New Model Tops Others for Predicting Heart Disease in RA

WASHINGTON – A new model for estimating 10-year cardiovascular disease risk in patients with rheumatoid arthritis that draws on a combination of demographic factors, cardiovascular risk factors, and RA-related factors appears to more accurately predict risk than do currently available models.

The new model was developed based on findings from the prospective longitudinal CARRE study, Dr. Alper M. van Sijl reported at the annual meeting of the American College of Rheumatology.

In that study of 353 RA patients, 58 cardiovascular events occurred over 2,361 patient years of follow-up. The cardiovascular disease incidence was 16.4%, but existing, commonly used risk prediction models, including the Reynolds Risk Score, the Systemic Coronary Risk Evaluation (SCORE), and the Framingham Risk Score, underestimated the risk. At baseline, the SCORE and Framingham models, for example, estimated the incidence at 5.9% and 13%, respectively, said Dr. van Sijl of Jan van Breemen Research Institute, Reade, Amsterdam.

Using CARRE study information, including cardiovascular risk factors, RA-related factors, and surrogate markers of cardiovascular disease collected at baseline, predictive models using a number of variables alone or in combinations were tested. The new model for predicting risk in RA patients without prior cardiovascular disease that emerged included age, gender, use of statins and prednisone, body-mass index, diastolic blood pressure, low-density lipoprotein cholesterol, total cholesterol to high-density lipoprotein cholesterol ratio, C-reactive protein, Health Assessment Questionnaire scores, and erythrocyte sedimentation rate.

Using receiver operating curves analyses, the new model predicted cardiovascular disease incidence better than the other methods (area under the curve [AUC] 0.801 vs. 0.712), he said, noting that at a cutoff value of 10, the model had 85% sensitivity.

The findings are important because RA is associated with an increased risk of incident cardiovascular disease, which, according to the CARRE findings, has failed to decline significantly since 2000 despite the advent of effective anti-inflammatory therapies and the increased use of cardioprotective therapies. The risk is only partly explained by cardiovascular risk factors.

Additional external validation studies are needed to confirm these findings before the model can be implemented, and studies should also consider whether modification of existing risk models is necessary to improve the cardiovascular risk assessment of RA patients, he concluded.

Dr. van Sijl reported having no disclosures.

WASHINGTON – A new model for estimating 10-year cardiovascular disease risk in patients with rheumatoid arthritis that draws on a combination of demographic factors, cardiovascular risk factors, and RA-related factors appears to more accurately predict risk than do currently available models.

The new model was developed based on findings from the prospective longitudinal CARRE study, Dr. Alper M. van Sijl reported at the annual meeting of the American College of Rheumatology.

In that study of 353 RA patients, 58 cardiovascular events occurred over 2,361 patient years of follow-up. The cardiovascular disease incidence was 16.4%, but existing, commonly used risk prediction models, including the Reynolds Risk Score, the Systemic Coronary Risk Evaluation (SCORE), and the Framingham Risk Score, underestimated the risk. At baseline, the SCORE and Framingham models, for example, estimated the incidence at 5.9% and 13%, respectively, said Dr. van Sijl of Jan van Breemen Research Institute, Reade, Amsterdam.

Using CARRE study information, including cardiovascular risk factors, RA-related factors, and surrogate markers of cardiovascular disease collected at baseline, predictive models using a number of variables alone or in combinations were tested. The new model for predicting risk in RA patients without prior cardiovascular disease that emerged included age, gender, use of statins and prednisone, body-mass index, diastolic blood pressure, low-density lipoprotein cholesterol, total cholesterol to high-density lipoprotein cholesterol ratio, C-reactive protein, Health Assessment Questionnaire scores, and erythrocyte sedimentation rate.

Using receiver operating curves analyses, the new model predicted cardiovascular disease incidence better than the other methods (area under the curve [AUC] 0.801 vs. 0.712), he said, noting that at a cutoff value of 10, the model had 85% sensitivity.

The findings are important because RA is associated with an increased risk of incident cardiovascular disease, which, according to the CARRE findings, has failed to decline significantly since 2000 despite the advent of effective anti-inflammatory therapies and the increased use of cardioprotective therapies. The risk is only partly explained by cardiovascular risk factors.

Additional external validation studies are needed to confirm these findings before the model can be implemented, and studies should also consider whether modification of existing risk models is necessary to improve the cardiovascular risk assessment of RA patients, he concluded.

Dr. van Sijl reported having no disclosures.

WASHINGTON – A new model for estimating 10-year cardiovascular disease risk in patients with rheumatoid arthritis that draws on a combination of demographic factors, cardiovascular risk factors, and RA-related factors appears to more accurately predict risk than do currently available models.

The new model was developed based on findings from the prospective longitudinal CARRE study, Dr. Alper M. van Sijl reported at the annual meeting of the American College of Rheumatology.

In that study of 353 RA patients, 58 cardiovascular events occurred over 2,361 patient years of follow-up. The cardiovascular disease incidence was 16.4%, but existing, commonly used risk prediction models, including the Reynolds Risk Score, the Systemic Coronary Risk Evaluation (SCORE), and the Framingham Risk Score, underestimated the risk. At baseline, the SCORE and Framingham models, for example, estimated the incidence at 5.9% and 13%, respectively, said Dr. van Sijl of Jan van Breemen Research Institute, Reade, Amsterdam.

Using CARRE study information, including cardiovascular risk factors, RA-related factors, and surrogate markers of cardiovascular disease collected at baseline, predictive models using a number of variables alone or in combinations were tested. The new model for predicting risk in RA patients without prior cardiovascular disease that emerged included age, gender, use of statins and prednisone, body-mass index, diastolic blood pressure, low-density lipoprotein cholesterol, total cholesterol to high-density lipoprotein cholesterol ratio, C-reactive protein, Health Assessment Questionnaire scores, and erythrocyte sedimentation rate.

Using receiver operating curves analyses, the new model predicted cardiovascular disease incidence better than the other methods (area under the curve [AUC] 0.801 vs. 0.712), he said, noting that at a cutoff value of 10, the model had 85% sensitivity.

The findings are important because RA is associated with an increased risk of incident cardiovascular disease, which, according to the CARRE findings, has failed to decline significantly since 2000 despite the advent of effective anti-inflammatory therapies and the increased use of cardioprotective therapies. The risk is only partly explained by cardiovascular risk factors.

Additional external validation studies are needed to confirm these findings before the model can be implemented, and studies should also consider whether modification of existing risk models is necessary to improve the cardiovascular risk assessment of RA patients, he concluded.

Dr. van Sijl reported having no disclosures.