scholarly journals Combination of Tertiary Lymphoid Structure and Neutrophil-to-Lymphocyte Ratio Predicts Survival in Patients With Hepatocellular Carcinoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Shaodi Wen ◽  
Yuzhong Chen ◽  
Chupeng Hu ◽  
Xiaoyue Du ◽  
Jingwei Xia ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Systemic Inflammation ◽  
Cox Regression ◽  
Primary Liver Cancer ◽  
Paraffin Section ◽  
Neutrophil To Lymphocyte Ratio ◽  
Survival Prediction ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Inflammation Parameters

BackgroundHepatocellular carcinoma (HCC) is the most common pathological type of primary liver cancer. The lack of prognosis indicators is one of the challenges in HCC. In this study, we investigated the combination of tertiary lymphoid structure (TLS) and several systemic inflammation parameters as a prognosis indicator for HCC.Materials and MethodsWe retrospectively recruited 126 postoperative patients with primary HCC. The paraffin section was collected for TLS density assessment. In addition, we collected the systemic inflammation parameters from peripheral blood samples. We evaluated the prognostic values of those parameters on overall survival (OS) using Kaplan-Meier curves, univariate and multivariate Cox regression. Last, we plotted a nomogram to predict the survival of HCC patients.ResultsWe first found TLS density was positively correlated with HCC patients’ survival (HR=0.16, 95% CI: 0.06 − 0.39, p < 0.0001), but the power of TLS density for survival prediction was found to be limited (AUC=0.776, 95% CI:0.772 − 0.806). Thus, we further introduced several systemic inflammation parameters for survival analysis, we found neutrophil-to-lymphocyte ratio (NLR) was positively associated with OS in univariate Cox regression analysis. However, the combination of TLS density and NLR better predicts patient’s survival (AUC=0.800, 95% CI: 0.698-0.902, p < 0.001) compared with using any single indicator alone. Last, we incorporated TLS density, NLR, and other parameters into the nomogram to provide a reproducible approach for survival prediction in HCC clinical practice.ConclusionThe combination of TLS density and NLR was shown to be a good predictor of HCC patient survival. It also provides a novel direction for the evaluation of immunotherapies in HCC.

scholarly journals The prognostic and diagnostic significance of the neutrophil-to-lymphocyte ratio in hepatocellular carcinoma: a prospective controlled study

2021 ◽  
Author(s):  
Philip J. Johnson ◽  
Sofi Dhanaraj ◽  
Sarah Berhane ◽  
Laura Bonnett ◽  
Yuk Ting Ma
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Prognostic Factor ◽  
Cox Regression ◽  
Prognostic Models ◽  
Controlled Study ◽  
Cox Regression Analysis ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Significant Difference

Abstract Background The neutrophil–lymphocyte ratio (NLR), a presumed measure of the balance between neutrophil-associated pro-tumour inflammation and lymphocyte-dependent antitumour immune function, has been suggested as a prognostic factor for several cancers, including hepatocellular carcinoma (HCC). Methods In this study, a prospectively accrued cohort of 781 patients (493 HCC and 288 chronic liver disease (CLD) without HCC) were followed-up for more than 6 years. NLR levels between HCC and CLD patients were compared, and the effect of baseline NLR on overall survival amongst HCC patients was assessed via multivariable Cox regression analysis. Results On entry into the study (‘baseline’), there was no clinically significant difference in the NLR values between CLD and HCC patients. Amongst HCC patients, NLR levels closest to last visit/death were significantly higher compared to baseline. Multivariable Cox regression analysis showed that NLR was an independent prognostic factor, even after adjustment for the HCC stage. Conclusion NLR is a significant independent factor influencing survival in HCC patients, hence offering an additional dimension in prognostic models.

scholarly journals Dynamic Changes of the Neutrophil-to-Lymphocyte Ratio, Systemic Inflammation Index, and Derived Neutrophil-to-Lymphocyte Ratio Independently Predict Invasive Mechanical Ventilation Need and Death in Critically Ill COVID-19 Patients

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1656
Author(s):  
Emanuel Moisa ◽  
Dan Corneci ◽  
Silvius Negoita ◽  
Cristina Raluca Filimon ◽  
Andreea Serbu ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Critically Ill ◽  
Systemic Inflammation ◽  
Predictive Value ◽  
Cox Regression ◽  
Invasive Mechanical Ventilation ◽  
Neutrophil To Lymphocyte Ratio ◽  
Dynamic Changes ◽  
Hematological Indices ◽  
Lymphocyte Ratio

Background: Hematological indices can predict disease severity, progression, and death in patients with coronavirus disease-19 (COVID-19). Objectives: To study the predictive value of the dynamic changes (first 48 h after ICU admission) of the following ratios: neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR), systemic inflammation index (SII), and derived neutrophil-to-lymphocyte (dNLR) for invasive mechanical ventilation (IMV) need and death in critically ill COVID-19 patients. Methods: Observational, retrospective, and multicentric analysis on 272 patients with severe or critical COVID-19 from two tertiary centers. Hematological indices were adjusted for confounders through multivariate analysis using Cox regression. Results: Patients comprised 186 males and 86 females with no difference across groups (p > 0.05). ΔNLR > 2 had the best independent predictive value for IMV need (HR = 5.05 (95% CI, 3.06–8.33, p < 0.0001)), followed by ΔSII > 340 (HR = 3.56, 95% CI 2.21–5.74, p < 0.0001) and ