scholarly journals Performance of the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis in a geographically distant National Register-based cohort: an external validation

RMD Open ◽  
2018 ◽  
Vol 4 (2) ◽  
pp. e000771 ◽  
Author(s):  
Lotta Ljung ◽  
Peter Ueda ◽  
Katherine P Liao ◽  
Jeffrey D Greenberg ◽  
Carol J Etzel ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Risk ◽  
Risk Stratification ◽  
Risk Prediction ◽  
External Validation ◽  
Risk Groups ◽  
Prediction Score ◽  
Swedish Population ◽  
Quality Register ◽  
Cardiovascular Risk Prediction

BackgroundCardiovascular (CV) risk stratification for patients with rheumatoid arthritis (RA) should facilitate evidence-based management. Prior work has derived an internally validated a CV risk score, the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis (ERS-RA), using US data. The aim of this study was to perform an external validation among unselected patients with RA from Europe.MethodsThree large, partially overlapping, cohorts of patients with RA from the Swedish Rheumatology Quality register were identified for external validation, two with information on smoking and two with close to 10 years of median follow-up. The 10 -year rate of first CV events was assessed using the Kaplan-Meier method. The performance of ERS-RA was assessed using C-index and comparisons of observed versus predicted risks.ResultsThe C-index for ERS-RA varied across the three RA cohorts, from 0.75 to 0.78. Predicted risks corresponded well to observed risks among individuals with ≤10 % observed 10- year CV risk, but underestimated risk in individuals with a higher observed risk. In the absence of data on smoking, ERS-RA underestimated the CV risk by 3.3%, whereas in the cohorts including data on smoking, the calibration was within 1% (0.06% and 0.7%). In the clinically relevant risk intervals (<5%, 5.0%–<7.5%, 7.5%–<10%), ERS-RA performed well.ConclusionsIn an unselected Swedish population with RA, ERS-RA performed well, although the 10-year CV risk was underestimated in high-risk groups and in the absence of data on smoking. ERS-RA could be considered as a risk stratification tool for targeted preventive interventions in clinical rheumatology practice.

Performance of the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis Is Not Superior to the ACC/AHA Risk Calculator

2018 ◽  
Vol 46 (2) ◽  
pp. 130-137 ◽  
Author(s):  
Bengt Wahlin ◽  
Lena Innala ◽  
Staffan Magnusson ◽  
Bozena Möller ◽  
Torgny Smedby ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Risk ◽  
General Population ◽  
Risk Prediction ◽  
Blood Lipids ◽  
Heart Association ◽  
Prediction Score ◽  
Risk Calculator ◽  
Cardiovascular Risk Prediction ◽  
Better Than

Objective.Cardiovascular (CV) risk estimation calculators for the general population do not perform well in patients with rheumatoid arthritis (RA). An RA-specific risk calculator has been developed, but did not perform better than a risk calculator for the general population when validated in a heterogeneous multinational cohort.Methods.In a cohort of patients with new-onset RA from northern Sweden (n = 665), the risk of CV disease was estimated by the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis (ERS-RA) and the American College of Cardiology/American Heart Association algorithm (ACC/AHA). The ACC/AHA estimation was analyzed, both as crude data and when adjusted according to the recommendations by the European League Against Rheumatism (ACC/AHA × 1.5). ERS-RA was calculated using 2 variants: 1 from patient and physician reports of hypertension (HTN) and hyperlipidemia [ERS-RA (reported)] and 1 from assessments of blood pressure (BP) and blood lipids [ERS-RA (measured)]. The estimations were compared with observed CV events.Results.All variants of risk calculators underestimated the CV risk. Discrimination was good for all risk calculators studied. Performance of all risk calculators was poorer in patients with a high grade of inflammation, whereas ACC/AHA × 1.5 performed best in the high-inflammatory patients. In those patients with an estimated risk of 5–15%, no risk calculator performed well.Conclusion.ERS-RA underestimated the risk of a CV event in our cohort of patients, especially when risk estimations were based on patient or physician reports of HTN and hyperlipidemia instead of assessment of BP and blood lipids. The performance of ERS-RA was no better than that of ACC/AHA × 1.5, and neither performed well in high-inflammatory patients.

scholarly journals Does coronary calcium scoring adds value to cardiovascular risk prediction in asymptomatic population?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Serrao ◽  
M Temtem ◽  
A Pereira ◽  
J Monteiro ◽  
M Santos ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Cardiovascular Risk ◽  
Risk Stratification ◽  
Risk Prediction ◽  
Cardiovascular Events ◽  
Cardiovascular Risk Prediction ◽  
Traditional Risk Factors ◽  
The Impact

