scholarly journals Neutrophil-to-Lymphocyte Ratio as a Biomarker Predicting Overall Survival after Chemoembolization for Intermediate-Stage Hepatocellular Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2830
Author(s):  
Hee Ho Chu ◽  
Jin Hyoung Kim ◽  
Ju Hyun Shim ◽  
Dong Il Gwon ◽  
Heung-Kyu Ko ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Large Scale ◽  
Validation Cohort ◽  
Intermediate Stage ◽  
Neutrophil To Lymphocyte Ratio ◽  
Risk Scores ◽  
Multivariable Logistic Regression Analysis ◽  
Lymphocyte Ratio

The clinical impact of neutrophil-to-lymphocyte ratio (NLR) in predicting outcomes in hepatocellular carcinoma (HCC) patients treated with transarterial chemoembolization (TACE) remain unclear, and additional large-scale studies are required. This retrospective study evaluated outcomes in treatment-naïve patients who received TACE as first-line treatment for intermediate-stage HCC between 2008 and 2017. Patients who underwent TACE before and after 2013 were assigned to the development (n = 495) and validation (n = 436) cohorts, respectively. Multivariable Cox analysis identified six factors predictive of outcome, including NLR, which were used to create models predictive of overall survival (OS) in the development cohort. Risk scores of 0–3, 4–7, and 8–12 were defined as low, intermediate, and high risk, respectively. Median OS times in the low-, medium-, and high-risk groups in the validation cohort were 48.1, 24.3, and 9.7 months, respectively (p < 0.001). Application to the validation cohort of time-dependent ROC curves for models predictive of OS showed AUC values of 0.72 and 0.70 at 3 and 5 years, respectively. Multivariable logistic regression analysis found that NLR ≥ 3 was a significant predictor (odds ratio, 3.4; p < 0.001) of disease progression 6 months after TACE. Higher baseline NLR was predictive of poor prognosis in patients who underwent TACE for intermediate-stage HCC.

scholarly journals A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Junli Wang ◽  
Qi Zhang ◽  
Fukang Shi ◽  
Dipesh Kumar Yadav ◽  
Zhengtao Hong ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Group ◽  
Radical Resection ◽  
Tissue Microarrays ◽  
Gene Signature ◽  
High Risk Group ◽  
Prognostic Models ◽  
Risk Scores

Purpose: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant diseases worldwide and has a poor prognosis. Gene-based prognostic models have been reported to predict the overall survival of patients with HCC. Unfortunately, most of the genes used in earlier prognostic models lack prospective validation and, thus, cannot be used in clinical practice.Methods: Candidate genes were selected from GEPIA (Gene Expression Profiling Interactive Analysis), and their associations with patients’ survival were confirmed by RT-PCR using cDNA tissue microarrays established from patients with HCC after radical resection. A multivariate Cox proportion model was used to calculate the coefficient of corresponding gene. The expression of seven genes of interest (MKI67, AR, PLG, DNASE1L3, PTTG1, PPP1R1A, and TTR) with two reference genes was defined to calculate a risk score which determined groups of different risks.Results: Our risk scoring efficiently classified patients (n = 129) with HCC into a low-, intermediate-, and high-risk group. The three groups showed meaningful distinction of 3-year overall survival rate, i.e., 88.9, 74.5, and 20.6% for the low-, intermediate-, and high-risk group, respectively. The prognostic prediction model of risk scores was subsequently verified using an independent prospective cohort (n = 77) and showed high accuracy.Conclusion: Our seven-gene signature model performed excellent long-term prediction power and provided crucially guiding therapy for patients who are not a candidate for surgery.

