scholarly journals The Expanded Risk Score in Rheumatoid Arthritis (ERS-RA): performance of a disease-specific calculator in comparison with the traditional prediction scores in the assessment of the 10-year risk of cardiovascular disease in patients with rheumatoid arthrit

2018 ◽  
Author(s):  
Fausto Salaffi ◽  
Marina Carotti ◽  
Marco Di Carlo ◽  
Marika Tardella ◽  
Valentina Lato ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Disease ◽  
Risk Score ◽  
Disease Specific

THU0107 Improving the Prediction of 10-Year Risk of Cardiovascular Disease using Traditional and Disease-Specific Predictors in Patients with Rheumatoid Arthritis

2015 ◽  
Vol 74 (Suppl 2) ◽  
pp. 232.1-232
Author(s):  
M. Schulpen ◽  
G.C. Puts ◽  
E. Arts ◽  
A.A. den Broeder ◽  
C.D. Popa ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Disease ◽  
Disease Specific

scholarly journals Derivation and internal validation of a multi-biomarker-based cardiovascular disease risk prediction score for rheumatoid arthritis patients

2020 ◽  
Vol 22 (1) ◽  
Author(s):  
Jeffrey R. Curtis ◽  
Fenglong Xie ◽  
Cynthia S. Crowson ◽  
Eric H. Sasso ◽  
Elena Hitraya ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Disease ◽  
Risk Prediction ◽  
Tobacco Use ◽  
Risk Score ◽  
Cvd Risk ◽  
Internal Validation ◽  
Clinical Model ◽  
History Of ◽  
Clinical Models

Abstract Background Rheumatoid arthritis (RA) patients have increased risk for cardiovascular disease (CVD). Accurate CVD risk prediction could improve care for RA patients. Our goal is to develop and validate a biomarker-based model for predicting CVD risk in RA patients. Methods Medicare claims data were linked to multi-biomarker disease activity (MBDA) test results to create an RA patient cohort with age ≥ 40 years that was split 2:1 for training and internal validation. Clinical and RA-related variables, MBDA score, and its 12 biomarkers were evaluated as predictors of a composite CVD outcome: myocardial infarction (MI), stroke, or fatal CVD within 3 years. Model building used Cox proportional hazard regression with backward elimination. The final MBDA-based CVD risk score was internally validated and compared to four clinical CVD risk prediction models. Results 30,751 RA patients (904 CVD events) were analyzed. Covariates in the final MBDA-based CVD risk score were age, diabetes, hypertension, tobacco use, history of CVD (excluding MI/stroke), MBDA score, leptin, MMP-3 and TNF-R1. In internal validation, the MBDA-based CVD risk score was a strong predictor of 3-year risk for a CVD event, with hazard ratio (95% CI) of 2.89 (2.46–3.41). The predicted 3-year CVD risk was low for 9.4% of patients, borderline for 10.2%, intermediate for 52.2%, and high for 28.2%. Model fit was good, with mean predicted versus observed 3-year CVD risks of 4.5% versus 4.4%. The MBDA-based CVD risk score significantly improved risk discrimination by the likelihood ratio test, compared to four clinical models. The risk score also improved prediction, reclassifying 42% of patients versus the simplest clinical model (age + sex), with a net reclassification index (NRI) (95% CI) of 0.19 (0.10–0.27); and 28% of patients versus the most comprehensive clinical model (age + sex + diabetes + hypertension + tobacco use + history of CVD + CRP), with an NRI of 0.07 (0.001–0.13). C-index was 0.715 versus 0.661 to 0.696 for the four clinical models. Conclusion A prognostic score has been developed to predict 3-year CVD risk for RA patients by using clinical data, three serum biomarkers and the MBDA score. In internal validation, it had good accuracy and outperformed clinical models with and without CRP. The MBDA-based CVD risk prediction score may improve RA patient care by offering a risk stratification tool that incorporates the effect of RA inflammation.

scholarly journals Cardiovascular disease risk calculators to reflect the subclinical atherosclerosis of coronary artery in rheumatoid arthritis: a pilot study

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Se Hee Kim ◽  
Sang-Heon Lee ◽  
Hae-Rim Kim ◽  
Hong Ki Min
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Disease ◽  
Regression Analysis ◽  
Coronary Artery ◽  
Linear Regression ◽  
Risk Score ◽  
Subclinical Atherosclerosis ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression Analysis ◽  
Cvd Risk

