Outcomes of curative liver resection for hepatocellular carcinoma in patients with cirrhosis

BACKGROUND Given the poor synthetic function of cirrhotic liver, successful resection for patients with hepatocellular carcinoma (HCC) necessitates the ability to achieve resections with tumor free margins. AIM To validate post hepatectomy liver failure score (PHLF), compare it to other established systems and to stratify risks in patients with cirrhosis who underwent curative liver resection for HCC. METHODS Between December 2010 and January 2017, 120 patients underwent curative resection for HCC in patients with cirrhosis were included, the pre-operative, operative and post-operative factors were recorded to stratify patients' risks of decompensation, survival, and PHLF. RESULTS The preoperative model for end-stage liver disease (MELD) score [odds ratio (OR) = 2.7, 95%CI: 1.2-5.7, P = 0.013], tumor diameter (OR = 5.4, 95% CI: 2-14.8, P = 0.001) and duration of hospital stay (OR = 2.5, 95%CI: 1.5-4.2, P = 0.001) were significant independent predictors of hepatic decompensation after resection. While the preoperative MELD score [hazard ratio (HR) = 1.37, 95%CI: 1.16-1.62, P < 0.001] and different grades of PHLF (grade A: HR = 2.33, 95% CI: 0.59-9.24; Grade B: HR = 3.15, 95%CI: 1.11-8.95; Grade C: HR = 373.41, 95%CI: 66.23-2105.43; P < 0.001) and HCC recurrence (HR = 11.67, 95%CI: 4.19-32.52, P < 0.001) were significant independent predictors for survival. CONCLUSION Preoperative MELD score and tumor diameter can independently predict hepatic decompensation. While, preoperative MELD score, different grades of PHLF and HCC recurrence can precisely predict survival.

Automated summary

This study validated the effectiveness of post hepatectomy liver failure score (PHLF) in cirrhotic patients undergoing curative liver resection for HCC. The results showed that preoperative MELD score and tumor diameter can independently predict hepatic decompensation, while preoperative MELD score, different grades of PHLF, and HCC recurrence can accurately predict survival.