A Nomogram-Based Prognostic Model for Advanced Hepatocellular Carcinoma Patients Treated with Sorafenib: A Multicenter Study

Establishing and Externally Validating a Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score-Based Nomogram for Predicting Early Recurrence in BCLC Stage 0/A Hepatocellular Carcinoma Patients After Radical Liver Resection: A Multi-Center Study

Purpose

Early recurrence (ER) is associated with poor prognosis in hepatocellular carcinoma (HCC). In this study, we developed and externally validated a nomogram based on the hemoglobin, albumin, lymphocytes, and platelets (HALP) score to predict ER for patients with BCLC stage 0/A HCC who underwent radical liver resection.

Patients and Methods

A total of 808 BCLC stage 0/A HCC patients from six hospitals were included in this study, and they were assigned to a training cohort (n = 500) and an external validation cohort (n = 308). We used univariate and multivariate Cox regression analysis to identify the independent risk factors for disease-free survival (DFS). We also established and externally validated a nomogram based on these risk predictors. The nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), the concordance index (C-index), the calibration curve, decision curve analysis (DCA), and Kaplan‒Meier analysis.

Results

Multivariate COX regression showed that HBV DNA ≥10,000 IU/mL (P < 0.001), HALP score ≤38.20 (P < 0.001), tumor size (P = 0.003), clinically significant portal hypertension (P = 0.001), Edmondson-Steiner grade (III-IV) (P = 0.007), satellite nodules (P < 0.001), and MVI (P = 0.001) were independent risk factors for post-operative tumor recurrence. The AUC of our nomogram for predicting the 2-year and 5-year DFS was 0.756 and 0.750, respectively, in the training cohort and 0.764 and 0.705, respectively, in the external validation cohort. We divided the patients into low-, intermediate- and high-risk groups according to the risk score calculated by the nomogram. There were statistically significant differences in the DFS and overall survival (OS) among the three groups of patients (P < 0.001).

Conclusion

We developed and externally validated a new nomogram, which is accurate and can predict ER in BCLC stage 0/A HCC patients after curative liver resection.

Preoperative aspartate aminotransferase to albumin ratio correlates with tumor characteristics and predicts outcome of hepatocellular carcinoma patients after curative hepatectomy: a multicenter study

Aims

This study aimed to evaluate the clinical significance of the preoperative aminotransferase to albumin ratio (AAR) in patients with hepatocellular carcinoma (HCC) after hepatectomy.

Methods

From five hospitals, a total of 991 patients with HCC admitted between December 2014 and December 2019 were included as the primary cohort and 883 patients with HCC admitted between December 2010 and December 2014 were included as the validation cohort. The X-tile software was conducted to identify the optimal cut-off value of AAR.

Results

In the primary cohort, the optimal cut-off value of the AAR was defined as 0.7 and 1.6, respectively. Compared to patients with AAR 0.7–1.6, those with AAR > 1.6 showed significantly worse overall survival (OS) and RFS, whereas those with AAR < 0.7 showed significantly better OS and RFS (all p < 0.001). Pathologically, patients with AAR > 1.6 had more aggressive tumour characteristics, such as larger tumour size, higher incidence of microvascular invasion, and severe histologic activity, and higher AFP level than patients with AAR < 0.7. Consistently, the abovementioned clinical significance of AAR was confirmed in the validation cohort.

Conclusions

A high AAR was significantly correlated with advanced tumours and severe hepatic inflammation, and a worse prognosis of HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12893-022-01751-4.

The Prognostic Value of Baseline Clinical and Radiologic Imaging Features in Patients with Unresectable Hepatocellular Carcinoma Treated with Atezolizumab Plus Bevacizumab

Purpose

To identify prognostic clinical and radiologic features in patients with unresectable hepatocellular carcinoma (HCC) treated with atezolizumab plus bevacizumab.

Patients and Methods

Clinical and imaging records of patients with unresectable HCC were retrospectively reviewed, and baseline features were recorded. Patients’ records and imaging studies were used to determine the patients’ overall survival (OS) and progression-free survival (PFS). Univariate and multivariate analyses were performed to determine prognostic features. Subanalyses of treatment-naïve patients (who never received local or systemic therapy) and previously treated patients were also performed.

