Prognostic value of inflammatory and nutritional markers for hepatocellular carcinoma

Symptom clusters and nutritional status in primary liver cancer patients receiving TACE

INTRODUCTION

symptom clusters (SCs) are highly prevalent among patients diagnosed with primary liver cancer. Malnutrition poses a heightened risk for a more pronounced total symptom cluster score.

OBJECTIVE

this study aimed to identify SCs and assess the nutritional status of patients undergoing transcatheter arterial chemoembolization (TACE). Furthermore, it aimed to investigate the association between nutritional status and symptom clusters.

METHODS

primary liver cancer patients who were scheduled to receive TACE were recruited. Symptoms data were collected using the MD Anderson Symptom Inventory (MDASI-C) and the Symptom Module specific to Primary Cancer (TSM-PLC). Nutritional assessment relied on the Nutritional Risk Screening-2002 (NRS-2002) and blood biochemistry. The SCs were extracted using exploratory factor analysis, while the relationship between SCs and nutritional status was evaluated using Spearman correlation analysis.

RESULTS

the study included 226 patients, four distinct symptom clusters emerged: emotional-psychological symptom cluster, upper gastrointestinal symptom cluster, post-embolization-related symptom cluster, and liver function impairment symptom cluster. 68.14 % of patients were found to be at high risk of malnutrition. Our study revealed significant differences in Scs scores between patients at risk of malnutrition and those without such risk (p < 0.050). Notably, we observed a positive correlation between NRS-2002 scores and the scores of all symptom clusters (r = 0.205 to 0.419, p < 0.001), while a negative correlation was observed between prealbumin levels and the scores of all symptom clusters (r = -0.183 to -0.454, p < 0.001).

CONCLUSION

the study highlights the high risk of malnutrition among liver cancer patients receiving TACE and the positive correlation between high malnutrition risk and Scs scores.

Development of a Nomogram Using the Inflammatory Risk Score for Prognostication in Moderate and Advanced Hepatocellular Carcinoma Associated with Hepatitis B Virus

Background

The changes in risk scores of inflammatory markers among patients diagnosed with hepatocellular carcinoma (HCC) remain unknown.

Aims

To investigate the relationship between the inflammation risk score and other contributing factors and the prognostic outcomes in patients with moderate and advanced hepatitis B virus (HBV)-related HCC.

Study Design

A retrospective cohort study.

Methods

A total of 174 patients with moderate and advanced HBV related HCC were recruited to investigate the impact of stratified inflammatory risk scores and other associated risk factors on disease prognosis. Based on the optimal cut-off values calculated by the Youden index, the patients were divided into high-risk and low-risk groups based on their inflammation risk scores.

Results

The study found a significant difference in median survival time between the low-risk and high-risk groups based on the inflammation risk score. Furthermore, the inflammation risk score, alpha-fetoprotein levels, transarterial chemoembolization treatment, and Barcelona Clinic Liver Cancer stage were identified as independent prognostic factors. The four variables were used to construct a prognostic nomogram for HCC. Subsequent evaluations using time-dependent receiver operating characteristic analysis and calibration curve tests revealed the nomogram's commendable discriminatory ability. As a result, the nomogram proved to be an effective tool for predicting survival at 2- to 4-years.

Conclusion

The inflammation risk score has been identified as a significant prognostic factor for HBV-related HCC. The development of nomogram models has provided a practical and effective tool for determining the prognosis of patients affected by HBV-related HCC.

C-reactive protein to albumin ratio predict responses to programmed cell death-1 inhibitors in hepatocellular carcinoma patients

BACKGROUND

Over the years, programmed cell death-1 (PD-1) inhibitors have been routinely used for hepatocellular carcinoma (HCC) treatment and yielded improved survival outcomes. Nonetheless, significant heterogeneity surrounds the outcomes of most studies. Therefore, it is critical to search for biomarkers that predict the efficacy of PD-1 inhibitors in patients with HCC.

AIM

To investigate the role of the C-reactive protein to albumin ratio (CAR) in evaluating the efficacy of PD-1 inhibitors for HCC.

METHODS

The clinical data of 160 patients with HCC treated with PD-1 inhibitors from January 2018 to November 2022 at the First Affiliated Hospital of Guangxi Medical University were retrospectively analyzed.

RESULTS

The optimal cut-off value for CAR based on progression-free survival (PFS) was determined to be 1.20 using x-tile software. Cox proportional risk model was used to determine the factors affecting prognosis. Eastern Cooperative Oncology Group performance status [hazard ratio (HR) = 1.754, 95% confidence interval (95%CI) = 1.045-2.944, P = 0.033], CAR (HR = 2.118, 95%CI = 1.057-4.243, P = 0.034) and tumor number (HR = 2.932, 95%CI = 1.246-6.897, P = 0.014) were independent prognostic factors for overall survival. CAR (HR = 2.730, 95%CI = 1.502-4.961, P = 0.001), tumor number (HR = 1.584, 95%CI = 1.003-2.500, P = 0.048) and neutrophil to lymphocyte ratio (HR = 1.120, 95%CI = 1.022-1.228, P = 0.015) were independent prognostic factors for PFS. Two nomograms were constructed based on independent prognostic factors. The C-index index and calibration plots confirmed that the nomogram is a reliable risk prediction tool. The ROC curve and decision curve analysis confirmed that the nomogram has a good predictive effect as well as a net clinical benefit.

CONCLUSION

Overall, we reveal that the CAR is a potential predictor of short- and long-term prognosis in patients with HCC treated with PD-1 inhibitors. If further verified, CAR-based nomogram may increase the number of markers that predict individualized prognosis.

A novel nomogram and risk classification system based on inflammatory and immune indicators for predicting prognosis of pancreatic cancer patients with liver metastases

BACKGROUND

The study determined to construct a novel predictive nomogram to access the prognosis of pancreatic cancer patients with liver metastases (PCLM).

METHODS

Medical records included clinical and laboratory variables were collected. The patients were randomly divided into training and validation cohort. First, in the training cohort, the optimal cutoff value of SII, PNI, NLR, PLR were obtained. Then the survival analysis evaluated the effects of above indices on OS. Next, univariate and multivariate analyses were used to identify the independent factors of OS. Moreover, a nomogram was constructed based on LASSO cox analysis. Additionally, the predictive efficacy of the nomogram was evaluated by ROC curve and calibration curve in the training and validation cohort. Finally, a risk stratification system based on the nomogram was performed.

RESULTS

A total of 472 PCLM patients were enrolled in the study. The optimal cutoff values of SII, PNI, PLR and NLR were 372, 43.6, 285.7143 and 1.48, respectively. By combing SII and PNI, named coSII-PNI, we divided the patients into three groups. The Kaplan-Meier curves demonstrated above indices were correlated with OS. Univariate and multivariate analyses found the independent prognostic factors of OS. Through LASSO cox analysis, coSII-PNI, PNI, NLR, CA199, CEA, chemotherapy and gender were used to construct the nomogram. Lastly, the ROC curve and calibration curve demonstrated that the nomogram can predict prognosis of PCLM patients. Significant differences were observed between high and low groups.

CONCLUSIONS

The nomogram based on immune, inflammation, nutritional status and other clinical factors can accurately predict OS of PCLM patients.

Associations of gallbladder and gallstone parameters with clinical outcomes in patients with cirrhosis

Background

Morphologic changes in the gallbladder and gallstones are common in cirrhotic patients, but their associations with outcomes of cirrhotic patients are unclear.

Methods

We retrospectively enrolled 206 cirrhotic patients and measured their gallbladder length and width, gallbladder wall thickness, presence of gallstones, and gallstones’ length and width in axial contrast-enhanced computed tomography (CT) images. X-tile software was utilized to calculate the optimal cutoff values of these parameters for evaluating survival and hepatic decompensation events in the cirrhosis group. Their associations with survival were explored by Cox regression analyses and Kaplan–Meier curve analyses. Their associations with hepatic decompensation events were evaluated by competing risk analyses and Nelson-Aalen cumulative risk curve analyses where death was a competing event.

Results

Cirrhotic patients with gallbladder length < 72 mm had a significantly higher cumulative survival rate than those with a length of ≥ 72 mm (P = 0.049 by log-rank test), but gallbladder width, gallbladder wall thickness, presence of gallstones, and gallstones’ length and width were not significantly associated with survival (P = 0.10, P = 0.14, P = 0.97, P = 0.73, and P = 0.73 by log-rank tests, respectively). Cirrhotic patients with gallbladder wall thickness < 3.4 mm had a significantly lower cumulative rate of hepatic decompensation events than those with a wall thickness of ≥ 3.4 mm (P = 0.02 by Gray’s test), but gallbladder length and width, presence of gallstones, and gallstones’ length and width were not significantly associated with hepatic decompensation events (P = 0.15, P = 0.15, P = 0.54, P = 0.76, and P = 0.54 by Gray’s tests, respectively).

Conclusion

Changes in gallbladder length and gallbladder wall thickness, rather than gallstone parameters, may be in parallel with the long-term outcomes of cirrhotic patients.

Prognostic Value of Inflammatory and Nutritional Markers for Patients With Early-Stage Poorly-to Moderately-Differentiated Cervical Squamous Cell Carcinoma

BACKGROUND

The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic inflammation response index (SIRI), and Onodera's prognostic nutritional index (OPNI) have been reported as prognostic markers for various cancers. We evaluated the prognostic value of the NLR, PLR, MLR, SII, SIRI, and OPNI for poorly-to moderately-differentiated cervical squamous cell carcinoma (CSCC).

PATIENTS AND METHODS

We retrospectively analyzed the cases of 109 patients with early-stage poorly-to moderately-differentiated CSCC who underwent radical surgery at our institution in 2014-2017. The optimal cutoff points for the NLR, PLR, MLR, SII, SIRI, and OPNI were determined by receiver operating characteristic curves. Overall survival was analyzed by the Kaplan-Meier method. We performed a multivariate analysis using the Cox proportional hazard regression model to determine the independent prognostic indicators for early-stage poorly-to moderately-differentiated CSCC.

RESULTS

The appropriate cutoff points were: NLR, 1.72; PLR, 111.96; MLR, .24; SII, 566.23; SIRI, 1.38; and OPNI, 52.68. The OS of the patients with a high OPNI (P = .04), low SII (P = .03), or low SIRI (P = .01) was significantly better. The uni- and multivariate analyses identified only the OPNI as an independent prognostic marker for early-stage poorly-to moderately-differentiated CSCC (P = .04 and P = .02).

CONCLUSION

The OPNI is an independent prognostic marker for early-stage poorly-to moderately-differentiated CSCC; the NLR, PLR, MLR, SII, and SIRI are not.

Prognostic factors for disease-free survival in postoperative patients with hepatocellular carcinoma and construction of a nomogram model

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has a high risk of invasion and metastasis along with a poor prognosis.

AIM

To investigate the independent predictive markers for disease-free survival (DFS) in patients with HCC and establish a trustworthy nomogram.

METHODS

In this study, 445 patients who were hospitalized in The First Affiliated Hospital of Anhui Medical College between December 2009 and December 2014 were retrospectively examined. The survival curve was plotted using the Kaplan–Meier method and survival was determined using the log-rank test. To identify the prognostic variables, multivariate Cox regression analyses were carried out. To predict the DFS in patients with HCC, a nomogram was created. C-indices and receiver operator characteristic curves were used to evaluate the nomogram's performance. Decision curve analysis (DCA) was used to evaluate the clinical application value of the nomogram.

RESULTS

Longer DFS was observed in patients with the following characteristics: elderly, I–II stage, and no history of hepatitis B. The calibration curve showed that this nomogram was reliable and had a higher area under the curve value than the tumor node metastasis (TNM) stage. Moreover, the DCA curve revealed that the nomogram had good clinical applicability in predicting 3- and 5-year DFS in HCC patients after surgery.

CONCLUSION

Age, TNM stage, and history of hepatitis B infection were independent factors for DFS in HCC patients, and a novel nomogram for DFS of HCC patients was created and validated.

Prognostic Role of Molecular and Imaging Biomarkers for Predicting Advanced Hepatocellular Carcinoma Treatment Efficacy

Simple Summary

Molecular biomarkers play a marginal role in clinical practice for hepatocellular carcinoma (HCC) diagnosis, surveillance and treatment monitoring. Radiological biomarker: alpha-fetoprotein is still a lone protagonist in this field. The potential role of molecular biomarkers in the assessment of prognosis and treatment results could reduce the health costs faced by standard radiology. The majority of efforts are oriented towards early HCC detection, but the field faces an important challenge to find adequate biomarkers for advanced HCC management.

Abstract

Hepatocellular carcinoma (HCC) is the sixth most common malignancy worldwide and the fourth cause of tumor-related death. Imaging biomarkers are based on computed tomography, magnetic resonance, and contrast-enhanced ultrasound, and are widely applied in HCC diagnosis and treatment monitoring. Unfortunately, in the field of molecular biomarkers, alpha-fetoprotein (AFP) is still the only recognized tool for HCC surveillance in both diagnostic and follow-up purposes. Other molecular biomarkers have little roles in clinical practice regarding HCC, mainly for the detection of early-stage HCC, monitoring the response to treatments and analyzing tumor prognosis. In the last decades no important improvements have been achieved in this field and imaging biomarkers maintain the primacy in HCC diagnosis and follow-up. Despite the still inconsistent role of molecular biomarkers in surveillance and early HCC detection, they could play an outstanding role in prognosis estimation and treatment monitoring with a potential reduction in health costs faced by standard radiology. An important challenge resides in identifying sufficiently sensitive and specific biomarkers for advanced HCC for prognostic evaluation and detection of tumor progression, overcoming imaging biomarker sensitivity. The aim of this review is to analyze the current molecular and imaging biomarkers in advanced HCC.

The LncRNA DUXAP10 Could Function as a Promising Oncogene in Human Cancer

Cancer is one of the most prevalent and deadliest diseases globally, with an increasing morbidity of approximately 14 million new cancer cases per year. Identifying novel diagnostic and prognostic biomarkers for cancers is important for developing cancer therapeutic strategies and lowering mortality rates. Long noncoding RNAs (lncRNAs) represent a group of noncoding RNAs of more than 200 nucleotides that have been shown to participate in the development of human cancers. The novel lncRNA DUXAP10 was newly reported to be abnormally overexpressed in several cancers and positively correlated with poor clinical characteristics of cancer patients. Multiple studies have found that DUXAP10 widely regulates vital biological functions related to the development and progression of cancers, including cell proliferation, apoptosis, invasion, migration, and stemness, through different molecular mechanisms. The aim of this review was to recapitulate current findings regarding the roles of DUXAP10 in cancers and evaluate the potential of DUXAP10 as a novel biomarker for cancer diagnosis, treatment, and prognostic assessment.