The Early Decline of α-Fetoprotein and Des-γ-Carboxy Prothrombin Predicts the Response of Hepatic Arterial Infusion Chemotherapy in Hepatocellular Carcinoma Patients

Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma

Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.

Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma

Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.

Cost-effectiveness and prognostic model of hepatic arterial infusion chemotherapy for hepatocellular carcinoma with high tumor burden and/or Vp4 tumor thrombus compared with sorafenib: a post-hoc analysis of the FOHAIC-1 trial

OBJECTIVES

The phase III FOHAIC-1 trial revealed that hepatic arterial infusion of chemotherapy (HAIC) improved overall survival compared to sorafenib in the high-risk hepatocellular carcinoma (HCC). This study therefore set out to evaluate the cost-effectiveness and establish a prognostic clinico-radiological score of HAIC.

MATERIALS AND METHODS

A total of 409 patients with high-risk HCC who received HAIC between 2014 and 2020 were included. A Markov model was applied in the cost-effectiveness analysis using data from the FOHAIC-1 trial. In prognosis analysis, a clinico-radiological score was developed using a Cox-regression model and subsequently confirmed in the internal validation and test cohorts. The area under the curve from receiver operator characteristic analysis was used to assess the performance of the clinico-radiological score.

RESULTS

HAIC resulted in an incremental cost-effectiveness ratio of $10190.41/quality-adjusted life years compared to sorafenib, which was lower than the willingness-to-pay threshold. Probabilistic sensitivity analysis predicted a ≥99.9% probability that the incremental cost-effectiveness ratio was below the willingness-to-pay. The Cox analysis identified five factors, namely extrahepatic metastasis (m), arterial enhancing type (a), tumor number (nu), albumin-bilirubin index (a), and involved lobe (l), which together comprise the clinico-radiological score (HAIC-manual). Patients were classified into three groups based on the number of factors present, with cutoffs at 2 and 4 factors. The stratified median overall survival for these groups were 21.6, 10.0, and 5.9 months, respectively ( P <0.001). These findings were verified through internal validation and test cohorts with a significance level of P ≤0.01. The time-dependent area under the curve from receiver operator characteristic for the ability of the HAIC-manual to predict survival in 1, 2, and 3 years were 0.71, 0.76, and 0.78, which significantly outperformed existing staging systems.

CONCLUSION

HAIC is a promising and cost-effective strategy for patients with high-risk HCC. The clinico-radiological score may be a simple prognostic tool for predicting HAIC treatment.

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram

OBJECTIVES

Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obtain objective response (OR) to HAIC preoperatively remains a challenge, we aimed to develop an automatic and non-invasive model for predicting HAIC response.

METHODS

A total of 458 patients with Ad-HCC who underwent HAIC were retrospectively included from three hospitals (310 for training, 77 for internal validation, and 71 for external validation). The deep learning and radiomic features were extracted from the automatically segmented liver region on contrast-enhanced computed tomography images. Then, a deep learning radiomic nomogram (DLRN) was constructed by integrating deep learning scores, radiomic scores, and significant clinical variables with multivariate logistic regression. Model performance was assessed by AUC and Kaplan-Meier estimator.

RESULTS

After automatic segmentation, only a few modifications were needed (less than 30 min for 458 patients). The DLRN achieved an AUC of 0.988 in the training cohort, 0.915 in the internal validation cohort, and 0.896 in the external validation cohort, respectively, outperforming other models in HAIC response prediction. Moreover, survival risk stratification was also successfully performed by the DLRN. The overall survival (OS) of the predictive OR group was significantly longer than that of the predictive non-OR group (median OS: 26.0 vs. 12.3 months, p < 0.001).

CONCLUSIONS

The DLRN provided a satisfactory performance for predicting HAIC response, which is essential to identify Ad-HCC patients for HAIC and may potentially benefit personalized pre-treatment decision-making.

CLINICAL RELEVANCE STATEMENT

This study presents an accurate and automatic method for predicting response to hepatic arterial infusion chemotherapy in patients with advanced hepatocellular carcinoma, and therefore help in defining the best candidates for this treatment.

KEY POINTS

• Deep learning radiomic nomogram (DLRN) based on automatic segmentation of CECT can accurately predict hepatic arterial infusion chemotherapy (HAIC) response of advanced HCC patients. • The proposed prediction model can perform survival risk stratification and is an easy-to-use tool for personalized pre-treatment decision-making for advanced HCC patients.

Short Half-Life of Des-γ-Carboxy Prothrombin Is a Superior Factor for Early Prediction of Outcomes of Hepatocellular Carcinoma Treated with Radiofrequency Ablation

BACKGROUND

The role of des-γ-carboxy prothrombin (DCP) in patients undergoing radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC) needs to be clarified.

MATERIALS AND METHODS

174 HCC patients that underwent RFA were enrolled. We calculated the HLs of DCP from the available values before and on first day after ablation and assessed the correlation between HLs of DCP and RFA efficacy.

