4.7 Article

Assessment of QRISK3 as a predictor of cardiovascular disease events in type 2 diabetes mellitus

Journal

FRONTIERS IN ENDOCRINOLOGY
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fendo.2022.1077632

Keywords

cardiovascular disease; type 2 diabetes mellitus (DM); risk score; QRESEARCH risk estimator version 3 (QRISK3); framingham risk score (FRS)

Funding

  1. National Natural Science Foundation of China
  2. Changzhou Sci Tech Program
  3. [82000684]
  4. [CJ20200025]

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This study compared the performance of QRISK3 and FRS as cardiovascular disease (CVD) risk assessment tools in T2DM patients and found that QRISK3 was able to comprehensively and accurately predict the risk of CVD events in these patients compared to FRS. However, larger studies are needed to further validate the predictive ability of QRISK3.
BackgroundThe risk of cardiovascular disease (CVD) in diabetes mellitus (DM) patients is two- to three-fold higher than in the general population. We designed a 10-year cohort trial in T2DM patients to explore the performance of QRESEARCH risk estimator version 3 (QRISK3) as a CVD risk assessment tool and compared to Framingham Risk Score (FRS). MethodThis is a single-center analysis of prospective data collected from 566 newly-diagnosed patients with type 2 DM (T2DM). The risk scores were compared to CVD development in patients with and without CVD. The risk variables of CVD were identified using univariate analysis and multivariate cox regression analysis. The number of patients classified as low risk (<10%), intermediate risk (10%-20%), and high risk (>20%) for two tools were identified and compared, as well as their sensitivity, specificity, positive and negative predictive values, and consistency (C) statistics analysis. ResultsAmong the 566 individuals identified in our cohort, there were 138 (24.4%) CVD episodes. QRISK3 classified most CVD patients as high risk, with 91 (65.9%) patients. QRISK3 had a high sensitivity of 91.3% on a 10% cut-off dichotomy, but a higher specificity of 90.7% on a 20% cut-off dichotomy. With a 10% cut-off dichotomy, FRS had a higher specificity of 89.1%, but a higher sensitivity of 80.1% on a 20% cut-off dichotomy. Regardless of the cut-off dichotomy approach, the C-statistics of QRISK3 were higher than those of FRS. ConclusionQRISK3 comprehensively and accurately predicted the risk of CVD events in T2DM patients, superior to FRS. In the future, we need to conduct a large-scale T2DM cohort study to verify further the ability of QRISK3 to predict CVD events.

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