Biomarkers for Atherosclerotic Cardiovascular Events in Rheumatoid Arthritis: Towards Validation of a...

Area of Science:

• Rheumatology
• Cardiology
• Biomarker Discovery

Background:

• Rheumatoid arthritis (RA) significantly increases cardiovascular (CV) disease risk, a leading cause of mortality.
• Improved CV risk stratification in RA is crucial for effective preventative strategies and better patient outcomes.

Purpose of the Study:

• To evaluate whether specific biomarkers, when added to clinical risk factors, improve the prediction of CV events in rheumatoid arthritis patients.
• To assess the performance of novel risk models using biomarkers like high-sensitivity cardiac troponin T (hsTnT) and soluble TNF receptor 1 (sTNFR1).

Main Methods:

• A nested case-control study was conducted using an external cohort of RA patients.
• Biomarkers including hsTnT and sTNFR1 were assessed at cohort entry and analyzed using conditional logistic regression.
• Model prediction was evaluated using the area under the curve (AUC) and net reclassification index (NRI).

Main Results:

• LASSO regression identified hsTnT and sTNFR1 as significantly associated with CV events in RA patients.
• The AUC increased from 0.758 (clinical factors alone) to 0.802 after adding hsTnT and sTNFR1.
• A net reclassification index (NRI) of 16.3% indicated improved risk prediction, particularly in patients without CV events during follow-up.

Conclusions:

• Selected biomarkers (hsTnT, sTNFR1) enhance the discrimination of models predicting CV events in RA patients.
• These enhanced risk models demonstrate potential for improving clinical decision-making regarding preventative care in RA.
• Prospective validation is recommended to confirm the clinical utility of these biomarker-enhanced risk models.