Results

Fifty-five patients were included in the final analysis, 23 (41.8%) of whom were treatment naïve. The median PFS and OS for the entire cohort were 3.0 months and 7.9 months. The 3-, 6- and 12-month OS rates were 85.5%, 79.8% and 45.7%, respectively. The 3-, 6- and 12-month PFS rates were 50.1%, 41.2% and 20.1%, respectively. On multivariate analysis, independent prognostic features for poor PFS of the entire cohort were pleural effusions (p = 0.047, HR: 6.3; CI: 1.03–38.90) and hepatic vein tumor thrombus (p = 0.005; HR: 23.37; CI: 2.63–207.67); independent prognostic features for poor OS were ascites (p = 0.008; HR: 37.37; CI: 2.53–467.64), pleural effusion (p = 0.003; HR: 110.17; CI: 5.00–2426.54), and low (<40HU) pre-contrast attenuation on CT images (p = 0.007; HR: 0.09; CI: 0.02–0.53). On subanalysis of treatment-naïve patients, the median OS and PFS were 7.4 months and 2.8 months, respectively. The 3-, 6- and 12-month PFS rates were 43.5%, 38.6% and 24.8%, respectively. Pleural effusion was the only independent poor prognostic feature (p = 0.036; HR: 206.34; CI: 1.41–30,167.58).

Conclusion

Independent prognostic features for survival outcomes include the presence of ascites, pleural effusions, hepatic vein tumor thrombus, and HCC with low attenuation (<40 HU) on unenhanced CT images. Although several biochemical variables were significant on univariate analysis, none were independent predictors of OS or PFS.

Impact of psoas muscle index assessed by a simple measurement method on tolerability and duration of continued treatment with sorafenib in hepatocellular carcinoma patients

BACKGROUND

In this study, we investigated the impact of simple measurement of psoas muscle index (PMI) on the tolerability of sorafenib treatment of switch from sorafenib to regorafenib.

METHOD

This retrospective study enrolled 109 patients with Child-Pugh A hepatocellular carcinoma (HCC) treated with sorafenib. Pretreatment PMI was calculated by measuring and multiplying the greatest anterior/posterior and transverse diameters of the psoas muscles on axial computed tomography images at the L3 vertebral level, and normalizing the sum of bilateral psoas muscle areas by the square of the height in meters. We, then, statistically analyzed the association between PMI and adverse events (AEs) to treatment, tolerability of sorafenib, time to treatment failure (TTF), and prognosis in patients stratified according to PMI.

RESULT

Patients were divided into high PMI (n = 41) and low PMI (n = 68) groups based on the cutoff PMI values (men: 7.04 cm2/m2; women: 4.40 cm2/m2) determined by receiver operating characteristic curve analysis to determine sorafenib tolerability. Frequencies of all types of severe AEs were higher in the low PMI group (50.0%) than in the high PMI group (29.3%; P = 0.045). The high PMI group (51.2%) had greater tolerance to sorafenib than the low PMI group (25.0%; P = 0.007). Moreover, in multivariable analysis, PMI was associated with sorafenib tolerability (odds ratio 0.26; P = 0.008) and was a prognostic factor affecting TTF (hazard ratio 1.77; P = 0.021).

CONCLUSION

PMI might be a predictive marker of tolerance to treatment and TTF in HCC patients receiving sorafenib treatment.

Dynamics of endothelial progenitor cells in patients with advanced hepatocellular carcinoma

BACKGROUND AND AIMS

Circulating endothelial progenitor cells (EPC) predict tumor vascularization and disease progression, but limited information is available on their dynamics in hepatocellular carcinoma (HCC) undergoing systemic treatment.

METHODS

We prospectively analyzed different populations of EPC in 16 patients with advanced HCC receiving sorafenib. Patients were studied before therapy (T0, n = 16) and after two (T2, n = 12) and eight weeks (T8, n = 8), using high-performance flow-cytometry. The tumor response at T8 was categorized as progressive disease (PD) or clinical benefit (CB, all other responses).

RESULTS

At T0, higher levels of CD34⁺CD133⁺KDR⁺ and CD34⁺KDR⁺ were observed in patients with alpha-fetoprotein ≥400 ng/ml or non-viral liver disease, whereas CD34⁺CD133⁺KDR⁺ cells were virtually absent in patients with vascular invasion. CD34⁺KDR⁺ and CD34⁺CD133⁺KDR⁺ were directly correlated with platelet count. Frequencies of all populations of EPC declined in patients receiving sorafenib. Levels of CD34⁺CD133⁺ were higher at T0 in patients with CB compared to patients with PD. In patients belonging to the CB group CD34⁺KDR⁺ cells at T0 were directly correlated to platelet count.

