Comparison of different cardiovascular risk score calculators for cardiovascular risk prediction and guideline recommended statin uses

Background. CRP and family history independently associate with future cardiovascular events and have been incorporated into risk prediction models for women (the Reynolds Risk Score for women). However, no cardiovascular risk prediction algorithm incorporating these variables currently exists for men. Methods. Among 10,724 initially healthy American non-diabetic men who were followed prospectively for incident cardiovascular events over a median period of 10.8 years, we developed a cardiovascular risk prediction model that included hsCRP and parental history of myocardial infarction before age 60 years, and compared model fit, discrimination, and reclassification to prediction models limited to age, blood pressure, smoking, total cholesterol, and high-density lipoprotein cholesterol. Results. 1,294 cardiovascular events accrued during study follow-up. Predictive models incorporating hsCRP and parental history (the Reynolds Risk Score for men) had better global fit (P<0.001), a superior (lower) Bayes Information Criterion (BIC)(23008 vs 23048), and larger C-indexes (0.708 vs 0.699, P < 0.001) than did predictive models without these variables. For the endpoint of all cardiovascular events, the Reynolds Risk Score for men reclassified 17.8 percent of the study population into higher- or lower-risk categories with markedly improved accuracy among those reclassified. In models based on the ATP-III preferred endpoint of coronary heart disease and limited to men not taking lipid-lowering therapy, 16.7 percent of the study population were reclassified to higher- or lower-risk groups, again with significantly improved global fit (P<0.001), smaller BIC (13870 vs 13891), larger C-index (0.714 vs 0.704, P < 0.001), and almost perfect accuracy among those reclassified (99.9 percent). For this model, NRI was 8.4 percent and CNRI 15.8 percent (both P-values < 0.001). Conclusion. We developed an improved global risk prediction algorithm for men incorporating hsCRP and parental history that should allow better targeting of preventive therapies to maximize benefit while minimizing toxicity and cost.

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

The Journal of Rheumatology ◽

10.3899/jrheum.190261 ◽

2019 ◽

Vol 47 (6) ◽

pp. 928-938 ◽

Cited By ~ 2

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.

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AB0567 USING Q-RISK SCALE FOR CHECKING CARDIOVASCULAR RISK IN PATIENTS WITH PSORIATIC ARTHRITIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.905 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1320.2-1321

Author(s):

S. Smiyan ◽

A. Bilukha

Keyword(s):

Cardiovascular Disease ◽

Cardiovascular Risk ◽

Psoriatic Arthritis ◽

Autoimmune Diseases ◽

Risk Prediction ◽

Risk Score ◽

Diagnostic Methods ◽

Joint Involvement ◽

Cardiovascular Risk Score ◽

Risk Scale

Background:Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. In addition to skin and joint involvement, there is a growing evidence suggesting that patients with PsA also have increased risk of clinical and subclinical cardiovascular disease (CVD), mostly due to endothelial dysfunction and accelerated atherosclerosis, which are the main causes of elevated mortality rate among patients with PsA. For prevention and monitoring progression of CVD in clinical practice scale SCORE usually used, but it isn’t adapted for checking in patients with autoimmune diseases and can be used only for patients after forty years old.Objectives:To check a cardiovascular risk in patient with PsA using Q-risk scale.Methods:In total, ninety-four patients with PsA, who fulfilled the disease criteria (CASPAR) were examined using standard diagnostic methods (including C-reactive protein, lipid profile). The QRISK-3 and SCORE scales were used to assess the 10-year risk of CVD.Results:Intermediate (12.4 ± 0,75 %) risk of adverse cardiovascular events within the next 10 years was estimated for PsA patients and it was 7 to 8 – fold higher than the Q - score of a healthy age, sex, and ethnicity – matched subjects. Using classical SCORE, the risk was estimated as low (1,9±0.24 %). Healthy Heart Age was about 25 % higher than predicted as assessed by QRISK.Conclusion:The Q-risk Scale considers not only classical of such risk factors as age, sex, smoking, systolic blood pressure, total cholesterol (which used SCORE) but also index of atherogenity, BMI, family history of coronary artery disease, treatment with antihypertensive drugs and glucocorticosteroids, comorbidity, systemic inflammatory disease and can be used for different age groups and ethnicity.Q-risk scale appears to be adaptive and informative in patients with chronic inflammatory and autoimmune diseases as compared with SCORE, because it uses mostly all important etiological and trigger factors of CVD especially presence autoimmune inflammatory process in our case.References:[1]Abrar Ahmed Wagan. Cardiovascular risk score in Rheumatoid Arthritis. Pak J Med Sci, Vol. 32, Issue 3, 2016, P.534-538;[2]Frank Verhoeven, Clément Prati. Cardiovascular risk in psoriatic arthritis, a narrative review. Joint Bone Spine, Vol. 87, Issue 5, 2020, P.413-418;[3]Julia Hippisley-Cox, Carol Coupland. Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study. BMJ, Vol. 23, 2017, P.357;[4]Naveen Garg, Subrat K. Muduli. Comparison of different cardiovascular risk score calculators for cardiovascular risk prediction and guideline recommended statin uses. Indian Heart J, Vol. 69, Issue 4, 2017, P.458-463;Disclosure of Interests:None declared.

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