Improved Preoperative Risk Assessment Tools Are Needed to Guide Informed Decision Making before Esophagectomy. Issue 1 (18th January 2023) - Gray, Katherine D.; Nobel, Tamar B.; Hsu, Meier; Tan, Kay See; Chudgar, Neel; Yan, Shi; Rusch, Valerie W.; Jones, David R.; Rocco, Gaetano; Molena, Daniela; Isbell, James M.
Abstract : Objective: We sought to evaluate the performance of 2 commonly used prediction models for postoperative morbidity in patients undergoing open and minimally invasive esophagectomy. Summary Background Data: Patients undergoing esophagectomy have a high risk of postoperative complications. Accurate risk assessment in this cohort is important for informed decision-making. Methods: We identified patients who underwent esophagectomy between January 2016 and June 2018 from our prospectively maintained database. Predicted morbidity was calculated using the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator (SRC) and a 5-factor National Surgical Quality Improvement Programderived frailty index. Performance was evaluated using concordance index (C-index) and calibration curves. Results: In total, 240 consecutive patients were included for analysis. Most patients (85%) underwent Ivor Lewis esophagectomy. The observed overall complication rate was 39%; the observed serious complication rate was 33%. The SRC did not identify risk of complications in the entire cohort (C-index, 0.553), patients undergoing open esophagectomy (C-index, 0.569), or patients undergoing minimally invasive esophagectomy (C-index, 0.542); calibration curves showed general underestimation. Discrimination of the SRC was lowest for reoperation (C-index, 0.533) and highest for discharge to a facility other than home (C-index, 0.728). Similarly, the frailty index had C-index of 0.513 for discriminating any complication, 0.523 for serious complication, and 0.559 for readmission. Conclusions: SRC and frailty index did not adequately predict complications after esophagectomy. Procedure-specific risk-assessment tools are needed to guide shared patient-physician decision-making in this high-risk population.