CONCLUSION

In patients with advanced HCC, EPC are directly correlated with platelet count, suggesting a common activation of selected bone marrow pathways. Levels of a CD34⁺KDR⁺ are higher at baseline in patients responding to sorafenib.

Myosteatosis can Predict Unfavorable Outcomes in Advanced Hepatocellular Carcinoma Patients Treated With Hepatic Artery Infusion Chemotherapy and Anti-PD-1 Immunotherapy

Aim

To evaluate the feasibility of computed tomography (CT) - derived measurements of body composition parameters to predict the risk factor of non-objective response (non-OR) in patients with hepatocellular carcinoma (HCC) undergoing anti-PD-1 immunotherapy and hepatic artery infusion chemotherapy (immune-HAIC).

Methods

Patients with histologically confirmed HCC and treated with the immune-HAIC were retrospectively recruited between June 30, 2019, and July 31, 2021. CT-based estimations of body composition parameters were acquired from the baseline unenhanced abdominal CT images at the level of the third lumbar vertebra (L3) and were applied to develop models predicting the probability of OR. A myosteatosis nomogram was built using the multivariate logistic regression incorporating both myosteatosis measurements and clinical variables. Receiver operating characteristic (ROC) curves assessed the performance of prediction models, including the area under the curve (AUC). The nomogram’s performance was assessed by the calibration, discrimination, and decision curve analyses. Associations among predictors and gene mutations were also examined by correlation matrix analysis.

Results

Fifty-two patients were recruited to this study cohort, with 30 patients having a OR status after immune-HAIC treatment. Estimations of myosteatosis parameters, like SM-RA (skeletal muscle radiation attenuation), were significantly associated with the probability of predicting OR (P=0.007). The SM-RA combined nomogram model, including serum red blood cell, hemoglobin, creatinine, and the mean CT value of visceral fat (VFmean) improved the prediction probability for OR disease with an AUC of 0.713 (95% CI, 0.75 to 0.95) than the clinical model nomogram with AUC of 0.62 using a 5-fold cross-validation methodology. Favorable clinical potentials were observed in the decision curve analysis.

Conclusions

The CT-based estimations of myosteatosis could be used as an indicator to predict a higher risk of transition to the Non-OR disease state in HCC patients treated with immune-HAIC therapy. This study demonstrated the therapeutic relevance of skeletal muscle composition assessments in the overall prediction of treatment response and prognosis in HCC patients.

The ITA.LI.CA Consortium: How multicentre collaboration helped shape the management of patients with hepatocellular carcinoma on the basis of real-world evidence

The growing diffusion of digitalisation and informatics has promoted the creation and analysis of large databases able to provide solid information. Analyses of "big data" generated by real-world practice are particularly useful for knowing incidence and mortality, disparities, temporal trends of diseases, identifying risk factors, predicting future scenarios, obtaining inputs for cost-effectiveness and treatment benefit modelling, designing new studies, and monitoring rare diseases. Although randomised controlled trials (RCTs) represent the gold-standard for generating evidence about new diagnostic, preventive or therapeutic procedures, their results should be integrated with real-world data to personalise patient management. Indeed, a substantial proportion of patients observed in field-practice have characteristics that prevent the access to RCTs or, when included, form sub-groups too small to provide robust post-hoc analyses. Furthermore, as RCTs are resource-consuming and designed to maximize the probability of success, they are generally performed in expert centres of high-income areas, excluding economically-deprived regions which could complementarily contribute to the medical progress as huge sources of real-world data. These considerations fuelled the creation in 1998 of the Italian Liver Cancer (ITA.LI.CA) consortium, with the aim to merge data of patients with hepatocellular carcinoma (HCC) managed in several centres. This cooperation permitted to analyse a multicentre, large cohort of HCC patients. Since then, the ITA.LI.CA group has progressively expanded to currently include 24 centres, and its database counts more than 9,000 patients. This article describes the history of the ITA.LI.CA consortium and presents its scientific production whose results greatly contributed to the incessant improvement of HCC management.