PURPOSE

To develop and validate a nomogram for individualized prediction of the long-term prognosis of patients with non-B, non-C hepatocellular carcinoma (NBNC-HCC) who underwent hepatectomy.

MATERIALS AND METHODS

Five hundred ninety-four patients who met the criteria were included in the research and randomly categorized into the training or validation cohort. The nomogram was constructed on the basis of the independent risk variables that were acquired via multivariate Cox proportional hazard regression analysis. Several complementary methods included the Harrell c-index, time-dependent areas under the receiver operating characteristic curve (tdAUC), and calibration plot, and the Kaplan-Meier curve with Log rank test were used to test predictive performance of the model. The clinical utility of the model was tested by the decision cure analysis (DCA).

RESULTS

Tumor diameter, tumor number, elevated serum gamma-glutamyl transpeptidase (GGT) level, microvascular invasion (MVI), and macrovascular invasion were independent risk factors of prognosis of NBNC-HCC. C-indexes of the nomogram were 0.702 (95% confidence interval [CI], 0.662-0.741) in the training cohort and 0.700 (95% CI, 0.643-0.758) in the validation cohort, and median tdAUC values of the nomogram were 0.743 (range, 0.736-0.775) in the training cohort and 0.751 (range, 0.686-0.793) in the validation cohort, which were both higher than those in the conventionally used Barcelona Clinic Liver Cancer staging system, American Joint Committee on Cancer, and eighth edition and the model of Zhang et al. The calibration plot depicted a good consistency between prediction of the model and observed outcome. The Kaplan-Meier curve analysis showed that the model was able to separate patients into three distinct risk subgroups. The DCA analysis also demonstrated that the nomogram was clinically useful.

CONCLUSION

We developed and validated a nomogram that was accurate and clinically useful in patients with NBNC-HCC who underwent hepatectomy.