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Framingham, ACC/AHA or QRISK3: which is the best in systemic lupus erythematosus cardiovascular risk estimation?

1, 2, 3, 4, 5, 6, 7, 8

 

  1. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  2. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  3. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  4. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  5. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  6. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  7. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
  8. Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy. marta.mosca@med.unipi.it

CER12291
2020 Vol.38, N°4
PI 0602, PF 0608
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PMID: 31694741 [PubMed]

Received: 01/04/2019
Accepted : 22/07/2019
In Press: 28/10/2019
Published: 28/07/2020

Abstract

OBJECTIVES:
Our objective was to compare three algorithms for cardiovascular (CV) risk estimation, namely Framingham, ACC/AHA and QRISK3, in a cohort of patients with systemic lupus erythematosus (SLE).
METHODS:
Consecutive patients with SLE according to the ACR criteria were enrolled. Traditional risk factors, ongoing therapies, comorbidities and SLE-specific evaluations were assessed. In those without previous myocardial infarction or stroke, Framingham, ACC/AHA and QRISK3 algorithms were then used to estimate the individual risk of developing a CV disease over the next 10 years.
RESULTS:
Patients eligible for CV risk estimation were 123 out of 135 enrolled. Framingham index reported a median risk score of 4.7% (IQR 9.5–2.2), considering 29 patients (23.6%) at high CV risk. ACC/AHA index showed a median risk score of 1.4% (IQR 4.5–0.7), with 17 patients (13.8%) at high-risk. QRISK3 revealed a median risk score of 6.2% (IQR 12.5–2.8), making it possible to classify 44 patients (35.8%) at high CV risk. The subgroup analysis of subjects older than 40 years confirmed the same number of high-risk patients for both Framingham and ACC/AHA, whereas QRISK3 classified 38 subjects at high CV risk.
CONCLUSIONS:
QRISK3 classifies a greater number of SLE patients at high-risk of developing CV diseases over the next 10 years in comparison with classic algorithms as Framingham and ACC/AHA. If its predictive accuracy were confirmed by longitudinal data, QRISK3 could become an important tool in the early detection of a considerable part of CV high-risk SLE patients that would be underestimated when applying classic algorithms.

Rheumatology Article