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Table 3 Predictive performance for RFS of the proposed models

From: Prediction early recurrence of hepatocellular carcinoma eligible for curative ablation using a Radiomics nomogram

Models

Training dataset

N = 129

Validation dataset

N = 55

C-index (95%CI)

C-index (95%CI)

Clinical model

 clinicopathologic feature

0.649 (0.592–0.706)

0.556 (0.471–0.641)

Radiomics model

 Arterial phase

0.767 (0.702–0.832)

0.694 (0.623–0.832)

Portal vein phase

0.757 (0.692–0.821)

0.736 (0.632–0.841)

 Parenchymal phase

0.789 (0.723–0.853)

0.686 (0.582–0.791)

All phases

0.791 (0.726–0.856)

0.690 (0.586–0.795)

Combined model

 Arterial phase + Clinicopathologic feature

0.797 (0.732–0.862)

0.732 (0.628–0.837)

 Portal vein phase + Clinicopathologic feature

0.792 (0.727–0.857)

0.755 (0.651–0.860)

 Parenchymal phase + Clinicopathologic feature

0.806 (0.741–0.871)

0.728 (0.624–0.834)

 All phases + Clinicopathologic feature

0.809 (0.744–0.874)

0.724 (0.620–0.829)

  1. C-index (Harrell concordance index) indicates the predictive performance