Comorbidity onset varies within clusters among patients with gout; however flare patterns did not differ between clusters, according to study results published in Rheumatology.

In the current 5-year primary, care-based, prospective cohort study, the researchers enrolled adults with gout from 20 general practices across the United Kingdom. Data of patients with gout were identified from electronic medical records. Patients who completed a baseline questionnaire were mailed follow-up questionnaires at 1, 2, 3, 4, and 5 years post-enrollment; the questionnaires included clinical and demographic characteristics, including gout onset and the presence of gout flares. The primary outcome was development of an incident comorbidity during follow-up.

Patients were categorized into 4 primary clusters depending on the presence of comorbidities at baseline: gout with prevalent chronic kidney disease (CKD; cluster 1); isolated gout with few comorbidities (cluster 2); gout with multiple comorbidities (cluster 3); and gout with prevalent obesity and hypertension (cluster 4).


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Poisson regression was used to calculate the incidence rate ratios (IRRs) of comorbidities within each cluster compared with the isolated gout cluster. Finally, logistic regression was used to assess the relationship between baseline characteristics and the number of reported gout flares over time.

Baseline and follow-up data were available for 916 patients with gout. The comorbidities with the highest incidence over follow-up were coronary artery disease (CAD; 39.2%), hypertension (36.7%), CKD stage 3 or higher (18.1%), obesity (16.0%), hyperlipidemia (11.7%), diabetes (8.8%), and cancer (8.4%). Baseline cluster membership was significantly associated with the incidence of certain conditions during follow-up. The IRR of CAD was substantially elevated in cluster 1 (IRR, 1.73), cluster 3 (IRR, 1.55), and cluster 4 (2.31). Similarly, hyperlipidemia was substantially more common in cluster 3 (IRR, 1.85) and cluster 4 (IRR, 1.99). The incidence of hypertension was elevated only in cluster 1 (IRR, 1.46).

Based on fully adjusted regression models, the researchers did not observe a significant association between baseline cluster membership and the frequency of gout flares during follow-up. However, other baseline characteristics were substantially associated with gout flares, including history of oligo/polyarticular flares (odds ratio [OR], 2.16; 95% CI, 1.73-2.70; P <.001) and obesity (OR, 1.66; 95% CI, 1.25-2.25; P =.001). Age at questionnaire completion (OR, 0.98; 95% CI, 0.97-0.99; P =.007) and use of allopurinol (OR, 0.42; 95% CI, 0.34-0.53; P <.001) appeared to be protective against flares.

Researchers suggested that prevalent comorbidities influenced the development of later comorbidities in gout. The most common incident comorbidities in the study were CAD, hypertension, obesity, CKD, and diabetes.

Study limitations included the fact that self-report questionnaires were used rather than medical records to assess gout flares. In addition, adherence to gout medications was not included in the study.

“[Our] findings reinforce the need for screening people with gout for cardiovascular risk factors and renal function, guide clinicians as to which comorbidity phenotypes are at particular risk of developing new comorbidities, and support the provision of integrated care for comorbidities,” the researchers wrote. “Future research could examine whether comorbidity cluster membership changes over time and longitudinal patterns of comorbidity clustering, and further explore the influence of clustering on flare frequency.”

Reference

Bajpai R, Muller S, Mallen C, et al. Onset of comorbidities and flare patterns within pre-existing morbidity clusters in people with gout: 5-year primary care cohort study. Rheumatology (Oxford). Published online March 21, 2021. doi:10.1093/rheumatology/keab283