Limited incremental value and cross-cohort transferability of CT radiomics for survival prediction after TACE in hepatocellular carcinoma

Abstract Purpose To evaluate whether pretreatment CT radiomics adds information for overall survival (OS) prediction among patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE), and assess frozen imaging-model performance in an independent cohort. Methods This retrospective study included 221 WAW-TACE and 98 HCC-TACE-SEG patients with pretreatment arterial and portal venous CT. Incremental value of a tumor-radiomics Random Survival Forest score (R1) beyond cohort-specific clinical Cox models (C0) was evaluated within each cohort using 5-fold cross-validation repeated 10 times. External validation was restricted to frozen WAW-trained R1 models (Top-K = 5, 10, 15) applied to HCC-TACE-SEG without refitting; the combined C0 + R1 model was not externally validated. Results WAW-TACE included 162 deaths and HCC-TACE-SEG 86 deaths. In WAW-TACE, C0, R1 Top-K = 15, and C0 + R1 achieved C-indices of 0.646 ± 0.043, 0.593 ± 0.049, and 0.639 ± 0.045, respectively. Corresponding HCC-TACE-SEG estimates were 0.496 ± 0.087, 0.530 ± 0.072, and 0.495 ± 0.094. Thus, R1 did not consistently improve cohort-specific clinical reference models. In frozen external application, Top-K = 5, 10, and 15 achieved C-indices of 0.463 (95% CI 0.397–0.532), 0.535 (0.468–0.608), and 0.528 (0.460–0.598), respectively. Conclusion The evaluated models showed no consistent incremental value for OS prediction within these TACE cohorts and limited frozen-model discrimination in the clinically distinct HCC-TACE-SEG cohort. These findings do not support clinical use of these models or establish a general limitation of CT radiomics.