Abstract Background Cardiovascular diseases (CVDs) are the leading cause of death in patients with rheumatoid arthritis (RA). Coronary artery calcium (CAC) score quantifies the severity of atherosclerosis. We estimated CVD risk using several methods and compared these with the CAC score to identify the most suitable CVD risk calculator in RA patients. Methods We recruited RA patients, and the 10-year CVD risk was assessed using various tools, viz. Framingham risk score, Systemic Coronary Risk Evaluation (SCORE), Atherosclerotic Cardiovascular Disease (ASCVD) risk estimator plus, QRISK3, Expanded Risk Score in Rheumatoid Arthritis (ERS-RA), and Reynolds risk score. Computed tomography was used to determine the CAC score of each patient. Correlation analysis and linear regression analysis between the CAC score and CVD risk score was performed. Results In total, 54 RA patients were enrolled. ERS-RA showed the highest correlation coefficient (r = 0.430, P = 0.001). In multivariate linear regression analysis, ERS-RA (β = 10.01, 95% confidence interval 3.78–16.23) showed a positive association with the CAC score in RA patients. Conclusions The ERS-RA method was highly correlated with the CAC score in RA patients. Therefore, the application of the ERS-RA method may be suitable for predicting subclinical atherosclerosis and CVD risk in RA patients.

scholarly journals Plasma expression of microRNA-425-5p and microRNA-451a as biomarkers of cardiovascular disease in rheumatoid arthritis patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Delia Taverner ◽  
Dídac Llop ◽  
Roser Rosales ◽  
Raimon Ferré ◽  
Luis Masana ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Disease ◽  
Pulse Wave Velocity ◽  
Wave Velocity ◽  
Pulse Wave ◽  
Disease Risk ◽  
Intima Media Thickness ◽  
Carotid Intima Media Thickness ◽  
Media Thickness ◽  
Epigenetic Biomarkers

AbstractTo validate in a cohort of 214 rheumatoid arthritis patients a panel of 10 plasmatic microRNAs, which we previously identified and that can facilitate earlier diagnosis of cardiovascular disease in rheumatoid arthritis patients. We identified 10 plasma miRs that were downregulated in male rheumatoid arthritis patients and in patients with acute myocardial infarction compared to controls suggesting that these microRNAs could be epigenetic biomarkers for cardiovascular disease in rheumatoid arthritis patients. Six of those microRNAs were validated in independent plasma samples from 214 rheumatoid arthritis patients and levels of expression were associated with surrogate markers of cardiovascular disease (carotid intima-media thickness, plaque formation, pulse wave velocity and distensibility) and with prior cardiovascular disease. Multivariate analyses adjusted for traditional confounders and treatments showed that decreased expression of microRNA-425-5p in men and decreased expression of microRNA-451 in women were significantly associated with increased (β = 0.072; p = 0.017) and decreased carotid intima-media thickness (β = −0.05; p = 0.013), respectively. MicroRNA-425-5p and microRNA-451 also increased the accuracy to discriminate patients with pathological carotid intima-media thickness by 1.8% (p = 0.036) in men and 3.5% (p = 0.027) in women, respectively. In addition, microRNA-425-5p increased the accuracy to discriminate male patients with prior cardiovascular disease by 3% (p = 0.008). Additionally, decreased expression of microRNA-451 was significantly associated with decreased pulse wave velocity (β = −0.72; p = 0.035) in overall rheumatoid arthritis population. Distensibility showed no significant association with expression levels of the microRNAs studied. We provide evidence of a possible role of microRNA-425-5p and microRNA-451 as useful epigenetic biomarkers to assess cardiovascular disease risk in patients with rheumatoid arthritis.

Advanced cardiometabolic & inflammatory markers for prediction of cardiovascular disease and cancer

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Radenkovic ◽  
S.C Chawla ◽  
G Botta ◽  
A Boli ◽  
M.B Banach ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Score ◽  
Cancer Incidence ◽  
Risk Function ◽  
Patient Characteristics ◽  
Risk Scores ◽  
Uk Biobank ◽  
Training Set ◽  
All Cause Mortality ◽  
The Uk

