Joanna C Robson1, Amit Kiran1, Joe Maskell1, Andrew Hutchings1, Nigel Arden1, Bhaskar Dasgupta1, William Hamilton1, Akan Emin1, David Culliford1, Raashid Luqmani1. 1. From the Faculty of Health and Applied Sciences, University of the West of England; School of Clinical Sciences at South Bristol, University of Bristol; Rheumatology, University Hospitals Bristol National Health Service (NHS) Trust, Bristol; Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Rheumatology Department, Nuffield Orthopaedic Centre, Oxford; Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton; Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine Room; Clinical Effectiveness Unit, The Royal College of Surgeons of England, London; Southend University Hospital NHS Trust, Essex; University of Exeter Medical School, Exeter, UK.J.C. Robson, MBBS, PhD, MRCP, Consultant Senior Lecturer in Rheumatology, Faculty of Health and Applied Sciences, University of the West of England, Bristol, and Honorary Senior Lecturer, School of Clinical Sciences at South Bristol, University of Bristol, and Honorary Consultant in Rheumatology, University Hospitals Bristol NHS Trust; A. Kiran, PhD, Statistician, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Nuffield Orthopaedic Centre; J. Maskell, BSc, Data Manager, Faculty of Medicine, University of Southampton, Southampton General Hospital; A. Hutchings, MSc, Lecturer, Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine Room; N. Arden, MBBS, FRCP, MSc, MD, Professor of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Nuffield Orthopaedic Centre; B. Dasgupta, MBBS, MD, FRCP, Professor of Rheumatology, Southend University Hospital NHS Trust; W. Hamilton, MD, FRCP, FRCGP, Professor of Primary Care Diagnostics, University of Exeter Medical School; A. Emin, BSc, MSc, MBBS, MRCS, UK Cardiothoracic Transplant Research Fellow, Clinical Effectivene
Abstract
OBJECTIVE: To evaluate the risk of cerebrovascular disease and cardiovascular disease (CVD) in patients with giant cell arteritis (GCA), and to identify predictors. METHODS: The UK Clinical Practice Research Datalink 1991-2010 was used for a parallel cohort study of 5827 patients with GCA and 37,090 age-, sex-, and location-matched controls. A multivariable competing risk model (non-cerebrovascular/CV-related death as the competing risk) determined the relative risk [subhazard ratio (SHR)] between patients with GCA compared with background controls for cerebrovascular disease, CVD, or either. Each cohort (GCA and controls) was then analyzed individually using the same multivariable model, with age and sex now present, to identify predictors of CVD or cerebrovascular disease. RESULTS: Patients with GCA, compared with controls, had an increased risk SHR (95% CI) of cerebrovascular disease (1.45, 1.31-1.60), CVD (1.49, 1.37-1.62), or either (1.47, 1.37-1.57). In the GCA cohort, predictors of "cerebrovascular disease or CVD" included increasing age, > 80 years versus < 65 years (1.98, 1.62-2.42), male sex (1.20, 1.05-1.38), and socioeconomic status, most deprived quintile versus least deprived (1.34, 1.01-1.78). These predictors were also present within the non-GCA cohort. CONCLUSION: Patients with GCA are more likely to develop cerebrovascular disease or CVD than age-, sex-, and location-matched controls. In common with the non-GCA cohort, patients who are older, male, and from the most deprived compared with least deprived areas have a higher risk of cerebrovascular disease or CVD. Further work is needed to understand how this risk may be mediated by specific behavioral, social, and economic factors.
OBJECTIVE: To evaluate the risk of cerebrovascular disease and cardiovascular disease (CVD) in patients with giant cell arteritis (GCA), and to identify predictors. METHODS: The UK Clinical Practice Research Datalink 1991-2010 was used for a parallel cohort study of 5827 patients with GCA and 37,090 age-, sex-, and location-matched controls. A multivariable competing risk model (non-cerebrovascular/CV-related death as the competing risk) determined the relative risk [subhazard ratio (SHR)] between patients with GCA compared with background controls for cerebrovascular disease, CVD, or either. Each cohort (GCA and controls) was then analyzed individually using the same multivariable model, with age and sex now present, to identify predictors of CVD or cerebrovascular disease. RESULTS: Patients with GCA, compared with controls, had an increased risk SHR (95% CI) of cerebrovascular disease (1.45, 1.31-1.60), CVD (1.49, 1.37-1.62), or either (1.47, 1.37-1.57). In the GCA cohort, predictors of "cerebrovascular disease or CVD" included increasing age, > 80 years versus < 65 years (1.98, 1.62-2.42), male sex (1.20, 1.05-1.38), and socioeconomic status, most deprived quintile versus least deprived (1.34, 1.01-1.78). These predictors were also present within the non-GCA cohort. CONCLUSION: Patients with GCA are more likely to develop cerebrovascular disease or CVD than age-, sex-, and location-matched controls. In common with the non-GCA cohort, patients who are older, male, and from the most deprived compared with least deprived areas have a higher risk of cerebrovascular disease or CVD. Further work is needed to understand how this risk may be mediated by specific behavioral, social, and economic factors.
Authors: Max Yates; Robert Luben; Shabina Hayat; Sarah L Mackie; Richard A Watts; Kay-Tee Khaw; Nick J Wareham; Alex J MacGregor Journal: Rheumatology (Oxford) Date: 2020-02-01 Impact factor: 7.580