Neus Quilis1, Francisca Sivera2, Daniel Seoane-Mato3, Fernando Pérez-Ruiz4, Carlos Sánchez-Piedra3, Federico Díaz-González5, Sagrario Bustabad-Reyes6. 1. Rheumatology, Hospital General Universitario Elda, Elda, Spain. 2. Rheumatology, Hospital General Universitario Elda, Elda, Spain; Dept Medicine, Universidad Miguel Hernandez, Elche, Spain. Electronic address: fransimas@yahoo.es. 3. Research Unit (UI), Sociedad Española de Reumatologia (SER), Madrid, Spain. 4. Rheumatology, Hospital Universitario Cruces, Baracaldo, Spain. 5. Rheumatology, Hospital Universitario de Canarias, La Laguna, Santa Cruz de Tenerife, Spain; Universidad de La Laguna, La Laguna, Santa Cruz de Tenerife, Spain. 6. Rheumatology, Hospital Universitario de Canarias, La Laguna, Santa Cruz de Tenerife, Spain.
Abstract
OBJECTIVE: To estimate the prevalence of gout in Spain. METHODS: Cross-sectional, population-based study of people aged 20 years or older. First, randomly selected individuals were contacted by telephone and rheumatic disease screening questionnaires were conducted. If the first screening was positive, medical records were then reviewed and/or a phone questionnaire was conducted by a rheumatologist, followed by an appointment if necessary. Newly diagnosed cases had to fulfil the ACR/EULAR 2015 criteria. To calculate the prevalence and its 95% CI, the sample design was taken into account and weighing was calculated according to age, sex and geographic origin. RESULTS: In all, 4916 individuals were included, 1361 had a positive screening result for gout (59 of them reported a prior diagnosis). Of these, 51 were classified as missing and 95 were classified as gout cases. An additional case was detected through a positive screening for fibromyalgia and Sjögren's syndrome, although a previous gout diagnosis was confirmed by a review of the medical records. Of the 96 gout cases, 31 (32%) were de novo diagnoses. The estimated weighted prevalence of gout was 2.4% (95% CI 1.95-2.95), with a higher prevalence in men (4.55% [95%CI 3.65-5.65]) than women (0.38% [95%CI 0.19-0.76]). CONCLUSION: EPISER2016 is the first population-based study to estimate the prevalence of gout in Spain. Undiagnosed patients accounted for a substantial proportion of cases, highlighting the need for population-approaches when estimating the prevalence of infra-diagnosed diseases. Reliable national approaches are key to obtaining accurate estimates of diseases to better aid healthcare and workforce planning.
OBJECTIVE: To estimate the prevalence of gout in Spain. METHODS: Cross-sectional, population-based study of people aged 20 years or older. First, randomly selected individuals were contacted by telephone and rheumatic disease screening questionnaires were conducted. If the first screening was positive, medical records were then reviewed and/or a phone questionnaire was conducted by a rheumatologist, followed by an appointment if necessary. Newly diagnosed cases had to fulfil the ACR/EULAR 2015 criteria. To calculate the prevalence and its 95% CI, the sample design was taken into account and weighing was calculated according to age, sex and geographic origin. RESULTS: In all, 4916 individuals were included, 1361 had a positive screening result for gout (59 of them reported a prior diagnosis). Of these, 51 were classified as missing and 95 were classified as gout cases. An additional case was detected through a positive screening for fibromyalgia and Sjögren's syndrome, although a previous gout diagnosis was confirmed by a review of the medical records. Of the 96 gout cases, 31 (32%) were de novo diagnoses. The estimated weighted prevalence of gout was 2.4% (95% CI 1.95-2.95), with a higher prevalence in men (4.55% [95%CI 3.65-5.65]) than women (0.38% [95%CI 0.19-0.76]). CONCLUSION: EPISER2016 is the first population-based study to estimate the prevalence of gout in Spain. Undiagnosed patients accounted for a substantial proportion of cases, highlighting the need for population-approaches when estimating the prevalence of infra-diagnosed diseases. Reliable national approaches are key to obtaining accurate estimates of diseases to better aid healthcare and workforce planning.