The inflammation based index (IBI) predicts survival advantage after transarterial chemoembolization in hepatocellular carcinoma.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e15101-e15101
Author(s):  
Delali Akosua Adjogatse ◽  
George Karamanakos ◽  
David James Pinato ◽  
Rohini Sharma
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Transarterial Chemoembolization ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Intermediate Stage ◽  
Survival Advantage ◽  
Significant Survival ◽  
Before And After

e15101 Background: Transarterial chemoembolization (TACE) is a standard treatment for unresectable, intermediate stage hepatocellular carcinoma (HCC). Survival after TACE, however, can be highly variable, with no suitable biomarker predicting for therapeutic outcome. The inflammation based index (IBI) has previously been shown to independently predict overall survival in all stages of HCC. This retrospective study explored the prognostic ability of the IBI as a predictor of survival after TACE. Methods: Sixty three eligible patients who had undergone TACE for intermediate stage HCC were selected. The IBI was calculated using serum albumin and CRP levels as previously described; giving a score of 0-2, equating to low, intermediate and high risk respectively. Survival was calculated from the date of TACE to date of death. Dynamic changes in the IBI before and after TACE were studied as predictors of survival using both a univariate and multivariate Cox regression model. Results: Patients with a normal IBI prior to TACE had a significant improvement in survival in comparison to those with an intermediate or high-risk score (p=0.02). Other predictors of survival on univariate analysis were radiological response to TACE (p<0.001), pre-TACE CLIP score (p<0.01), initial tumour diameter >5 cm (p=0.049) and AFP > 400 (p<0.001). On multivariate analysis; normalisation of IBI post TACE was associated with improved overall survival, compared to patients showing a persistently abnormal index (p<0.001; HR 5.5, 95% CI 1.9 – 16.5). Conclusions: Normalisation of IBI after TACE is shown to be an independent predictor of survival. Patients with a persistently raised IBI following TACE have a worse survival outcome. As a simple and accessible stratifying biomarker, IBI aides the identification of patients with a significant survival advantage following TACE.

The predictive value of neutrophil-to-lymphocyte ratio on overall survival and pathological complete response in breast cancer patients receiving neoadjuvant chemotherapy.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12625-e12625
Author(s):  
Wenjie Tang ◽  
Linlin Wang ◽  
Jinming Yu ◽  
Yishan Yu
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Longitudinal Analysis ◽  
Validation Cohort ◽  
Univariate Analysis ◽  
Complete Response ◽  
Neutrophil To Lymphocyte Ratio ◽  
Training Cohort ◽  
Lymphocyte Ratio

e12625 Background: Neutrophil-to-lymphocyte ratio (NLR) has been found to offer clear predictive utility for the overall survival (OS) and pathologic complete response (pCR) in breast cancer (BC) patients receiving neoadjuvant chemotherapy(NAC). However, previous studies mainly focused on pre-NLR. The aim of this study was to explore the role of pre-/post-NLR towards OS and longitudinal NLR kineticsonpCR for BC patients undergoing NAC. And we also tried to build a nomogram for OS prediction based on these parameters. Methods: In this study, we retrospectively collected 501 female patients with locally advanced BC receiving 4-8 cycles of NAC from 2009 to 2018. Clinicopathological characteristics, NLR at pre-, mid-(every two cycles of NAC) and post-treatment were collected. The primary endpoint was OS. Among the patients, 421 patients with available pre- and post-NLR were included in the survival analysis. These patients were randomly divided into a training cohort (n = 224) and a validation cohort (n = 197). Multivariate survival model was built by including all the significant prognostic factors from the univariate analysis in the training cohort, and a nomogram model was established by “R” version 3.4.3. The performance of the model was further tested in the validation cohort by the concordance index. The second endpoint was pCR. Longitudinal analysis of NLR was performed using a mixed-effects regression model to predict pCR among 176 patients who finished 8 cycles of NAC. Results: The median follow-up time was 43.2 months for 421 patients. In the training cohort, multivariate analysis revealed that ER status, clinical node stage , pCR , pre-NLR, and post-NLR (all Ps＜0.05) were independent predictors of OS. Nomogram for OS prediction was established by combining all these significant factors. The C-indexes of the nomogram were 0.764 and 0.693, respectively in the training and validation cohort. In the longitudinal analysis, patients achieved pCR experienced a reduction of NLR every 2 cycles (Coef = -0.032, std error = 0.014, P = 0.024). Conclusions: This study demonstrated the prognostic value of pre-NLR and post-NLR towards BC patients received NAC. Based on that , a novel nomogram was established to predict the 3- and 5- year OS for BC patients. And we also found patients who experienced a decline of NLR during NAC seems to be more likely to achieve pCR from chemotherapy. Routine assessment of NLR may be an easy and affordable tool for defining prognosis.