RESULTS

Of 174 patients, 63 with pre-ablation DCP concentrations of ≥80 mAU/mL were analyzed. The ROC analysis showed the optimal cut-off value of HLs of DCP for predicting RFA response was 47.5 h. Therefore, we defined short HLs of DCP < 48 h as a predictor of favorable treatment response. Of 43 patients with a complete radiological response, 34 (79.1%) had short HLs of DCP. In 36 patients with short HLs of DCP, 34 (94.4%) had a complete radiologic response. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 79.1%, 90.0%, 82.5%, 94.4%, and 66.7%. During the 12-month follow-up, patients who had short HLs of DCP had a better disease-free survival rate than patients with long HLs of DCP (p < 0.001).

CONCLUSIONS

Short HLs of DCP < 48 h calculated on the first day post-RFA are a useful predictor for treatment response and recurrence-free survival after RFA.

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.

DEB-TACE combined with hepatic artery infusion chemotherapy might be an affordable treatment option for advanced stage of HCC

Alternative treatment modalities are necessary because of the low response rates and unsuitability of molecular-targeted agents (MTA) and/or immune checkpoint inhibitors (iCIs) in HCC patients. Therefore, we analyzed whether drug-eluting beads (DEB)-transcatheter arterial chemoembolization (TACE) with low-dose-FP (Ultra-FP) therapy could improve the efficacy and safety of treatment in difficult-to-treat HCC patients, especially those with advanced stage HCC. From November 2017 to April 2021, 118 consecutive patients with non-resectable difficult-to-treat HCC were included in this study. All patients were treated with Ultra-FP therapy. After the weak DEB-TACE procedure, we administered low-dose FP for 2 weeks followed by resting for 4 weeks. The numbers of HCC patients CR/PR/SD/PD induced by Ultra-FP therapy were 36/52/17/13 (Modified RECIST) patients, respectively. The objective response rate of Ultra-FP therapy was 74.6% (88/118 patients). Tumor marker reduction was observed in 81.4% (96/118 patients). The objective response rate (ORR) in the HCC patients with portal vein tumor thrombosis (PVTT) was 75% (18/24 patients). Median overall survival (mOS) of all included HCC patients was 738 days. The mOS of HCC patients with PVTT (-)/PVTT (+) was 816 days/718 days. The proportion of patients based on ALBI grade system was not significantly different between pre- and after 3 course Ultra-FP therapy. Ultra-FP therapy might be an affordable treatment option for difficult-to-treat advanced HCC. ORR and overall survival after receiving Ultra-FP therapy were remarkable in comparison to various kinds of systemic therapy including MTA and iCIs.

Arterial Chemotherapy of Oxaliplatin Plus Fluorouracil Versus Sorafenib in Advanced Hepatocellular Carcinoma: A Biomolecular Exploratory, Randomized, Phase III Trial (FOHAIC-1)

PURPOSE

Interventional hepatic arterial infusion chemotherapy of infusional fluorouracil, leucovorin, and oxaliplatin (HAIC-FO) displayed an encouraging safety profile and antitumor activity in a previous phase II trial and a propensity-score-matching study involving patients with locally advanced hepatocellular carcinoma (HCC).

METHODS

In this open-label, phase III trial, patients with advanced HCC, previously untreated with systemic therapy, were randomly assigned in a 1:1 ratio to receive HAIC-FO or sorafenib. The primary end point was overall survival (OS) in the intention-to-treat population. An exploratory model for predicting the efficacy of HAIC-FO on the basis of genomic sequencing was developed.

RESULTS

Between May 2017 and May 2020, 262 patients were randomly assigned. The median tumor size was 11.2 cm (interquartile range, 8.5-13.7 cm). Macrovascular invasion was present in 65.6%, and the percentage of patients with > 50% tumor volume involvement of the liver and/or Vp-4 portal vein tumor thrombosis was 49.2%. At data cutoff (October 31, 2020), median OS was 13.9 months for HAIC-FO and 8.2 for sorafenib (hazard ratio [HR] 0.408; 95% CI, 0.301 to 0.552; P < .001). Tumor downstaging occurred in 16 (12.3% of 130) patients receiving HAIC-FO, including 15 receiving curative surgery or ablation, and finally achieving a median OS of 20.8 months, with a 1-year OS rate of 93.8%. In high-risk subpopulations, OS was significantly longer with HAIC-FO than with sorafenib (10.8 months v 5.7 months; HR 0.343; 95% CI, 0.219 to 0.538; P < .001). A newly developed 15-mutant-gene prediction model identified 83% of patients with response to HAIC-FO. HAIC-FO responders had longer OS than HAIC-FO nonresponders (19.3 months v 10.6 months; HR 0.323; 95% CI, 0.186 to 0.560; P = .002).

CONCLUSION

HAIC-FO achieved better survival outcomes than sorafenib in advanced HCC, even in association with a high intrahepatic disease burden.