TY - JOUR
T1 - Gout incidence and management during the COVID-19 pandemic in England, UK
T2 - a nationwide observational study using OpenSAFELY
AU - Russell, Mark D.
AU - Massey, Jon
AU - Roddy, Edward
AU - MacKenna, Brian
AU - Bacon, Seb
AU - Goldacre, Ben
AU - Andrews, Colm D.
AU - Hickman, George
AU - Mehrkar, Amir
AU - Mahto, Arti
AU - Rutherford, Andrew I.
AU - Patel, Samir
AU - Adas, Maryam A.
AU - Alveyn, Edward
AU - Nagra, Deepak
AU - Bechman, Katie
AU - Ledingham, Joanna M.
AU - Hudson, Joanna
AU - Norton, Sam
AU - Cope, Andrew P.
AU - Galloway, James B.
N1 - Funding Information:
We are grateful for the support received from the TPP Technical Operations team throughout this work, and for generous assistance from the information governance and database teams at NHS England and the NHS England Transformation Directorate. This research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (MC_PC_20058). In addition, the OpenSAFELY platform is supported by grants from the Wellcome Trust (222097/Z/20/Z), Medical Research Council (MR/V015757/1, MC_PC-20059, and MR/W016729/1), NIHR (NIHR135559 and COV-LT2–0073), and Health Data Research UK (HDRUK2021.000 and 2021.0157). MDR is funded by an NIHR Doctoral Fellowship (NIHR300967). BG has received funding from the Peter Bennett Foundation, the Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, and the Mohn Westlake Foundation; all authors employed by the Bennett Institute for Applied Data Science were supported by BG's grants on this work. BMK is employed by NHS England, working on medicines policy, and is Clinical Lead for primary care medicines data. The views expressed in this publication are those of the authors and not necessarily those of the NHS, NIHR, Public Health England, or the Department of Health and Social Care. No funding bodies had any role in study design, data collection, analysis or interpretation, manuscript writing, or in the decision to submit the article for publication.
Funding Information:
We are grateful for the support received from the TPP Technical Operations team throughout this work, and for generous assistance from the information governance and database teams at NHS England and the NHS England Transformation Directorate. This research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (MC_PC_20058). In addition, the OpenSAFELY platform is supported by grants from the Wellcome Trust (222097/Z/20/Z), Medical Research Council (MR/V015757/1, MC_PC-20059, and MR/W016729/1), NIHR (NIHR135559 and COV-LT2–0073), and Health Data Research UK (HDRUK2021.000 and 2021.0157). MDR is funded by an NIHR Doctoral Fellowship (NIHR300967). BG has received funding from the Peter Bennett Foundation, the Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, and the Mohn Westlake Foundation; all authors employed by the Bennett Institute for Applied Data Science were supported by BG's grants on this work. BMK is employed by NHS England, working on medicines policy, and is Clinical Lead for primary care medicines data. The views expressed in this publication are those of the authors and not necessarily those of the NHS, NIHR, Public Health England, or the Department of Health and Social Care. No funding bodies had any role in study design, data collection, analysis or interpretation, manuscript writing, or in the decision to submit the article for publication.
Funding Information:
MDR, BM, and JBG conceptualised the study. MDR, JM, ER, BM, AMa, AIR, SP, MAA, EA, DN, JH, KB, JML, SN, APC, and JBG developed the methodology. MDR, CDA, SN, and JBG contributed to the formal analysis. MDR and JBG developed the diagnostic codelists. JM, BM, SB, BG, CDA, GH, and AMe developed software for the OpenSAFELY platform. MDR wrote the original draft. All authors revised, reviewed, and edited the manuscript. All authors read and approved the final manuscript. MDR and JBG are the guarantors for the Article, accept full responsibility for the work and the conduct of the study, and had final responsibility for the decision to submit for publication. MDR and JM directly accessed and verified the underlying data reported in the manuscript. This study was supported by JML (Clinical Director for the National Early Inflammatory Arthritis Audit) as senior sponsor.