The importance of the glucose-to-lymphocyte ratio in patients with hepatocellular carcinoma treated with sorafenib

2021 ◽  
Author(s):  
Ali Yılmaz ◽  
Melih Şimşek ◽  
Zekeriya Hannarici ◽  
Mehmet E Büyükbayram ◽  
Mehmet Bilici ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Prognostic Nutritional Index ◽  
Neutrophil To Lymphocyte Ratio ◽  
Advanced Hcc ◽  
Lymphocyte Ratio ◽  
Lymphocyte To Monocyte Ratio ◽  
Nutritional Index ◽  
Before And After ◽  
Immune Inflammation

Aim: To show the prognostic significance of the glucose-to-lymphocyte ratio (GLR) in hepatocellular carcinoma (HCC). Patients & methods: A total of 150 patients with advanced HCC who were treated with sorafenib in our center between January 2011 and December 2019 were included in the study retrospectively. Neutrophil-to-lymphocyte ratio, systemic immune-inflammation index, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, prognostic nutritional index and GLR were analyzed to assess their prognostic value using Kaplan–Meier and Cox regression analysis before and after propensity score matching (PSM). Results: In univariate analysis before and after PSM, albumin–bilirubin grade, neutrophil-to-lymphocyte ratio, systemic immune-inflammation index, lymphocyte-to-monocyte ratio, prognostic nutritional index, AFP level and GLR were found to be significantly associated with both progression-free and overall survival. In multivariate analysis before and after PSM, GLR, albumin–bilirubin grade and AFP were determined to be independent prognostic factors for progression-free and overall survival. Conclusion: The GLR prior to sorafenib treatment is a new prognostic biomarker that may predict survival in advanced HCC.

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

scholarly journals Astragalus Polysaccharide Injection (PG2) Normalizes the Neutrophil-to-Lymphocyte Ratio in Patients with Advanced Lung Cancer Receiving Immunotherapy

2021 ◽  
Vol 20 ◽  
pp. 153473542199525
Author(s):  
Shih Ming Tsao ◽  
Tz Chin Wu ◽  
JiZhen Chen ◽  
Feichi Chang ◽  
Thomos Tsao
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Survival Data ◽  
Treatment Initiation ◽  
Checkpoint Inhibitors ◽  
Neutrophil To Lymphocyte Ratio ◽  
Advanced Lung Cancer ◽  
Control Group ◽  
Lymphocyte Ratio ◽  
Astragalus Polysaccharide

Objectives: The neutrophil-to-lymphocyte ratio (NLR) is a prognostic marker in patients with cancer receiving immunotherapy. Recent studies have shown that a high NLR was associated with a poor response and decreased survival. However, there is no intervention to reverse abnormally high NLR and improve clinical outcomes. Astragalus polysaccharide injection (PG2) is an immunomodulatory therapy for cancer-related fatigue. This study aimed to examine whether PG2 might normalize the NLR and affect the overall survival of patients with lung cancer treated with immunotherapy. Materials and Methods: We retrospectively examined the medical records of patients with lung cancer treated with immune checkpoint inhibitors (ICIs) between October 1, 2015 and November 30, 2019. All patients received ICI combination chemotherapies, and some similarly received PG2 (Control vs PG2). The NLR was assessed before treatment and 6 weeks after ICI initiation, and the survival data was collected at least 4 years after treatment initiation for the first enrolled patient. Results: Fifty-three patients were included. Six weeks after ICI initiation, 91.3% of the patients in the PG2 group exhibited a predefined “Decrease or no change” in the NLR, which was 28% higher than that in the Control group (63.3%) ( P = .028). The NLR significantly decreased by 31.60% from baseline in the PG2 group ( P = .012), whereas it increased by 5.80% in the Control group ( P = .572). Six weeks after ICI treatment initiation, both groups had a median NLR of 3.73, and the overall survival was also similar (PG2 vs Control, 26.1 months vs 25.4 months, respectively); however, the PG2 group had a higher median baseline NLR than the Control group (PG2 vs Control, 4.51 vs 2.81, respectively). Conclusion: This study demonstrated that PG2 could normalize the NLR in patients with lung cancer receiving ICI combination treatments.

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