External Validation of Risk Prediction Models to Improve Selection of Patients for Carotid Endarterectomy
Related Experiment Video
Updated: Oct 17, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Michiel H F Poorthuis1, Reinier A R Herings2, Kirsten Dansey3
1Department of Neurology (M.H.F.P.), University Medical Center Utrecht, the Netherlands.
Insights
The Ontario Carotid Endarterectomy Registry risk model best predicts stroke or death after carotid endarterectomy (CEA). This tool helps identify patients most likely to benefit from CEA, improving procedural safety and outcomes.
Area of Science:
- Vascular Surgery
- Medical Decision Making
- Health Outcomes Research
Background:
- Carotid endarterectomy (CEA) offers net benefit when procedural stroke or death risk is low.
- Guidelines recommend CEA for symptomatic stenosis if 30-day risks are <6% and asymptomatic stenosis if <3%.
Purpose of the Study:
- Identify and externally validate prediction models for procedural stroke or death after CEA.
- Assess the reliability of existing models in a large US patient cohort.
Main Methods:
- Systematic search of MEDLINE and EMBASE for CEA prediction models.
- External validation using 26,293 patients from the American College of Surgeons National Surgical Quality Improvement Program (2011-2017).
- Assessed model discrimination (C statistics) and calibration; identified patients exceeding risk thresholds.
Main Results:
- 17 prediction models were evaluated; 702 (2.7%) patients experienced stroke or death within 30 days.
- C statistics ranged from 0.49 to 0.64, indicating variable predictive accuracy.
- The Ontario Carotid Endarterectomy Registry model demonstrated the best performance (C statistic 0.64) and calibration.
Conclusions:
- The Ontario Carotid Endarterectomy Registry risk model provides the most reliable predictions for post-CEA stroke or death.
- This validated model can inform patient counseling on procedural risks.
- It aids in focusing CEA towards patients who stand to gain the most benefit.
Background And Purpose:
The net benefit of carotid endarterectomy (CEA) is determined partly by the risk of procedural stroke or death. Current guidelines recommend CEA if 30-day risks are <6% for symptomatic stenosis and <3% for asymptomatic stenosis. We aimed to identify prediction models for procedural stroke or death after CEA and to externally validate these models in a large registry of patients from the United States.
Methods:
We conducted a systematic search in MEDLINE and EMBASE for prediction models of procedural outcomes after CEA. We validated these models with data from patients who underwent CEA in the American College of Surgeons National Surgical Quality Improvement Program (2011-2017). We assessed discrimination using C statistics and calibration graphically. We determined the number of patients with predicted risks that exceeded recommended thresholds of procedural risks to perform CEA.
Results:
After screening 788 reports, 15 studies describing 17 prediction models were included. Nine were developed in populations including both asymptomatic and symptomatic patients, 2 in symptomatic and 5 in asymptomatic populations. In the external validation cohort of 26 293 patients who underwent CEA, 702 (2.7%) developed a stroke or died within 30-days. C statistics varied between 0.52 and 0.64 using all patients, between 0.51 and 0.59 using symptomatic patients, and between 0.49 to 0.58 using asymptomatic patients. The Ontario Carotid Endarterectomy Registry model that included symptomatic status, diabetes, heart failure, and contralateral occlusion as predictors, had C statistic of 0.64 and the best concordance between predicted and observed risks. This model identified 4.5% of symptomatic and 2.1% of asymptomatic patients with procedural risks that exceeded recommended thresholds.
Conclusions:
Of the 17 externally validated prediction models, the Ontario Carotid Endarterectomy Registry risk model had most reliable predictions of procedural stroke or death after CEA and can inform patients about procedural hazards and help focus CEA toward patients who would benefit most from it.
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