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A novel model for predicting posthepatectomy liver failure in patients with hepatocellular carcinoma.

ABSTRACT: Posthepatectomy liver failure (PHLF) is the most leading cause of mortality following hepatectomy in patients with hepatocellular carcinoma (HCC). Platelet count was reported to be a simple but useful indicator of liver cirrhosis and function of spleen. Spleen stiffness (SS) was used to evaluate the morphological change of spleen and was reported to be related to liver cirrhosis and portal hypertension. However, the predictive value of platelet to spleen stiffness ratio (PSR) on PHLF remains unknown. A retrospective study was performed to analyze 158 patients with HCC following hepatectomy from August 2015 to February 2016. Univariate and multivariate analyses were performed to evaluate the value of each risk factor for predicting PHLF. The predictive efficiency of the risk factors was evaluated by receiver operating characteristic (ROC) curve. PHLF occured in 23 (14.6%) patients. PSR (P<0.001, odds ratio (OR) = 0.622, 95% confidence interval (CI) 0.493~0.784), hepatic inflow occlusion (HIO) (P = 0.003, OR = 1.044, 95% CI 1.015~1.075) and major hepatectomy (P = 0.019, OR = 5.967, 95% CI 1.346~26.443) were demonstrated to be the independent predictive factors for development of PHLF in a multivariate analysis. Results of the present study suggested PSR is a novel and non-invasive model for predicting PHLF in patients with HCC.

SUBMITTER: Peng W

PROVIDER: S-EPMC6608969 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesPosthepatectomy liver failure (PHLF) is a severe complication of liver resection. We aimed to develop and validate a model based on extracellular volume (ECV) and liver volumetry derived from computed tomography (CT) for preoperative predicting PHLF in resectable hepatocellular carcinoma (HCC) patients.MethodsA total of 393 resectable HCC patients from two hospitals were enrolled and underwent multiphasic contrast-enhanced CT before surgery. A total of 281 patients from our hospital were randomly divided into a training cohort (n = 181) and an internal validation cohort (n = 100), and 112 patients from another hospital formed the external validation cohort. CT-derived ECV was measured on nonenhanced and equilibrium phase images, and liver volumetry was measured on portal phase images. The model is composed of independent predictors of PHLF. The under the receiver operator characteristic curve (AUC) and calibration curve were used to reflect the predictive performance and calibration of the model. Comparison of AUCs used the DeLong test.ResultsCT-derived ECV, measured future liver remnant (mFLR) ratio, and serum albumin were independent predictors for PHLF in resectable HCC patients. The AUC of the model was significantly higher than that of the ALBI score in the training cohort, internal validation cohort, and external validation cohort (all p < 0.001). The calibration curve of the model showed good consistency in the training cohort and the internal and external validation cohorts.ConclusionsThe novel model contributes to the preoperative prediction of PHLF in resectable HCC patients.Critical relevance statementThe novel model combined CT-derived extracellular volume, measured future liver remnant ratio, and serum albumin outperforms the albumin-bilirubin score for predicting posthepatectomy liver failure in patients with resectable hepatocellular carcinoma.Key points• CT-derived ECV correlated well with the fibrosis stage of the background liver. • CT-derived ECV and mFLR ratio were independent predictors for PHLF in HCC. • The AUC of the model was higher than the CT-derived ECV and mFLR ratio. • The model showed a superior predictive performance than that of the ALBI score.

Project description:BackgroundPost-hepatectomy liver failure (PHLF) remains a complication with the potential risk of mortality for hepatocellular carcinoma (HCC) patients. The systemic inflammatory response (SIR) has been demonstrated to be associated with a bad prognosis of liver cirrhosis and tumors. This study aims to evaluate the incremental prognostic value of inflammatory markers in predicting PHLF in patients with HCC.MethodsClinical characteristics and variables were retrospectively collected in 2824 patients diagnosed with HCC who underwent radical hepatectomy from the First Medical Center of the General Hospital of the People's Liberation Army. A recently published prognostic model for PHLF was used as the reference model. The increase in AUC (ΔAUC), integrated discrimination improvement (IDI), and the continuous version of the net reclassification improvement (NRI) were applied for quantifying the incremental value of adding the inflammatory markers to the reference model. A p value < 0.05 was considered statistically significant.ResultsThe reference PHLF model showed acceptable prediction performance in the current cohort, with an AUC of 0.7492 (95%CI, 0.7191-0.7794). The calculated ΔAUC associated with procalcitonin (PCT) was the only one that was statistically significant (p < 0.05), with a value of 0.0044, and demonstrated the largest magnitude of the increase in AUC. The continuous NRI value associated with the systemic immune-inflammation index (SII) was 35.79%, second only to GPS (46.07%). However, the inflammatory markers of the new models with statistically significant IDI only included WBC count, lymphocyte count, and SII. IDI associated with SII, meanwhile, was the maximum (0.0076), which was consistent with the performance of using the ΔAUC (0.0044) to assess the incremental value of each inflammatory variable.ConclusionsAmong a wide range of inflammatory markers, only PCT and SII have potential incremental prognostic value for predicting PHLF in patients with radical resectable HCC.

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A novel model for predicting posthepatectomy liver failure in patients with hepatocellular carcinoma.

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