Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK.
Br J Surg. 2018 Sep;105(10):1294-1304. doi: 10.1002/bjs.10964.
Clinical and imaging surveillance practices following endovascular aneurysm repair (EVAR) for intact abdominal aortic aneurysm (AAA) vary considerably and compliance with recommended lifelong surveillance is poor. The aim of this study was to develop a dynamic prognostic model to enable stratification of patients at risk of future secondary aortic rupture or the need for intervention to prevent rupture (rupture-preventing reintervention) to enable the development of personalized surveillance intervals.
Baseline data and repeat measurements of postoperative aneurysm sac diameter from the EVAR-1 and EVAR-2 trials were used to develop the model, with external validation in a cohort from a single-centre vascular database. Longitudinal mixed-effects models were fitted to trajectories of sac diameter, and model-predicted sac diameter and rate of growth were used in prognostic Cox proportional hazards models.
Some 785 patients from the EVAR trials were included, of whom 155 (19·7 per cent) experienced at least one rupture or required a rupture-preventing reintervention during follow-up. An increased risk was associated with preoperative AAA size, rate of sac growth and the number of previously detected complications. A prognostic model using predicted sac growth alone had good discrimination at 2 years (C-index 0·68), 3 years (C-index 0·72) and 5 years (C-index 0·75) after operation and had excellent external validation (C-index 0·76-0·79). More than 5 years after operation, growth rates above 1 mm/year had a sensitivity of over 80 per cent and specificity over 50 per cent in identifying events occurring within 2 years.
Secondary sac growth is an important predictor of rupture or rupture-preventing reintervention to enable the development of personalized surveillance intervals. A dynamic prognostic model has the potential to tailor surveillance by identifying a large proportion of patients who may require less intensive follow-up.
血管内腹主动脉瘤修复术（EVAR）后对完整的腹主动脉瘤（AAA）进行临床和影像学监测的实践差异很大，并且对推荐的终身监测的依从性很差。本研究的目的是开发一种动态预后模型，以对未来发生二次主动脉破裂或需要进行干预以预防破裂（破裂预防再干预）的风险患者进行分层，从而制定个性化的监测间隔。
使用 EVAR-1 和 EVAR-2 试验的术后动脉瘤囊直径的基线数据和重复测量值来开发模型，并在单中心血管数据库的队列中进行外部验证。使用纵向混合效应模型拟合囊直径的轨迹，使用模型预测的囊直径和生长速度来进行预后 Cox 比例风险模型。
EVAR 试验共纳入 785 例患者，其中 155 例（19.7%）在随访期间至少经历过一次破裂或需要进行破裂预防再干预。术前 AAA 大小、囊生长速度和先前检测到的并发症数量与风险增加相关。仅使用预测的囊生长构建的预后模型在术后 2 年（C 指数 0.68）、3 年（C 指数 0.72）和 5 年（C 指数 0.75）时具有良好的区分能力，并且具有出色的外部验证（C 指数 0.76-0.79）。术后 5 年以上，生长速度超过 1mm/年时，在识别 2 年内发生的事件时，敏感性超过 80%，特异性超过 50%。
二次囊生长是破裂或破裂预防再干预的重要预测指标，可用于制定个性化的监测间隔。动态预后模型有可能通过识别需要较少密集随访的患者的很大一部分，从而对监测进行定制。
