Analysis of Benefit of carotid endarterectomy by mathematical model

我们建立了一个马尔可夫模型来评估颈动脉内膜切除术（CEA）的有效性。在对四种健康状态进行建模时，使用来自主要随机对照试验的数据来估计过渡到另一种状态的概率。重度颈动脉狭窄的CEA治疗将持续且显著地使近期有症状的患者受益。然而，无症状性狭窄的手术似乎只有在精心选择的条件下才是合理的：相对年轻的个体没有任何合并症的治疗风险低。

We constructed a Markov model to evaluate effectiveness of carotid endaterectomy (CEA). In modeling four health states, probabilities of transition to another state were estimated using data from major randomized control trials. CEA for severe carotid stenosis would consistently and significantly benefit patients with recent symptoms. However, surgery for asymptomatic stenosis appears justified only in carefully selected conditions : low treatment risks for relatively young individuals without any comorbidities.