Development and validation of a risk prediction algorithm for evaluating the efficacy of postoperative adjuvant TACE therapy for hepatocellular carcinoma: a retrospective study

Abstract Background and purpose There is a lack of a reliable outcome prediction model for patients evaluating the feasibility of postoperative adjuvant transarterial chemoembolization (PA-TACE) therapy. Our goal was to develop an easy-to-use tool specifically for these patients. Methods From January 2013 to June 2017, patients with liver cancer from the Liver Center of the First Affiliated Hospital of Chongqing Medical University received postoperative adjuvant Transarterial chemoembolization (TACE) therapy after liver cancer resection. A Cox’s proportional hazards model was established for these patients, followed by internal validation (enhanced bootstrap resampling technique) to further evaluate the predictive performance and discriminance, and compare with other predictive models. The prognostic factors considered included tumour number, maximum tumor diameter, Edmondson-Steiner (ES) grade, Microvascular invasion (MVI) grade, Ki67, age, sex, hepatitis B surface antigen, cirrhosis, Alpha-fetoprotein(AFP), Albumin-bilirubin (ALBI) grade, Child-pugh grade, body mass inex (BMI), Neutrophil-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR). Results The end point of the study was overall survival. The median overall survival was 31.8 (95%CI: 30.0-33.6 ) months, with 1-year, 2-year and 3-year survival rates being 96.3%, 84.0% and 75.3%, respectively. Tumour number, MVI grade, and BMI was incorporated into the model, which had good differentiation and accuracy. Internal validation (enhanced bootstrap ) suggested that Harrell’s C statistic is 0.72 (a measure of discrimination, with higher values indicating better discrimination). The model consistently outperforms other currently available models. Conclusions This model may be an easy-to-use tool for screening patients suitable for PA-TACE treatment and guiding the selection of clinical protocols. But further research and external validation are required.