Personalizing cardiovascular risk prediction for patients with systemic lupus erythematosus

Abstract

Objective: Cardiovascular disease (CVD) risk is increased in SLE and underestimated by general population prediction algorithms. We aimed to develop a novel SLE-specific prediction tool, SLECRISK, to provide a more accurate estimate of CVD risk in SLE.

Methods: We studied patients in the Brigham and Women's Hospital SLE cohort. We collected one-year baseline data including the presence of traditional CVD factors and SLE-related features at cohort enrollment. Ten-year follow-up for the first major adverse cardiovascular event (MACE; myocardial infarction (MI), stroke, or cardiac death) began at day +1 following the baseline period (index date). ICD-9/10 codes identified MACE were adjudicated by board-certified cardiologists. Least absolute shrinkage and selection operator regression selected SLE-related variables to add to the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Risk Equations 10-year risk Cox regression model. Model fit statistics and performance (sensitivity, specificity, positive/negative predictive value, c-statistic) for predicting moderate/high 10-year risk (≥7.5 %) of MACE were assessed and compared to ACC/AHA, Framingham risk score (FRS), and modified FRS (mFRS). Optimism adjustment internal validation was performed using bootstrapping.

Results: We included 1,243 patients with 90 MACEs (46 MIs, 36 strokes, 19 cardiac deaths) over 8946.5 person-years of follow-up. SLE variables selected for the new prediction algorithm (SLECRISK) were SLE activity (remission/mild vs. moderate/severe), disease duration (years), creatinine (mg/dL), anti-dsDNA, anti-RNP, lupus anticoagulant, anti-Ro positivity, and low C4. The sensitivity for detecting moderate/high-risk (≥7.5 %) of MACE using SLECRISK was 0.74 (95 %CI: 0.65, 0.83), which was better than the sensitivity of the ACC/AHA model (0.38 (95 %CI: 0.28, 0.48)). It also identified 3.4-fold more moderate/high-risk patients than the ACC/AHA. Patients who were moderate/high-risk according to SLECRISK but not ACC/AHA, were more likely to be young women with severe SLE and few other traditional CVD risk factors. Model performance between SLECRISK, FRS, and mFRS were similar.

Conclusion: The novel SLECRISK tool is more sensitive than the ACC/AHA for predicting moderate/high 10-year risk for MACE and may be particularly useful in predicting risk for young females with severe SLE. Future external validation studies utilizing cohorts with more severe SLE are needed.

Keywords: Cardiovascular risk; Prediction; Systemic lupus erythematosus.

Fig. 1.

Study design. We identified patients with SLE based using ICD-9/10 codes and meeting the Updated 1997 American College of Rheumatology (ACR) SLE criteria without a history of major adverse cardiovascular event (MACE, myocardial infarction (MI), stroke, and cardiac death) from the electronic medical records (EMR). One-year baseline data including traditional cardiovascular disease (CVD) risk factors, demographics, and SLE-related clinical features were collected from the EMR at cohort enrollment. We allowed for a one-year extension period to collect covariate data that was missing from baseline. Ten-year follow-up for first MACE began at day +1 following the baseline period (index date). ICD-9/10 codes identified MACE adjudicated by medical record review by board-certified cardiologists.

Fig. 2.

Receiver Operating Curves (ROC) at 10 years for novel SLECRISK compared to the American College of Cardiology/American Heart Association (ACC/AHA), Framingham Risk Score (FRS), and Modified Framingham Risk Score (mFRS) prediction models.

Fig. 3.

Calibration plots for ten-year predictions for Major Adverse Cardiovascular Event (MACE). X-axis is the deciles of the American College of Cardiology/American Heart Association (ACC/AHA) (A), Framingham Risk Score (FRS) (B), and modified Framingham Risk Score (mFRS) (C) models. Y-axis is the actual probability (observed definite and probable MACE event) and predicted probability (risk score from the SLECRISK formula).