Development and internal validation of a prognostic model for mortality of patients with abdominal aortic aneurysms treated with endovascular aneurysm repair
Abstract
Summary:Background: Morbidity and mortality associated with elective endovascular aneurysm repair (EVAR) for abdominal aortic aneurysms (AAA) must be balanced against the impending risk of aneurysm rupture and the estimated remaining lifetime. The aim of this study is to develop and validate a prognostic model for mortality of patients with AAA treated with EVAR. Methods: This retrospective observational study included 251 consecutive patients treated with EVAR for asymptomatic AAA between January 2001 and December 2012 at the University Hospital in Bern, Switzerland. Pre-selection of variables was based on a literature review; least absolute shrinkage and selection operator technique was used for the final variable selection. A Firth’s bias reduced Cox proportional hazard model was developed and validated using 10,000 bootstrap samples to predict survival after EVAR. Results: The median follow-up time was 5.3 years (range 0.1 to 15.9). At the study closing date 95% of follow-up information was available. The mortality rates were 31.9% at 5 years and 50.5% at the study closing date, respectively. Identified predictors for overall mortality after EVAR were age, hazard ratio (HR) = 2.24 per 10-year increase (95% CI 1.64 to 3.09), the presence of chronic obstructive pulmonary disease (COPD), HR = 2.22 (95% CI 1.48 to 3.31), and lower estimated glomerular filtration rate, HR = 1.24 per 10 ml/min/1.73 m2 decrease (95% CI 1.12 to 1.39). The model showed good discrimination ability, Harrell’s C = 0.722 (95% CI 0.667 to 0.778) and was very robust in the bootstrap in-sample validation Harrell’s C = 0.726 (95% CI 0.662 to 0.788). Conclusion: Higher age, the presence of COPD and impaired kidney function are independent predictors for impaired survival after EVAR. The expected remaining lifetime should be considered in patients with AAA. This prognostic model can help improving patient care; however, external validation is needed prior to clinical implementation.
References
1 . New ESC/ESA Guidelines on non-cardiac surgery: Cardiovascular assessment and management. Eur Heart J. 2014;35:2383–431.
2 . Endovascular repair of abdominal aortic aneurysm in patients physically ineligible for open repair. Ann Surg. 2017;266(5):713–9.
3 . The UK endovascular aneurysm repair (EVAR) randomised controlled trials: Long-term follow-up and cost-effectiveness analysis. Health Technol Asses. 2018;22(5):1–132.
4 The fate of patients referred to a specialist vascular unit with large infra-renal abdominal aortic aneurysms over a two-year period. Eur J Vasc Endovasc. 2011;42(3):295–301.
5 Editor’s Choice – European Society for Vascular Surgery (ESVS) 2019 Clinical Practice Guidelines on the Management of Abdominal Aorto-iliac Artery Aneurysms. Eur J Vasc Endovasc. 2019;57(1):8–93.
6 . Editor’s choice: Five-year outcomes in men screened for abdominal aortic aneurysm at 65 years of age: A population-based cohort study. Eur J Vasc Endovasc. 2014;47(1):37–44.
7 . Impact of the first 5 years of a national abdominal aortic aneurysm screening programme. Brit J Surg. 2016;103(9):1125–31.
8 . Surgery for small asymptomatic abdominal aortic aneurysms. Cochrane DB Syst Rev. 2015(2):CD001835.
9 . Rupture rates of untreated large abdominal aortic aneurysms in patients unfit for elective repair. J Vasc Surg. 2015;61(6):1606–12.
10 . Predictors of long-term mortality following elective endovascular repair of abdominal aortic aneurysms. Int Angiol. 2018;37(4):277–85.
11 . A model to predict outcomes for endovascular aneurysm repair using preoperative variables. Eur J Vasc Endovasc. 2008;35(5):571–9.
12 External validation of the Endovascular aneurysm repair Risk Assessment model in predicting survival, reinterventions, and endoleaks after endovascular aneurysm repair. J Vasc Surg. 2014;59(6):1555–61, 1561.e1–3.
13 . Survival analysis in clinical trials: Basics and must know areas. Perspect Clin Res. 2011;2(4):145–8.
14 Completeness of follow-up determines validity of study findings: Results of a prospective repeated measures cohort study. PLoS One. 2015;10(10):e0140817.
15 Effect of gender on long-term survival after abdominal aortic aneurysm repair based on results from the Medicare national database. J Vasc Surg. 2011;54(1):1–12.e6; discussion 11-2.
16 . Predictors of 1-year survival after endovascular aneurysm repair. Eur J Vasc Endovasc. 2016;51(4):528–34.
17 . Abdominal aortic aneurysms – glycaemic status and mortality. J Diabetes Complicat. 2016;30(3):438–43.
18 Outcome after open and endovascular repairs of abdominal aortic aneurysms in matched cohorts using propensity score modeling. J Vasc Surg. 2015;62(2):304–11.e2.
19 Long-term outcomes and factors influencing late survival following elective abdominal aortic aneurysm repair: A 24-year experience. Vascular. 2016;24(2):115–25.
20 . Systematic review and meta-analysis of factors influencing survival following abdominal aortic aneurysm repair. Eur J Vasc Endovasc. 2016;51(2):203–15.
21 . Ten-year comparison of all-cause mortality after endovascular or open repair of abdominal aortic aneurysms: A propensity score analysis. World J Surg. 2013;37(3):680–7.
22 . Preoperative spirometry results as a determinant for long-term mortality after EVAR for AAA. Eur J Vasc Endovasc. 2012;43(1):43–7.
23 . Cardiovascular predictors for long-term mortality after EVAR for AAA. Vasc Med. 2011;16(6):422–7.
24 FT07. Anatomical predictors of long-term mortality after standard EVAR. J Vasc Surg. 2017;65(6):17s–18 s.
25 . Bootstrap confidence intervals: When, which, what? A practical guide for medical statisticians. Stat Med. 2000;19(9):1141–64.
26 . Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD Statement. Eur Urol. 2015;67(6):1142–51.
27 . Epidemiology of heart failure. Circ Res. 2013;113(6):646–59.
28 . Importance of events per independent variable in proportional hazards analysis I. Background, goals, and general strategy. J Clin Epidemiol. 1995;48(12):1495–501.
29 . A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9.