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The predictive accuracy of cardiovascular risk prediction tools in inflammatory arthritis and psoriasis: an observational validation study using the Clinical Practice Research Datalink.
Hughes, David M; Coronado, Jose Ignacio Cuitun; Schofield, Pieta; Yiu, Zenas Z N; Zhao, Sizheng Steven.
Afiliação
  • Hughes DM; Department of Health Data Science, University of Liverpool, Liverpool, UK.
  • Coronado JIC; Department of Population Health Sciences, University of Bristol, Bristol, UK.
  • Schofield P; Institute of Population Health, University of Liverpool, Liverpool, UK.
  • Yiu ZZN; Centre for Dermatology Research, Northern Care Alliance NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, National Institute for Health and Care Research Manchester Biomedical Research Centre, Manchester, UK.
  • Zhao SS; Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Science, School of Biological Sciences, Faculty of Biological Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Article em En | MEDLINE | ID: mdl-37966910
ABSTRACT

OBJECTIVES:

Cardiovascular risk prediction tools developed for the general population often underperform for individuals with rheumatoid arthritis (RA), and their predictive accuracy are unclear for other inflammatory conditions that also have increased cardiovascular risk. We investigated performance of QRISK-3, Framingham Risk Score (FRS) and Reynolds Risk Score (RRS) in RA, psoriatic disease (psoriatic arthritis (PsA) and psoriasis) and ankylosing spondylitis (AS). We considered osteoarthritis as a non-inflammatory comparator.

METHODS:

We utilised primary care records from the Clinical Practice Research Datalink (CPRD) Aurum database to identify individuals with each condition and calculated 10-year cardiovascular risk using each prediction tool. Discrimination and calibration of each tool in each disease was assessed.

RESULTS:

Time-dependent AUC for QRISK3 was 0.752 for RA (95% CI 0.734-0.777), 0.794 for AS (95% CI 0.764-0.812), 0.764 for PsA (95% CI 0.741-0.791),0.815 for psoriasis (95% CI 0.789-0.835), and 0.698 for osteoarthritis (95% CI 0.670-0.717) indicating reasonably good predictive performance. AUC for FRS were similar, and slightly lower for RRS. FRS was reasonably well calibrated for each condition but underpredicted risk for patients with RA. RRS tended to underpredict CVD risk, whilst QRISK3 overpredicted CVD risk, especially for the most high-risk individuals.

CONCLUSIONS:

CVD risk for individuals with RA, AS and psoriatic disease were generally less accurately predicted using each of the 3 CVD risk prediction tools than reported accuracies in the original publications. Individuals with osteoarthritis also had less accurate predictions suggesting inflammation is not the sole reason for underperformance. Disease specific risk prediction tools may be required.
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Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Idioma: En Revista: Rheumatology (Oxford) Assunto da revista: REUMATOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Idioma: En Revista: Rheumatology (Oxford) Assunto da revista: REUMATOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido