Body Composition Changes in Hepatocellular Carcinoma: Prediction of Survival to Transcatheter Arterial Chemoembolization in Combination With Clinical Prognostic Factors

Impact of body composition on the prognosis of hepatocellular carcinoma patients treated with transarterial chemoembolization: A systematic review and meta-analysis

Objectives

To summarize current evidence about the influence of body composition on the prognosis of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) treatment.

Methods

Public databases were systematically searched to identify relevant studies published from the inception of the database up to May 2023. Studies that evaluated the association between body composition and clinical outcomes in HCC patients who underwent TACE were included. A pre-designed table was applied to summarize relevant information. Meta-analysis was performed to estimate the association of body composition with overall survival.

Results

Fourteen studies were included in this review, including 3631 patients (sample size range: 56-908, median 186). All body composition measurements (including skeletal muscle area, visceral and subcutaneous adipose area, and bone mineral density) were based on computer tomography. The commonly used parameter was skeletal muscle index at 3rd lumbar vertebra level (8/14). Three studies evaluated the correlations of body composition changes with the prognosis after TACE. Most studies (12/14) identified body composition parameters as an independent indicator for overall survival, progression-free survival, and treatment response rate. The hazard ratio of different body composition parameters ranged from 1.01 to 2.88, and hazard ratio of body composition changes ranged from 1.88 to 5.93. The pooled hazard ratio of sarcopenia for overall survival was 1.38 (95 %CI: 1.20-1.58).

Conclusions

Body composition seems to be an important prognostic factor for a poorer clinical outcome after TACE treatment in patients with hepatocellular carcinoma. Future prospective studies with a larger sample size are required to confirm these findings.

Registration study

This study has been prospectively registered at the PROSPERO platform (https://www.crd.york.ac.uk/prospero/) with the registration No. CRD42022345602.

Nomograms combining computed tomography-based body composition changes with clinical prognostic factors to predict survival in locally advanced cervical cancer patients

OBJECTIVE

To explore the value of body composition changes (BCC) measured by quantitative computed tomography (QCT) for evaluating the survival of patients with locally advanced cervical cancer (LACC) underwent concurrent chemoradiotherapy (CCRT), nomograms combined BCC with clinical prognostic factors (CPF) were constructed to predict overall survival (OS) and progression-free survival (PFS).

METHODS

Eighty-eight patients with LACC were retrospectively selected. All patients underwent QCT scans before and after CCRT, bone mineral density (BMD), subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), paravertebral muscle area (PMA) were measured from two sets of computed tomography (CT) images, and change rates of these were calculated.

RESULTS

Multivariate Cox regression analysis showed ΔBMD, ΔSFA, SCC-Ag, LNM were independent factors for OS (HR = 3.560, 5.870, 2.702, 2.499, respectively, all P < 0.05); ΔPMA, SCC-Ag, LNM were independent factors for PFS (HR = 2.915, 4.291, 2.902, respectively, all P < 0.05). Prognostic models of BCC combined with CPF had the highest predictive performance, and the area under the curve (AUC) for OS and PFS were 0.837, 0.846, respectively. The concordance index (C-index) of nomograms for OS and PFS were 0.834, 0.799, respectively. Calibration curves showed good agreement between the nomograms' predictive and actual OS and PFS, decision curve analysis (DCA) showed good clinical benefit of nomograms.

CONCLUSION

CT-based body composition changes and CPF (SCC-Ag, LNM) were associated with survival in patients with LACC. The prognostic nomograms combined BCC with CPF were able to predict the OS and PFS in patients with LACC reliably.

Development and External Validation of a Nomogram Including Body Composition Parameters for Predicting Early Recurrence of Hepatocellular Carcinoma After Hepatectomy

RATIONALE AND OBJECTIVES

Body composition, including adipose and muscle tissues, evaluated by computer tomography is correlated with the prognosis of hepatocellular carcinoma (HCC). However, its relationship with early recurrence (ER) remains unclear. This study aimed at establishing and validating a nomogram based on body composition and clinicopathological indices to predict ER of HCC.

MATERIALS AND METHODS

One hundred ninety-five patients from institution A formed the training cohort and internal validation cohort, and 50 patients from institution B formed the external validation cohort. Independent predictors of ER were identified using LASSO and Cox regression analyses. The performance of nomogram was evaluated using the calibration curve, concordance index (C-index), area under the curve (AUC), and decision curve analysis (DCA).

RESULTS

After data screening, the nomogram was constructed using eight independent predictors of ER, including the tumor size, alpha fetoprotein, body mass index, Edmondson Steiner grade, visceral adipose tissue radiodensity, intermuscular adipose tissue index, intramuscular adipose tissue content, and skeletal muscle area. The calibration curve exhibited excellent concordances, with C-indices of 0.808 (95%CI: 0.771-0.860), 0.802 (95%CI: 0.747-0.942), and 0.804 (95%CI: 0.701-0.861) in training, internal validation, and external validation cohorts, respectively. In addition, compared to conventional staging systems and pure clinical model, the nomogram exhibited a higher AUC and wider range of threshold probabilities in DCA, which indicated better discriminative ability and greater clinical benefit. Finally, patients with nomogram scores of <183.07, 183.07-243.09, and >243.09 were considered to have low, moderate, and high risks of ER, respectively.

CONCLUSION

The nomogram exhibits excellent ER predictive ability for patients with HCC who underwent hepatectomy.

Model containing sarcopenia and visceral adiposity can better predict the prognosis of hepatocellular carcinoma: a multicenter study

AIM

This study aimed to explore whether the addition of sarcopenia and visceral adiposity could improve the accuracy of model predicting progression-free survival (PFS) in hepatocellular carcinoma (HCC).

METHODS

In total, 394 patients with HCC from five hospitals were divided into the training and external validation datasets. Patients were initially treated by liver resection or transarterial chemoembolization. We evaluated adipose and skeletal muscle using preoperative computed tomography imaging and then constructed three predictive models, including metabolic (ModelMA), clinical-imaging (ModelCI), and combined (ModelMA-CI) models. Their discrimination, calibration, and decision curves were compared, to identify the best model. Nomogram and subgroup analysis was performed for the best model.

RESULTS

ModelMA-CI containing sarcopenia and visceral adiposity had good discrimination and calibrations (integrate area under the curve for PFS was 0.708 in the training dataset and 0.706 in the validation dataset). ModelMA-CI had better accuracy than ModelCI and ModelMA. The performance of ModelMA-CI was not affected by treatments or disease stages. The high-risk subgroup (scored > 198) had a significantly shorter PFS (p < 0.001) and poorer OS (p < 0.001).

CONCLUSIONS

The addition of sarcopenia and visceral adiposity improved accuracy in predicting PFS in HCC, which may provide additional insights in prognosis for HCC in subsequent studies.

Overexpression of CASC19 contributes to tumor progression and predicts poor prognosis after radical resection in hepatocellular carcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) have been implicated as functional molecules in hepatocellular carcinoma (HCC) progression. The present research aimed to investigate the levels of LncRNA cancer susceptibility candidate gene 19 (CASC19) in HCC tissues and cell lines and to explore its potential role in the diagnosis and prognosis of HCC.

METHODS

HCC tissues and cell lines were collected to assess the levels of CASC19 by real-time quantitative reverse transcription PCR (RT-qPCR). The prognostic value of CASC19 was evaluated using the Kaplan-Meier method and Cox regression analysis. The functional role of CASC19 in regulating HCC cell proliferation, migration, and invasion was evaluated by Cell Counting Kit-8 (CCK-8) and Transwell analysis. The potential targeted miR-140-5p of CASC19 was confirmed by a dual-luciferase reporter assay.

RESULTS

High CASC19 expression positively correlated with tumor size, differentiation, and TNM stage in HCC patients (P < 0.05). Patients with high CASC19 expression have a poorer survival prognosis and are prone to relapse compared to those with low CASC19. miR-140-5p, a target miRNA for CASC19, negatively correlated with CASC19 levels in tumor tissues. Reduced CASC19 levels attenuated cell proliferation, migration, and invasion, but this attenuation was reversed by suppression of miR-140-5p.

CONCLUSION

Up-regulated CASC19 may serve as a biomarker for predicting poor prognosis in HCC patients. In vitro, overexpressed CASC19 promoted the progression of HCC, indicating that CASC19 may be a possible therapeutic target for the treatment of HCC.

Association between sarcopenia and clinical outcomes in patients with hepatocellular carcinoma: an updated meta-analysis

Although numerous studies have reported the association between sarcopenia and the prognosis of hepatocellular carcinoma (HCC) patients, there is lack of a newer and more comprehensive meta-analysis. Herein, a comprehensive literature search was performed on PubMed, Web of Science, the Cochrane Library, and Embase databases to identify relevant studies published up to February 2022. The outcomes were overall survival (OS), recurrence, progression-free survival, tumor response, severe postoperative complications, and toxicity of drugs. A total of 57 studies involving 9790 HCC patients were included in the meta-analysis. The pooled prevalence of sarcopenia in HCC patients was 41.7% (95% CI 36.2-47.2%). Results demonstrated that sarcopenia was significantly associated with impaired OS (HR: 1.93, 95% CI 1.73-2.17, P < 0.001), higher risk of tumor recurrence (HR: 1.75, 95% CI 1.56-1.96, P < 0.001), lower objective response rate (OR: 0.37 95% CI 0.17-0.81, P = 0.012), and more drug-related adverse events (OR: 2.23, 95% CI 1.17-4.28, P = 0.015) in HCC patients. The subgroup analyses revealed that the OS of patients at the early stage of tumor was more severely affected by sarcopenia than for patients at other stages. Moreover, the presence of cirrhosis and Child Pugh class B increased the hazard of mortality from sarcopenia. This study has shown that sarcopenia is highly associated with poor prognosis in HCC patients. In addition, cirrhosis and poor liver functional reserve increase the danger of sarcopenia. OS was more impaired in HCC patients with sarcopenia at early stage of tumor than at other tumor stages.

Low bone mineral density is a prognostic factor for elderly patients with HCC undergoing TACE: results from a multicenter study

OBJECTIVES

Low bone mineral density (BMD) was recently identified as a novel risk factor for patients with hepatocellular carcinoma (HCC). In this multicenter study, we aimed to validate the role of BMD as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE).

METHODS

This retrospective multicenter trial included 908 treatment-naïve patients with HCC who were undergoing TACE as a first-line treatment, at six tertiary care centers, between 2010 and 2020. BMD was assessed by measuring the mean Hounsfield units (HUs) in the midvertebral core of the 11^th thoracic vertebra, on contrast-enhanced computer tomography performed before treatment. We assessed the influence of BMD on median overall survival (OS) and performed multivariate analysis including established estimates for survival.

RESULTS

The median BMD was 145 HU (IQR, 115-175 HU). Patients with a high BMD (≥ 114 HU) had a median OS of 22.2 months, while patients with a low BMD (< 114 HU) had a lower median OS of only 16.2 months (p < .001). Besides albumin, bilirubin, tumor number, and tumor diameter, BMD remained an independent prognostic factor in multivariate analysis.

CONCLUSIONS

BMD is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. The integration of BMD into novel scoring systems could potentially improve survival prediction and clinical decision-making.

KEY POINTS

• Bone mineral density can be easily assessed in routinely acquired pre-interventional computed tomography scans. • Bone mineral density is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. • Thus, bone mineral density is a novel imaging biomarker for prognosis prediction in elderly patients with HCC undergoing TACE.

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.