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  • Title: Value of E-PASS models for predicting postoperative morbidity and mortality in resection of perihilar cholangiocarcinoma and gallbladder carcinoma.
    Author: Haga Y, Miyamoto A, Wada Y, Takami Y, Takeuchi H.
    Journal: HPB (Oxford); 2016 Mar; 18(3):271-8. PubMed ID: 27017167.
    Abstract:
    BACKGROUND: It has previously been reported that a general risk model, Estimation of Physiologic Ability and Surgical Stress (E-PASS), and its modified version, mE-PASS, had a high predictive power for postoperative mortality and morbidity in a variety of gastrointestinal surgeries. This study evaluated their utilities in proximal biliary carcinoma resection. METHODS: E-PASS variables were collected in patients undergoing resection of perihilar cholangiocarcinoma and gallbladder carcinoma in Japanese referral hospitals. RESULTS: Analysis of 125 patients with gallbladder cancer and 97 patients with perihilar cholangiocarcinoma (n = 222). Fifty-six patients (25%) underwent liver resection with either hemihepatectomy or extended hemihepatectomy. The E-PASS models showed a high discrimination power to predict in-hospital mortality; areas under the receiver operating characteristic curve (95% confidence intervals) were 0.85 (0.76-0.94) for E-PASS and 0.82 (0.73-0.91) for mE-PASS. The predicted mortality rates correlated with the severity of postoperative complications (Spearman's rank correlation coefficient: ρ = 0.51, P < 0.001 for E-PASS; ρ = 0.47, P < 0.001 for mE-PASS). CONCLUSIONS: The E-PASS models examined herein may accurately predict postoperative morbidity and mortality in proximal biliary carcinoma resection. These models will be useful for surgical decision-making, informed consent, and risk adjustments in surgical audits.
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