Performance of non-invasive biomarkers compared with invasive methods for risk prediction of posthepatectomy liver failure in hepatocellular carcinoma

医学 肝细胞癌 内科学 胃肠病学 逻辑回归 肝切除术 优势比 肝癌 列线图 肿瘤科 外科 切除术
作者
Christian Hobeika,Clémence Guyard,Riccardo Sartoris,Cesare Maino,Pierre‐Emmanuel Rautou,Safi Dokmak,Mohamed Bouattour,François Durand,Emmanuel Weiss,Valérie Vilgrain,Aurélie Beaufrère,Ailton Sepulveda,Olivier Farges,Valérie Paradis,Alain Luciani,Chetana Lim,Danièle Sommacale,Olivier Scatton,Alexis Laurent,Jean‐Charles Nault,Olivier Soubrane,Maxime Ronot,François Cauchy
出处
期刊:British Journal of Surgery [Oxford University Press]
卷期号:109 (5): 455-463 被引量:8
标识
DOI:10.1093/bjs/znac017
摘要

Posthepatectomy liver failure (PHLF) is a rare but dreaded complication. The aim was to test whether a combination of non-invasive biomarkers (NIBs) and CT data could predict the risk of PHLF in patients who underwent resection of hepatocellular carcinoma (HCC).Patients with HCC who had liver resection between 2012 and 2020 were included. A relevant combination of NIBs (NIB model) to model PHLF risk was identified using a doubly robust estimator (inverse probability weighting combined with logistic regression). The adjustment variables were body surface area, ASA fitness grade, male sex, future liver remnant (FLR) ratio, difficulty of liver resection, and blood loss. The reference invasive biomarker (IB) model comprised a combination of pathological analysis of the underlying liver and hepatic venous pressure gradient (HVPG) measurement. Various NIB and IB models for prediction of PHLF were fitted and compared. NIB model performances were validated externally. Areas under the curve (AUCs) were corrected using bootstrapping.Overall 323 patients were included. The doubly robust estimator showed that hepatitis C infection (odds ratio (OR) 4.33, 95 per cent c.i. 1.29 to 9.20; P = 0.001), MELD score (OR 1.26, 1.04 to 1.66; P = 0.001), fibrosis-4 score (OR 1.36, 1.06 to 1.85; P = 0.001), liver surface nodularity score (OR 1.55, 1.28 to 4.29; P = 0.031), and FLR volume ratio (OR 0.99, 0.97 to 1.00; P = 0.014) were associated with PHLF. Their combination (NIB model) was fitted externally (2-centre cohort, 165 patients) to model PHLF risk (AUC 0.867). Among 129 of 323 patients who underwent preoperative HVPG measurement, NIB and IB models had similar performances (AUC 0.753 versus 0.732; P = 0.940). A well calibrated nomogram was drawn based on the NIB model (AUC 0.740). The risk of grade B/C PHLF could be ruled out in patients with a cumulative score of less than 160 points.The NIB model provides reliable preoperative evaluation with performance at least similar to that of invasive methods for PHLF risk prediction.
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