Abstract

Objectives Current predictors are largely unsatisfied for early recurrence (ER) of hepatocellular carcinoma (HCC) after thermal ablation. We aimed to explore the prognostic value of peripheral immune factors (PIFs) for better ER prediction of HCC after thermal ablation. Methods Patients who received peripheral blood mononuclear cells (PBMCs) tests before thermal ablation were included. Clinical parameters and 18 PIFs were selected to construct ModelClin, ModelPIFs and the hybrid ModelPIFs-Clin. Model performances were evaluated using area under the curve (AUC), and recurrence-free survival (RFS) were analyzed by Kaplan-Meier analysis and log-rank tests. Results 244 patients were included and were randomly divided in 3:1 ratio to discovery and validation cohorts. Clinical parameters including tumor size and AFP, and PIFs including neutrophils, platelets, CD3+CD16+CD56+ NKT and CD8+CD28- T lymphocytes were selected. The ModelPIFs-Clin showed increase in predictive performance compared with ModelClin, with the AUC improved from 0.664 (95%CI:0.588–0.740) to 0.801 (95%CI:0.734–0.867) in discovery cohort (p < 0.0001), and from 0.645 (95%CI:0.510–0.781) to 0.737(95%CI:0.608–0.865) in validation cohort (p = 0.1006). ModelPIFs-Clin enabled ER risk stratification of patients. Patients predicted in ModelPIFs-Clin high-risk subgroup had a poor RFS compared with those predicted as ModelPIFs-Clin low-risk subgroup, with the median RFS was 18.00 month versus 100.78 month in discovery cohort (p < 0.0001); and 24.00 month versus 60.35 month in validation cohort (p = 0.288). Patients in different risk subgroups exhibited distinct peripheral immune contexture. Conclusions Peripheral immune cells aiding clinical parameters boosted the prediction ability for ER of HCC after thermal ablation, which be helpful for pre-ablation ER risk stratification.

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