Validation of a preoperative prediction model for mortality within 1 year after endovascular aortic aneurysm repair of intact aneurysms

Objective Most would agree that at least 1-year survival is necessary after intact abdominal aortic aneurysm (AAA) repair to appropriately justify the cost and risk of the procedure. No validated clinical decision instruments exist to predict survival after endovascular aneurysm repair (EVAR) beyond the perioperative period. The purpose of this analysis was to create a preoperative prediction model for 1-year mortality after EVAR for intact AAA in the Society for Vascular Surgery Vascular Quality Initiative. Methods All intact EVARs in the Society for Vascular Surgery Vascular Quality Initiative from 2011 to 2015 were randomly divided into training (n = 17,836) and validation (n = 2500) data sets, and 31 preoperative candidate predictors were identified. A logistic regression model for 1-year mortality was created, and bootstrapped stepwise variable elimination was used to reduce this model to a best subset of predictors. Penalized maximum likelihood estimation was used to correct for potential overfitting. The final model was internally validated by bootstrapping the area under the curve (AUC) and the calibration slope and intercept, and its performance when applied to the training and validation data sets was compared. Results After elective and nonelective (symptomatic, intact) EVAR, 1-year mortality was 5.5% (n = 900/16,411) and 11.4% (n = 162/1425), respectively. The mean probability of 1-year mortality was 6.0% (n = 1062) in the training set and 5.7% (n = 143) in the validation cohort ( P = .12). Significant preoperative predictors of 1-year mortality included chronic obstructive pulmonary disease, age, preoperative renal insufficiency (creatinine concentration ≥1.8 mg/dL or on hemodialysis), ejection fraction <50%, transfer status, body mass index <24 kg/m 2 , preoperative beta-blocker exposure, larger AAA diameter, and lower admission hemoglobin level. Preoperative statin use was found to be protective. The bias-corrected AUC was 0.759 (Hosmer-Lemeshow goodness-of-fit P value of 0.36; calibration intercept, −0.003; slope, 0.999). When applied to the validation data set, the model had AUC of 0.724 (95% confidence interval, 0.676-0.768; calibration intercept, 0.0009; slope, 0.970), which was in excellent agreement with the original data set bias-corrected AUC. Notably, ∼27.5% (n = 4902) had four or more risk factors with a predicted 1-year post-EVAR mortality risk of 10% to 22% despite that 33.2% of these patients had AAA diameters below recommended treatment guideline minimum thresholds. Conclusions This validated preoperative prediction model for 1-year mortality identifies patients less likely to benefit from EVAR. Appropriateness of intact AAA EVAR care delivery can be improved by use of this clinical decision aid to determine which high-risk patients have lower probability of mortality within the first postoperative year relative to their predicted annualized rupture risk.