Incorporating albumin-bilirubin grade and up-to-seven criteria to predict outcomes of patients with intermediate stage hepatocellular carcinoma after transarterial (chemo)embolization

Clinical consensus statement: Establishing the roles of locoregional and systemic therapies for the treatment of intermediate-stage hepatocellular carcinoma in Canada

BACKGROUND

Hepatocellular carcinoma (HCC) a leading cause of cancer mortality worldwide and approximately one-third of patients present with intermediate-stage disease. The treatment landscape of intermediate-stage HCC is rapidly evolving due to developments in local, locoregional and systemic therapies. Treatment recommendations focused on this heterogenous disease stage and that take into account the Canadian reality are lacking. To address this gap, a pan-Canadian group of experts in hepatology, transplant, surgery, radiation therapy, nuclear medicine, interventional radiology, and medical oncology came together to develop consensus recommendations on management of intermediate-stage HCC relevant to the Canadian context.

METHODS

A modified Delphi framework was used to develop consensus statements with strengths of recommendation and supporting levels of evidence graded using the AHA/ACC classification system. Tentative consensus statements were drafted based on a systematic search and expert input in a series of iterative feedback cycles and were then circulated via online survey to assess the level of agreement.

RESULTS & CONCLUSION

The pre-defined ratification threshold of 80 % agreement was reached for all statements in the areas of multidisciplinary treatment (n = 4), intra-arterial therapy (n = 14), biologics (n = 5), radiation therapy (n = 3), surgical resection and transplantation (n = 7), and percutaneous ablative therapy (n = 4). These generally reflected an expansion in treatment options due to developments in previously established or emergent techniques, introduction of new and more active therapies and increased therapeutic flexibility. These developments have allowed for greater treatment tailoring and personalization as well as a paradigm shift toward strategies with curative intent in a wider range of disease settings.

Prognostic Significance of Serum Albumin Level and Albumin-Based Mono- and Combination Biomarkers in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer. Although many surgical and nonsurgical therapeutic options have been established for treating HCC, the overall prognosis for HCC patients receiving different treatment modalities remains inadequate, which causes HCC to remain among the most life-threatening human cancers worldwide. Therefore, it is vitally important and urgently needed to develop valuable and independent prognostic biomarkers for the early prediction of poor prognosis in HCC patients, allowing more time for more timely and appropriate treatment to improve the survival of patients. As the most abundant protein in plasma, human serum albumin (ALB) is predominantly expressed by the liver and exhibits a wide variety of essential biological functions. It has been well recognized that serum ALB level is a significant independent biomarker for a broad spectrum of human diseases including cancer. Moreover, ALB has been commonly used as a potent biomaterial and therapeutic agent in clinical settings for the treatment of various human diseases. This review provides a comprehensive summary of the evidence from the up-to-date published literature to underscore the prognostic significance of serum ALB level and various ALB-based mono- and combination biomarkers in the prediction of the prognosis of HCC patients after treatment with different surgical, locoregional, and systemic therapies.

Prediction of therapeutic response of unresectable hepatocellular carcinoma to hepatic arterial infusion chemotherapy based on pretherapeutic MRI radiomics and Albumin-Bilirubin score

Purpose

To construct and validate a combined nomogram model based on magnetic resonance imaging (MRI) radiomics and Albumin-Bilirubin (ALBI) score to predict therapeutic response in unresectable hepatocellular carcinoma (HCC) patients treated with hepatic arterial infusion chemotherapy (HAIC).

Methods

The retrospective study was conducted on 112 unresectable HCC patients who underwent pretherapeutic MRI examinations. Patients were randomly divided into training (n = 79) and validation cohorts (n = 33). A total of 396 radiomics features were extracted from the volume of interest of the primary lesion by the Artificial Kit software. The least absolute shrinkage and selection operator (LASSO) regression was applied to identify optimal radiomic features. After feature selection, three models, including the clinical, radiomics, and combined models, were developed to predict the non-response of unresectable HCC to HAIC treatment. The performance of these models was evaluated by the receiver operating characteristic curve. According to the most efficient model, a nomogram was established, and the performance of which was also assessed by calibration curve and decision curve analysis. Kaplan–Meier curve and log-rank test were performed to evaluate the Progression-free survival (PFS).

Results

Using the LASSO regression, we ultimately selected three radiomics features from T2-weighted images to construct the radiomics score (Radscore). Only the ALBI score was an independent factor associated with non-response in the clinical model (P = 0.033). The combined model, which included the ALBI score and Radscore, achieved better performance in the prediction of non-response, with an AUC of 0.79 (95% CI 0.68–0.90) and 0.75 (95% CI 0.58–0.92) in the training and validation cohorts, respectively. The nomogram based on the combined model also had good discrimination and calibration (P = 0.519 for the training cohort and P = 0.389 for the validation cohort). The Kaplan–Meier analysis also demonstrate that the high-score patients had significantly shorter PFS than the low-score patients (P = 0.031) in the combined model, with median PFS 6.0 vs 9.0 months.

Conclusion

The nomogram based on the combined model consisting of MRI radiomics and ALBI score could be used as a biomarker to predict the therapeutic response of unresectable HCC after HAIC.