A clinical prediction model using 8 predictors estimated the absolute 3-year risk of MACE after carotid endarterectomy with a C statistic of 0.69 (95% CI 0.64-0.73).
Cohort (n=1,138)
Can a clinical prediction rule accurately estimate the absolute 3-year risk of MACE after carotid endarterectomy?
A newly developed clinical prediction model can stratify the 3-year risk of MACE after carotid endarterectomy to help optimize secondary prevention.
Effect estimate: C statistic 0.69 (95% CI 0.64-0.73)
BACKGROUND AND PURPOSE: Prognosis after carotid endarterectomy is mainly determined by the occurrence of major adverse cardiovascular events (MACEs). Optimal medical treatment to reduce risk is the mainstay of MACE prevention. The level of risk of MACE may determine the initiation and aggressiveness of medical treatment, yet a prediction rule to assess that absolute MACE risk after carotid endarterectomy is currently unavailable. METHODS: The prediction model was developed in a consecutive cohort of 1138 patients who underwent carotid endarterectomy between 2002 and 2009. Primary end point was MACE and encompassed myocardial infarction, stroke, and cardiovascular death. Fourteen potential clinical predictors were entered into a Cox proportional hazard model. After backward stepwise regression, internal validation was conducted with bootstrapping techniques to correct for overfitting. To provide an easily applicable clinical tool, a score chart was constructed, dividing patients into 4 risk groups. Model performance was assessed in terms of discrimination, calibration, and risk stratification. RESULTS: During a mean follow-up of 2.28 (± 0.95) years, 148 events occurred, corresponding to a cumulative incidence of 13%. Clinical predictors in the final model were age, history of coronary or peripheral artery disease, smoking, systolic blood pressure, use of antihypertensive drugs, clinical presentation, presence of contralateral carotid stenosis, and serum creatinine levels. Discrimination of the final model, in terms of a C statistic, was 0.69 (0.64-0.73) and calibration showed a good overall fit (Gronnesby and Borgan, P=0.39). The observed incidence of MACE in the 4 risk groups was 6%, 9%, 19%, and 35%, respectively, indicating good overall risk stratification. CONCLUSIONS: The clinical prediction model for MACE in the first 3 years after carotid endarterectomy may be used to identify high-risk patients to help optimize medical treatment and risk factor management as part of secondary prevention to increase life expectancy free from MACE. Despite our success in stratifying risk among these patients, even the lowest stratum remains at high risk and all of these patients should receive maximal secondary preventive measures.
Lammeren et al. (2012) conducted a cohort in Carotid endarterectomy (n=1,138). Clinical prediction model was evaluated on Major adverse cardiovascular events (myocardial infarction, stroke, and cardiovascular death) (C statistic 0.69, 95% CI 0.64-0.73). A clinical prediction model using 8 predictors estimated the absolute 3-year risk of MACE after carotid endarterectomy with a C statistic of 0.69 (95% CI 0.64-0.73).