Neurology, University of Michigan Michigan Medicine, Ann Arbor, Michigan, USA
Neurology, University of Michigan Michigan Medicine, Ann Arbor, Michigan, USA.
Stroke Vasc Neurol. 2021 Sep;6(3):476-482. doi: 10.1136/svn-2020-000558. Epub 2021 Mar 8.
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.
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.
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).
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.
颈动脉内膜切除术（CEA）相较于颈动脉支架置入术（CAS）可降低围手术期卒中风险，但增加心肌梗死（MI）风险。我们探索了一种联合建模方法，通过基线卒中及 MI 对患者进行分层。
通过文献检索确定了围手术期卒中及 MI 的基于基线的登记风险模型。随后，我们在颈动脉血管重建术与内膜切除术（CREST）试验中通过逐步添加协变量（基线风险、治疗（CEA 与 CAS）、治疗风险交互及年龄与治疗交互项）来选择治疗风险模型。使用血管外科学会（SVS）血管质量倡议（VQI）CEA 和颈动脉支架置入登记数据对治疗风险模型进行外部验证，并将治疗模型重新校准至 SVS-VQI 人群。通过 CEA 与 CAS 相比的卒中及 MI 风险差异预测净获益。
围手术期治疗模型在 CREST 中对卒中及 MI 的预测准确性较高（卒中的 C 统计量为 0.69，MI 的 C 统计量为 0.68），且在风险谱内具有较好的校准度。在 SVS-VQI 的外部验证中，预测准确性显著降低（卒中的 C 统计量为 0.61，MI 的 C 统计量为 0.54），模型显著高估了风险。在 CREST 中，大多数患者（86.7%）预测可从 CEA 中获益（有症状患者为 97.0%，无症状患者为 75%）。
一种可分离风险因素的联合建模方法具有为最优治疗提供信息的潜力。然而，我们目前的方法还不能应用于临床。这些数据支持这样的指南建议，即对于大多数有症状颈动脉狭窄患者，CEA 应作为首选血运重建术式。
