Combined risk modelling approach to identify the optimal carotid revascularisation approach

Abstract

Background Carotid endarterectomy (CEA) results in fewer perioperative strokes, but more myocardial infarctions (MI) than carotid artery stenting (CAS). We explored a combined modelling approach that stratifies patients by baseline stroke and MI. Methods Baseline registry-based risk models for perioperative stroke and MI were identified via literature search. We then selected treatment risk models in the Carotid Revascularisation Stenting versus Endarterectomy (CREST) trial by serially adding covariates (baseline risk, treatment (CEA vs CAS), treatment-risk interaction and age-treatment interaction terms). Treatment risk models were externally validated using data from the Society for Vascular Surgery (SVS) Vascular Quality Initiative (VQI) CEA and carotid stenting registries and treatment models were recalibrated to the SVS-VQI population. Predicted net benefit was estimated by summing the predicted stroke and MI risk differences with CEA versus CAS. Results Perioperative treatment models had moderate predictiveness (c-statistic 0.69 for stroke and 0.68 for MI) and reasonable calibration across the risk spectrum for both stroke and MI within CREST. On external validation in SVS-VQI, predictiveness was substantially reduced (c-statistic 0.61 for stroke and 0.54 for MI) and models substantially overpredicted risk. Most patients (86.7%) were predicted to have net benefit from CEA in CREST (97.0% of symptomatic patients vs 75% of asymptomatic patients). Discussion A combined modelling approach that separates risk elements has potential to inform optimal treatment. However, our current approach is not ready for clinical application. These data support guidelines that suggest that CEA should be the preferred revascularisation modality in most patients with symptomatic carotid stenosis.