Clinical features and prognostic factors in patients with microvascular infiltration of hepatocellular carcinoma: Development and validation of a nomogram and risk stratification based on the SEER database

Abstract

Background: The goal is to establish and validate an innovative prognostic risk stratification and nomogram in patients of hepatocellular carcinoma (HCC) with microvascular invasion (MVI) for predicting the cancer-specific survival (CSS).

Methods: 1487 qualified patients were selected from the Surveillance, Epidemiology and End Results (SEER) database and randomly assigned to the training cohort and validation cohort in a ratio of 7:3. Concordance index (C-index), area under curve (AUC) and calibration plots were adopted to evaluate the discrimination and calibration of the nomogram. Decision curve analysis (DCA) was used to quantify the net benefit of the nomogram at different threshold probabilities and compare it to the American Joint Committee on Cancer (AJCC) tumor staging system. C-index, net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to evaluate the improvement of the new model over the AJCC tumor staging system. The new risk stratifications based on the nomogram and the AJCC tumor staging system were compared.

Results: Eight prognostic factors were used to construct the nomogram for HCC patients with MVI. The C-index for the training and validation cohorts was 0.785 and 0.776 respectively. The AUC values were higher than 0.7 both in the training cohort and validation cohort. The calibration plots showed good consistency between the actual observation and the nomogram prediction. The IDI values of 1-, 3-, 5-year CSS in the training cohort were 0.17, 0.16, 0.15, and in the validation cohort were 0.17, 0.17, 0.17 (P<0.05). The NRI values of the training cohort were 0.75 at 1-year, 0.68 at 3-year and 0.67 at 5-year. The DCA curves indicated that the new model more accurately predicted 1-year, 3-year, and 5-year CSS in both training and validation cohort, because it added more net benefit than the AJCC staging system. Furthermore, the risk stratification system showed the CSS in different groups had a good regional division.

Conclusions: A comprehensive risk stratification system and nomogram were established to forecast CSS for patients of HCC with MVI.

Keywords: cancer-specific survival; hepatocellular carcinoma; microvascular invasion; nomogram; prognostic model; risk stratification.

Figure 1

The flowchart of the hepatocellular carcinoma with microvascular infiltration identified in the SEER database.

Figure 2

The nomogram for HCC patients with MVI. * P < 0.05, ** P < 0.01, *** P < 0.001, HCC, hepatocellular carcinoma; MVI, microvascular invasion.

Figure 3

The area under the time-dependent receiver operating characteristic (ROC) curve (td-AUC) based on the nomogram. (A) Based on the training cohorts; (B) Based on the validation cohorts.

Figure 4

Decision curve analysis of the nomogram and AJCC tumor staging for the cancer-specific survival prediction of HCC patients with MVI. (A, C, E) 1-, 3- and 5-year cancer-specific survival benefits based on the training cohorts. (B, D, F) 1-, 3- and 5-year cancer-specific survival benefits based on the validation cohort. HCC, hepatocellular carcinoma; MVI, microvascular invasion.

Figure 5

Calibration curves in the training (A, C, E) and validation (B, C, F) cohorts for 1-year, 3-year, and 5-year cancer-specific survival.

Figure 6

C-index results, (A) The C-index based on the nomogram; (B) The C-index based on the AJCC tumor staging.

Figure 7

The basis for grouping new risk stratification (Cut-off point selected using X-tile).

Figure 8

Kaplan–Meier curves of cancer-specific survival for new risk classification and the AJCC tumor staging (A) The AJCC tumor staging in the training cohort; (B) The AJCC tumor staging in the validation cohort; (C) The new risk classification in the training cohort; (D) The new risk classification in the validation cohort.