Prediction of Survival Among Patients Receiving Transarterial Chemoembolization for Hepatocellular Carcinoma: A Response‐Based Approach

Abstract

Background and Aims The heterogeneity of intermediate‐stage hepatocellular carcinoma (HCC) and the widespread use of transarterial chemoembolization (TACE) outside recommended guidelines have encouraged the development of scoring systems that predict patient survival. The aim of this study was to build and validate statistical models that offer individualized patient survival prediction using response to TACE as a variable. Approach and Results Clinically relevant baseline parameters were collected for 4,621 patients with HCC treated with TACE at 19 centers in 11 countries. In some of the centers, radiological responses (as assessed by modified Response Evaluation Criteria in Solid Tumors [mRECIST]) were also accrued. The data set was divided into a training set, an internal validation set, and two external validation sets. A pre‐TACE model (“Pre‐TACE‐Predict”) and a post‐TACE model (“Post‐TACE‐Predict”) that included response were built. The performance of the models in predicting overall survival (OS) was compared with existing ones. The median OS was 19.9 months. The factors influencing survival were tumor number and size, alpha‐fetoprotein, albumin, bilirubin, vascular invasion, cause, and response as assessed by mRECIST. The proposed models showed superior predictive accuracy compared with existing models (the hepatoma arterial embolization prognostic score and its various modifications) and allowed for patient stratification into four distinct risk categories whose median OS ranged from 7 months to more than 4 years. Conclusions A TACE‐specific and extensively validated model based on routinely available clinical features and response after first TACE permitted patient‐level prognostication.

Current strategies for the treatment of intermediate and advanced hepatocellular carcinoma

“…The score has been internationally validated and bears the advantage of easy applicability and simplicity. A limitation of the score is that it does not permit patient-level prognostication; this limitation was recently met by Johnson and colleagues who developed a TACE-specific model based on routinely available clinical features [10]. In addition to the parameters included in the HAP score, this score considers further factors that influence survival, such as tumor number, vascular invasion and etiology of the underlying liver disease.…”

“…The optimal number of TACE sessions to reach the best response in an individual is not well defined and in clinical practice it is recommended that two TACE sessions can be performed based on observations that patients who do not respond to the first TACE may achieve a response after a second course [17,18]. In contrast to patients who experience a response after TACE, there is meanwhile convincing evidence that patients that only achieve disease stabilization have a poor prognosis and will not benefit from additional TACE treatments [10]. A switch to systemic therapies should therefore be considered in patients whose disease is refractory to TACE and/or with an early recurrence of new lesions.…”

Deep Learning Predicts Overall Survival of Patients With Unresectable Hepatocellular Carcinoma Treated by Transarterial Chemoembolization Plus Sorafenib

“…Given these factors, necrosis may emerge in HCCs, which might make it a predictor of prognosis. In the heat map, the general red area almost covered the entire tumor, which suggested that the deep learning signature could capture global features including the tumor size, which is a predictor of poor prognosis in HCC (47,48).…”

Initial treatment response to transarterial chemoembolization as a predictive factor for Child–Pugh class deterioration prior to refractoriness in hepatocellular carcinoma

“…According to several previous studies, the response assessment after initial TACE could be a significant surrogate marker for accurate prognostication in patients with repeated TACE. [27][28][29][30][31] In addition, the Assessment for Retreatment with TACE (ART) score, which is a scoring system including tumor response to initial TACE, was proposed to aid in selecting retreatment strategies. [32][33][34] The ART score is useful to identify patients who would not benefit from additional TACE and who should be converted to systemic therapy.…”