Nomogram for Predicting Postoperative Pulmonary Metastasis in Hepatocellular Carcinoma Based on Inflammatory Markers.

Background: Uncertainty surrounds the usefulness of inflammatory markers in hepatocellular carcinoma (HCC) patients for predicting postoperative pulmonary metastasis (PM). The purpose of this study was to assess the predictive value of inflammatory markers as well as to create a new nomogram model for predicting PM.

Methods: Cox regression was utilized to identify independent prognostic variables and to create a nomogram that predicted PM for comparison with a validation cohort and other prediction systems. We retrospectively analyzed a total of 1109 cases with HCC were included.

Results: The systemic inflammatory response index (SIRI) and aspartate aminotransferase-to-platelet ratio index (APRI) were independent risk factors for PM, with a concordance index of .78 (95% CI: .74-.81) for the nomogram. The areas under the curve of the nomograms for PM predicted at 1-, 3-, and 5-year were .82 (95% CI: .77-.87), .82 (95% CI: .78-.87) and .81 (95% CI: .75-.86), respectively, which were better than those of Barcelona Clinic Liver Cancer and China liver cancer stage. Decision curve analyses demonstrated a broader range of nomogram threshold probabilities.

Conclusion: A nomogram based on SIRI and APRI can accurately predict postoperative PM in HCC.