Publisher Copyright:
© 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2023/10
Y1 - 2023/10
N2 - Background: Gout is the most prevalent inflammatory arthritis, yet one of the worst managed. Our objective was to assess how the COVID-19 pandemic impacted incidence and quality of care for people with gout in England, UK. Methods: With the approval of National Health Service England, we did a population-level cohort study using primary care and hospital electronic health record data for 17·9 million adults registered with general practices using TPP health record software, via the OpenSAFELY platform. The study period was from March 1, 2015, to Feb 28, 2023. Individuals aged 18–110 years were defined as having incident gout if they were assigned index diagnostic codes for gout, were registered with TPP practices in England for at least 12 months before diagnosis, did not receive prescriptions for urate-lowering therapy more than 30 days before diagnosis, and had not been admitted to hospital or attended an emergency department for gout flares more than 30 days before diagnosis. Outcomes assessed were incidence and prevalence of people with recorded gout diagnoses, incidence of gout hospitalisations, initiation of urate-lowering therapy, and attainment of serum urate targets (≤360 μmol/L). Findings: From a reference population of 17 865 145 adults, 246 695 individuals were diagnosed with incident gout. The mean age of individuals with incident gout was 61·3 years (SD 16·2). 66 265 (26·9%) of 246 695 individuals were female, 180 430 (73·1%) were male, and 189 035 (90·9%) of 208 050 individuals with available ethnicity data were White. Incident gout diagnoses decreased by 30·9% in the year beginning March, 2020, compared with the preceding year (1·23 diagnoses vs 1·78 diagnoses per 1000 adults). Gout prevalence was 3·07% in 2015–16, and 3·21% in 2022–23. Gout hospitalisations decreased by 30·1% in the year commencing March, 2020, compared with the preceding year (9·6 admissions vs 13·7 admissions per 100 000 adults). Of 228 095 people with incident gout and available follow-up, 66 560 (29·2%) were prescribed urate-lowering therapy within 6 months. Of 65 305 individuals who initiated urate-lowering therapy with available follow-up, 16 790 (25·7%) attained a serum urate concentration of 360 μmol/L or less within 6 months of urate-lowering therapy initiation. In interrupted time-series analyses, urate-lowering therapy prescribing improved modestly during the pandemic, compared with pre-pandemic, whereas urate target attainment was similar. Interpretation: Using gout as an exemplar disease, we showed the complexity of how health care was impacted during the COVID-19 pandemic. We observed a reduction in gout diagnoses but no effect on treatment metrics. We showed how country-wide, routinely collected data can be used to map disease epidemiology and monitor care quality. Funding: None.
AB - Background: Gout is the most prevalent inflammatory arthritis, yet one of the worst managed. Our objective was to assess how the COVID-19 pandemic impacted incidence and quality of care for people with gout in England, UK. Methods: With the approval of National Health Service England, we did a population-level cohort study using primary care and hospital electronic health record data for 17·9 million adults registered with general practices using TPP health record software, via the OpenSAFELY platform. The study period was from March 1, 2015, to Feb 28, 2023. Individuals aged 18–110 years were defined as having incident gout if they were assigned index diagnostic codes for gout, were registered with TPP practices in England for at least 12 months before diagnosis, did not receive prescriptions for urate-lowering therapy more than 30 days before diagnosis, and had not been admitted to hospital or attended an emergency department for gout flares more than 30 days before diagnosis. Outcomes assessed were incidence and prevalence of people with recorded gout diagnoses, incidence of gout hospitalisations, initiation of urate-lowering therapy, and attainment of serum urate targets (≤360 μmol/L). Findings: From a reference population of 17 865 145 adults, 246 695 individuals were diagnosed with incident gout. The mean age of individuals with incident gout was 61·3 years (SD 16·2). 66 265 (26·9%) of 246 695 individuals were female, 180 430 (73·1%) were male, and 189 035 (90·9%) of 208 050 individuals with available ethnicity data were White. Incident gout diagnoses decreased by 30·9% in the year beginning March, 2020, compared with the preceding year (1·23 diagnoses vs 1·78 diagnoses per 1000 adults). Gout prevalence was 3·07% in 2015–16, and 3·21% in 2022–23. Gout hospitalisations decreased by 30·1% in the year commencing March, 2020, compared with the preceding year (9·6 admissions vs 13·7 admissions per 100 000 adults). Of 228 095 people with incident gout and available follow-up, 66 560 (29·2%) were prescribed urate-lowering therapy within 6 months. Of 65 305 individuals who initiated urate-lowering therapy with available follow-up, 16 790 (25·7%) attained a serum urate concentration of 360 μmol/L or less within 6 months of urate-lowering therapy initiation. In interrupted time-series analyses, urate-lowering therapy prescribing improved modestly during the pandemic, compared with pre-pandemic, whereas urate target attainment was similar. Interpretation: Using gout as an exemplar disease, we showed the complexity of how health care was impacted during the COVID-19 pandemic. We observed a reduction in gout diagnoses but no effect on treatment metrics. We showed how country-wide, routinely collected data can be used to map disease epidemiology and monitor care quality. Funding: None.
UR - http://www.scopus.com/inward/record.url?scp=85171741428&partnerID=8YFLogxK
U2 - 10.1016/S2665-9913(23)00206-0
DO - 10.1016/S2665-9913(23)00206-0
M3 - Article
AN - SCOPUS:85171741428
SN - 2665-9913
VL - 5
SP - e622-e632
JO - The Lancet Rheumatology
JF - The Lancet Rheumatology
IS - 10
ER -