Which patients with asymptomatic carotid stenosis are unlikely to benefit from carotid endarterectomy?
Among 2325 veterans in this cohort study that used Veterans Administration and Medicare data, a risk prediction tool (Carotid Mortality Index) based on 23 candidate variables and a simpler model based on the number of 4 key comorbidities (any cancer, chronic obstructive pulmonary disease, congestive heart failure, and chronic kidney disease [the 4C model]) were developed to identify patients at higher risk of 5-year mortality. The models were internally validated.
Study results suggest that both the Carotid Mortality Index and the 4C model may be used to inform clinicians whether a patient will live long enough to benefit from carotid endarterectomy.
Randomized clinical trials have demonstrated that patients with asymptomatic carotid stenosis are eligible for carotid endarterectomy (CEA) if the 30-day surgical complication rate is less than 3% and the patient’s life expectancy is at least 5 years.
To develop a risk prediction tool to improve patient selection for CEA among patients with asymptomatic carotid stenosis.
Design, Setting, and Participants
In this cohort study, veterans 65 years and older who received both carotid imaging and CEA in the Veterans Administration between January 1, 2005, and December 31, 2009 (n = 2325) were followed up for 5 years. Data were analyzed from January 2005 to December 2015. A risk prediction tool (the Carotid Mortality Index [CMI]) based on 23 candidate variables identified in the literature was developed using Veterans Administration and Medicare data. A simpler model based on the number of 4 key comorbidities that were prevalent and strongly associated with 5-year mortality was also developed (any cancer in the past 5 years, chronic obstructive pulmonary disease, congestive heart failure, and chronic kidney disease [the 4C model]). Model performance was assessed using measures of discrimination (eg, area under the curve [AUC]) and calibration. Internal validation was performed by correcting for optimism using 500 bootstrapped samples.
Main Outcome and Measure
Among 2325 veterans, the mean (SD) age was 73.74 (5.92) years. The cohort was predominantly male (98.8%) and of white race/ethnicity (94.4%). Overall, 29.5% (n = 687) of patients died within 5 years of CEA. On the basis of a backward selection algorithm, 9 patient characteristics were selected (age, chronic kidney disease, diabetes, chronic obstructive pulmonary disease, any cancer diagnosis in the past 5 years, congestive heart failure, atrial fibrillation, remote stroke or transient ischemic attack, and body mass index) for the final logistic model, which yielded an optimism-corrected AUC of 0.687 for the CMI. The 4C model had slightly worse discrimination (AUC, 0.657) compared with the CMI model; however, the calibration curve was similar to the full model in most of the range of predicted probabilities.
Conclusions and Relevance
According to results of this study, use of the CMI or the simpler 4C model may improve patient selection for CEA among patients with asymptomatic carotid stenosis.
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Keyhani S, Madden E, Cheng EM, et al. Risk Prediction Tools to Improve Patient Selection for Carotid Endarterectomy Among Patients With Asymptomatic Carotid Stenosis. JAMA Surg. Published online January 09, 2019154(4):336–344. doi:10.1001/jamasurg.2018.5119
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