Abstract Background Despite being a controversial subject, multiple guidelines mention the use of Coronary Artery Calcification (CAC) scoring in the cardiovascular risk prediction, in asymptomatic population. The inclusion of CAC scoring in traditional risk models may help in decision-make providing better cardiovascular risk stratification. Purpose The aim of our study is to estimate the impact of CAC scoring in cardiovascular events risk prediction in a model based on traditional risk factors (TRFs). Methods and results The study consisted of 1052 asymptomatic individuals free of known coronary heart disease, enrolled from GENEMACOR study and referred for computed tomography for the CAC scoring assessment. A cohort of 952 was followed for a mean of 5.2±3.2 years for the primary endpoint of all-cause of cardiovascular events. The following traditional risk factors were considered: (1) current cigarette smoking, (2) dyslipidemia, (3) diabetes mellitus, (4) hypertension and (5) family history of coronary heart disease. Among this population, the extent of CAC differs significantly between men and women in the same age group. Therefore, the distribution of CAC score by age and gender was done by using the Hoff's nomogram (a). According to this nomogram, 3 categories were created: low CAC (0≤CAC&lt;100 and P&lt;50); moderate CAC (100≤CAC&lt;400 or P50–75) and high CAC (CAC≥400 or P&gt;75). Two Cox regression models were created, the first only with TRFs and the second adding the CAC severity categories. When including CAC categories to the TRFs, the higher severity level presented a significant risk of MACE occurrence with an HR of 4.39 (95% CI 1.83–10.52; p=0.001). Conclusion Our results point to the importance of the inclusion of CAC in both primary and secondary prevention to an improved risk stratification. Larger prospective multicentre cohorts with longer follow-up should reproduce and validate these findings. Funding Acknowledgement Type of funding source: None

scholarly journals External validation and comparison of four cardiovascular risk prediction models with data from the Australian Diabetes, Obesity and Lifestyle study

2019 ◽  
Vol 210 (4) ◽  
pp. 161-167 ◽  
Author(s):  
Loai Albarqouni ◽  
Jennifer A Doust ◽  
Dianna Magliano ◽  
Elizabeth LM Barr ◽  
Jonathan E Shaw ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Risk Prediction Models ◽  
Cardiovascular Risk Prediction

Predictive Utility of Cardiovascular Risk Prediction Algorithms in Inflammatory Rheumatic Diseases: A Systematic Review

2019 ◽  
Vol 47 (6) ◽  
pp. 928-938 ◽  
Author(s):  
Keith Colaco ◽  
Vanessa Ocampo ◽  
Ana Patricia Ayala ◽  
Paula Harvey ◽  
Dafna D. Gladman ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Systematic Review ◽  
Cardiovascular Risk ◽  
Risk Prediction ◽  
Rheumatic Diseases ◽  
Risk Score ◽  
Predictive Performance ◽  
Inflammatory Rheumatic Diseases ◽  
Prediction Algorithms ◽  
Cardiovascular Risk Prediction

Objective.We performed a systematic review of the literature to describe current knowledge of cardiovascular (CV) risk prediction algorithms in rheumatic diseases.Methods.A systematic search of MEDLINE, EMBASE, and Cochrane Central databases was performed. The search was restricted to original publications in English, had to include clinical CV events as study outcomes, assess the predictive properties of at least 1 CV risk prediction algorithm, and include patients with rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), psoriatic arthritis (PsA), or psoriasis. By design, only cohort studies that followed participants for CV events were selected.Results.Eleven of 146 identified manuscripts were included. Studies evaluated the predictive performance of the Framingham Risk Score, QRISK2, Systematic Coronary Risk Evaluation (SCORE), Reynolds Risk Score, American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE), Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis (ERS-RA), and the Italian Progetto CUORE score. Approaches to improve predictive performance of general risk algorithms in patients with RA included the use of multipliers, biomarkers, disease-specific variables, or a combination of these to modify or develop an algorithm. In both SLE and PsA patients, multipliers were applied to general risk algorithms. In studies of RA and SLE patients, efforts to include nontraditional risk factors, disease-related variables, multipliers, and biomarkers largely failed to substantially improve risk estimates.Conclusion.Our study confirmed that general risk algorithms mostly underestimate and at times overestimate CV risk in rheumatic patients. We did not find studies that evaluated models for psoriasis or AS, which further demonstrates a need for research in these populations.

Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms

2015 ◽  
Vol 75 (4) ◽  
pp. 674-680 ◽  
Author(s):  
E E A Arts ◽  
C D Popa ◽  
A A Den Broeder ◽  
R Donders ◽  
A Sandoo ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Prediction ◽  
Risk Estimation ◽  
External Validation ◽  
Predictive Performance ◽  
Risk Groups ◽  
Cvd Risk ◽  
Risk Algorithm ◽  
Lemeshow Test ◽  
First Time

ObjectivesPredictive performance of cardiovascular disease (CVD) risk calculators appears suboptimal in rheumatoid arthritis (RA). A disease-specific CVD risk algorithm may improve CVD risk prediction in RA. The objectives of this study are to adapt the Systematic COronary Risk Evaluation (SCORE) algorithm with determinants of CVD risk in RA and to assess the accuracy of CVD risk prediction calculated with the adapted SCORE algorithm.MethodsData from the Nijmegen early RA inception cohort were used. The primary outcome was first CVD events. The SCORE algorithm was recalibrated by reweighing included traditional CVD risk factors and adapted by adding other potential predictors of CVD. Predictive performance of the recalibrated and adapted SCORE algorithms was assessed and the adapted SCORE was externally validated.ResultsOf the 1016 included patients with RA, 103 patients experienced a CVD event. Discriminatory ability was comparable across the original, recalibrated and adapted SCORE algorithms. The Hosmer–Lemeshow test results indicated that all three algorithms provided poor model fit (p<0.05) for the Nijmegen and external validation cohort. The adapted SCORE algorithm mainly improves CVD risk estimation in non-event cases and does not show a clear advantage in reclassifying patients with RA who develop CVD (event cases) into more appropriate risk groups.ConclusionsThis study demonstrates for the first time that adaptations of the SCORE algorithm do not provide sufficient improvement in risk prediction of future CVD in RA to serve as an appropriate alternative to the original SCORE. Risk assessment using the original SCORE algorithm may underestimate CVD risk in patients with RA.

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