Nomogram for prediction of the international study Group of Liver Surgery (ISGLS) grade B/C Posthepatectomy liver failure in HBV-related hepatocellular carcinoma patients: an external validation and prospective application study

Abstract

Background: To develop a nomogram for predicting the International Study Group of Liver Surgery (ISGLS) grade B/C posthepatectomy liver failure (PHLF) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients.

Methods: Patients initially treated with hepatectomy were included. Univariate regression analysis and stochastic forest algorithm were applied to extract the core indicators and reduce redundancy bias. The nomogram was then constructed by using multivariate logistic regression, and validated in internal and external cohorts, and a prospective clinical application.

Results: There were 900, 300 and 387 participants in training, internal and external validation cohorts, with the morbidity of grade B/C PHLF were 13.5, 11.0 and 20.2%, respectively. The nomogram was generated by integrating preoperative total bilirubin, platelet count, prealbumin, aspartate aminotransferase, prothrombin time and standard future liver remnant volume, then achieved good prediction performance in training (AUC = 0.868, 95%CI = 0.836-0.900), internal validation (AUC = 0.868, 95%CI = 0.811-0.926) and external validation cohorts (AUC = 0.820, 95%CI = 0.756-0.861), with well-fitted calibration curves. Negative predictive values were significantly higher than positive predictive values in training cohort (97.6% vs. 33.0%), internal validation cohort (97.4% vs. 25.9%) and external validation cohort (94.3% vs. 41.1%), respectively. Patients who had a nomogram score < 169 or ≧169 were considered to have low or high risk of grade B/C PHLF. Prospective application of the nomogram accurately predicted grade B/C PHLF in clinical practise.

Conclusions: The nomogram has a good performance in predicting ISGLS grade B/C PHLF in HBV-related HCC patients and determining appropriate candidates for hepatectomy.

Keywords: Hepatitis B virals; Hepatocellular carcinoma; Nomogram; Posthepatectomy liver failure.

Fig. 1

Flow chart of the study design

Fig. 2

Univariable logistic regression analyses to identify predictors of Grade B/C PHLF in patients with HBV-related HCC in the training cohort. Forest maps show the risk ratios of indicators. b Correlation analysis among indicators significantly related with grade B/C PHLF by logistic univariate analysis. Colors from red to blue indicate a correlation from positive to negative. The values represent the significant P values of the correlations, indicating the parts of correlations are significant. c The importance of the Stochastic Forest algorithm based on grouping indexes. Logistic univariate significant indicators were divided into seven groups according to clinical significance and a random forest model was constructed for each group of indicators to predict grade B/C PHLF risk. The bars represent the importance of each indicator; the red bars represent the most important indicators of each group. d There is no correlation among the indicators after redundancy removal by grouping stochastic forest algorithm. Colors from red to blue indicate a correlation from positive to negative. The values inside the circle represent the significant P values of the correlations, indicating the correlations among all indicators are not significant

Fig. 3

a Nomogram for predicting grade B/C PHLF in HBV-related HCC patients. To use the nomogram, find the position of each variable on the corresponding axis, draw a line to the points axis for the number of points, add the points from all of the variables, and draw a line from the total points axis to determine the grade B/C PHLF probabilities at the lower line of the nomogram. b Receiver operating characteristic (ROC) curves for the nomogram in predicting grade B/C PHLF. Calibration plots show the relationship between the predicted probabilities based on the nomogram and actual values: c Training cohort, d Internal validation cohort, e External validation cohort. Nomogram-predicted probability of grade B/C PHLF is plotted on the x-axis, and the actual probability is plotted on the y-axis

Fig. 4

a Total points distribution of false positive events (blue polyline). The X-axis represents the total points used to predict the risk of grade B/C PHLF, the Y-axis represents the frequency of false positive events. The red dotted line represents the fitted line and presents a normal distribution. a Training cohort, the false positive events were concentrated around the maximum value 175 point, and close to the preset cutoff (169 points). b Internal validation cohort, the false positive events were concentrated around the maximum value 170 points. c External validation cohort, the false positive events were concentrated around the maximum value 176 points. b Comparison of predicative performance for predicting grade B/C PHLF between the nomogram and conventional scores: a Training cohort, b Internal validation cohort, c External validation cohort