Title of Manuscript: Development and Internal-external Validation of a Comprehensive Model for Predicting Risk of Post-RFA Recurrence in HCC Patients

Background A predictive model for post radiofrequency ablation (RFA) recurrence in patients with Hepatocellular carcinoma (HCC) that incorporates variables like sleep quality and psychological factors can provide more time to prevent the recurrence. Our aim is to investigate the relationship between these factors and post-RFA recurrence, and to construct a predictive model includes these highly preventable factors. Methods We collected data from HCC patients who underwent RFA for the first time from January 1, 2015, to July 2023, assessing their sleep quality, anxiety, and depression levels. We employed Restricted cubic splines (RCS), mediation analysis, Cox proportional hazards model, Elastic network Cox proportional hazards, Competitive risk model to ascertain the relationship between these factors and post-RFA recurrence. We then constructed a predictive model incorporating these factors, and evaluated the model's performance through internal and external validation datasets partitioning by time period.