Abstract   The two leading causes of mortality worldwide are cardiovascular disease (CVD) and cancer. The annual total cost of CVD and cancer is an estimated $844.4 billion in the US and is projected to double by 2030. Thus, there has been an increased shift to preventive medicine to improve health outcomes and development of risk scores, which allow early identification of individuals at risk to target personalised interventions and prevent disease. Our aim was to define a Risk Score R(x) which, given the baseline characteristics of a given individual, outputs the relative risk for composite CVD, cancer incidence and all-cause mortality. A non-linear model was used to calculate risk scores based on the participants of the UK Biobank (= 502548). The model used parameters including patient characteristics (age, sex, ethnicity), baseline conditions, lifestyle factors of diet and physical activity, blood pressure, metabolic markers and advanced lipid variables, including ApoA and ApoB and lipoprotein(a), as input. The risk score was defined by normalising the risk function by a fixed value, the average risk of the training set. To fit the non-linear model >400,000 participants were used as training set and >45,000 participants were used as test set for validation. The exponent of risk function was represented as a multilayer neural network. This allowed capturing interdependent behaviour of covariates, training a single model for all outcomes, and preserving heterogeneity of the groups, which is in contrast to CoxPH models which are traditionally used in risk scores and require homogeneous groups. The model was trained over 60 epochs and predictive performance was determined by the C-index with standard errors and confidence intervals estimated with bootstrap sampling. By inputing the variables described, one can obtain personalised hazard ratios for 3 major outcomes of CVD, cancer and all-cause mortality. Therefore, an individual with a risk Score of e.g. 1.5, at any time he/she has 50% more chances than average of experiencing the corresponding event. The proposed model showed the following discrimination, for risk of CVD (C-index = 0.8006), cancer incidence (C-index = 0.6907), and all-cause mortality (C-index = 0.7770) on the validation set. The CVD model is particularly strong (C-index >0.8) and is an improvement on a previous CVD risk prediction model also based on classical risk factors with total cholesterol and HDL-c on the UK Biobank data (C-index = 0.7444) published last year (Welsh et al. 2019). Unlike classically-used CoxPH models, our model considers correlation of variables as shown by the table of the values of correlation in Figure 1. This is an accurate model that is based on the most comprehensive set of patient characteristics and biomarkers, allowing clinicians to identify multiple targets for improvement and practice active preventive cardiology in the era of precision medicine. Figure 1. Correlation of variables in the R(x) Funding Acknowledgement Type of funding source: None

scholarly journals Cardiovascular Disease in Rheumatoid Arthritis: Risk Factors, Autoantibodies, and the Effect of Antirheumatic Therapies

2021 ◽  
Vol 14 ◽  
pp. 117954412110287
Author(s):  
Mir Sohail Fazeli ◽  
Vadim Khaychuk ◽  
Keith Wittstock ◽  
Boris Breznen ◽  
Grace Crocket ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Cardiovascular Disease ◽  
Literature Review ◽  
Rheumatoid Factor ◽  
Qualitative Evidence Synthesis ◽  
Cvd Risk ◽  
Rheumatoid Arthritis Risk ◽  
Published Evidence ◽  
Increased Risk

Objective: To scope the current published evidence on cardiovascular risk factors in rheumatoid arthritis (RA) focusing on the role of autoantibodies and the effect of antirheumatic agents. Methods: Two reviews were conducted in parallel: A targeted literature review (TLR) describing the risk factors associated with cardiovascular disease (CVD) in RA patients; and a systematic literature review (SLR) identifying and characterizing the association between autoantibody status and CVD risk in RA. A narrative synthesis of the evidence was carried out. Results: A total of 69 publications (49 in the TLR and 20 in the SLR) were included in the qualitative evidence synthesis. The most prevalent topic related to CVD risks in RA was inflammation as a shared mechanism behind both RA morbidity and atherosclerotic processes. Published evidence indicated that most of RA patients already had significant CV pathologies at the time of diagnosis, suggesting subclinical CVD may be developing before patients become symptomatic. Four types of autoantibodies (rheumatoid factor, anti-citrullinated peptide antibodies, anti-phospholipid autoantibodies, anti-lipoprotein autoantibodies) showed increased risk of specific cardiovascular events, such as higher risk of cardiovascular death in rheumatoid factor positive patients and higher risk of thrombosis in anti-phospholipid autoantibody positive patients. Conclusion: Autoantibodies appear to increase CVD risk; however, the magnitude of the increase and the types of CVD outcomes affected are still unclear. Prospective studies with larger populations are required to further understand and quantify the association, including the causal pathway, between specific risk factors and CVD outcomes in RA patients.

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