McGinigle Katharine L, Freeman Nikki L B, Marston William A, Farber Alik, Conte Michael S, Kosorok Michael R, Kalbaugh Corey A
Department of Surgery, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Front Cardiovasc Med. 2021 Jul 16;8:709904. doi: 10.3389/fcvm.2021.709904. eCollection 2021.
In cancer, there are survival-based staging systems and tailored, stage-based treatments. There is little personalized treatment in vascular disease. The 2019 Global Vascular Guidelines on the Management of CLTI proposed successful treatment hinges upon Patient risk, Limb severity, and ANatomic complexity (PLAN). We sought to confirm a three axis approach and define how increasing severity affects mortality, not just limb loss. Patients revascularized for incident CLTI at our institution from 2013 to 2017 were included. Outcomes were mortality, limb loss, the composite endpoint of amputation-free survival. Using Bayesian machine learning, specifically supervised topic modeling, clusters of patient features associated with mortality were formed after controlling for revascularization type. Patients were assigned to the cluster they belonged to with highest probability; clusters were characterized by analyzing the characteristics of patients within them. Patient outcomes were used to order the clusters into stages with increasing mortality. We defined three distinct clusters as the basis for patient- and limb-centered stages. Across stages, rates of 1-year mortality were 7.6, 13.8, 18.9% and rates of amputation-free survival were 84.8, 79.3, and 63.2%. Stage one had patients with rest pain and previous revascularization who were less likely to have wounds, diabetes, and renal disease. Stage two had doubled mortality, likely related to diabetes prevalence. Stage three is characterized by high rates of complicated comorbidities, particularly end stage renal disease, and significantly higher rate of limb loss (22.6 vs. 8% in stages one and two). Using precision medicine, we have demonstrated clustering of CLTI patients that can be used toward a robust staging system. We provide empiric evidence for PLAN and detail about how changes in each variable affect survival and amputation-free survival.
在癌症领域，存在基于生存情况的分期系统以及针对性的、基于分期的治疗方法。而在血管疾病中，个性化治疗却很少。2019年全球下肢慢性威胁性缺血（CLTI）管理血管指南提出，成功治疗取决于患者风险、肢体严重程度和解剖复杂性（PLAN）。我们试图证实一种三轴方法，并确定病情严重程度增加如何影响死亡率，而不仅仅是肢体丧失情况。纳入了2013年至2017年在我们机构因新发CLTI接受血管重建术的患者。观察指标为死亡率、肢体丧失、无截肢生存的复合终点。使用贝叶斯机器学习，特别是监督主题建模，在控制血管重建类型后，形成了与死亡率相关的患者特征聚类。将患者分配到概率最高的所属聚类中；通过分析聚类中患者的特征来描述聚类。利用患者的观察结果将聚类按死亡率增加的顺序分为不同阶段。我们定义了三个不同的聚类作为以患者和肢体为中心的分期基础。在各个阶段中，1年死亡率分别为7.6%、13.8%、18.9%，无截肢生存率分别为84.8%、79.3%和63.2%。第一阶段的患者有静息痛且曾接受血管重建术，伤口、糖尿病和肾病的发生率较低。第二阶段的死亡率翻倍，可能与糖尿病患病率有关。第三阶段的特点是复杂合并症发生率高，尤其是终末期肾病，肢体丧失率显著更高（第一阶段和第二阶段分别为8%，第三阶段为22.6%）。通过精准医学，我们已经证明了CLTI患者的聚类可用于构建一个强大的分期系统。我们为PLAN提供了实证依据，并详细说明了每个变量的变化如何影响生存和无截肢生存情况。
