assess: Gender, age, episodes of gout, use of diuretics and salicylates, presence of diabetes, rheumatoid arthritis, cardiovascular diseases (angina pectoris, myocardial infarction, heart failure, cerebrovascular accident, transient ischemic attack, or peripheral vascular disease), cardiovascular risk factors and renal insufficiency. Patient cohort study At baseline patients will fill in questionnaires, and a physical examination and a blood sample will take place. During the two year follow-up, 8 questionnaires will be filled in every 3 months by the patients. We will assess: - Primary outcome: Frequency of gout attacks. - Secondary outcome: Presence of tophi. - Other determinants and co-factors: age, gender, body-mass index, smoking status, fructose-rich/carbonated beverages and alcohol consumption, purine rich food intake, education level, compliance to prescribed medication, use of (over the counter) medication, physical activity, co-morbidity, and quality of life. - Physical examination: blood pressure. - Laboratory serum examination: estimated glomerular filtration rate, uric acid level, cholesterol, low and high-density-lipoproteïne cholesterol, and glucose (fasting). STATISTICAL ANALYSES GP registry Database For objectives 1 to 4 we will use a marginal cox hazard regression modelling to assess risk factors. Patient cohort study Poisson regression analysis will be used for objective 5. For objective 6, before Poisson regression analysis, we will apply a propensity score matching analysis with caliper matching, a method to reduce selection by indication as much as possible in order to compare frequency of gout attacks with and without uric acid lowering treatment. FEASIBILITY The research is highly feasible because we have ample experience with recruiting patients from the IPCI database for further observational research (patient cohort study) and all data for the GP registry Database study is already available. TIME SCHEDULE We aim for a combined GP training and PhD traject (Aiotho); duration of 66 months which includes 27 months research: - 6 months clinical epidemiology courses (NIHES). - 6 months setting up the prospective cohort study; 2-year follow-up will take place in the period of GP training. - 9 months objectives 1 to 4. - 5 months objectives 5 and 6. - 1 month thesis preparation.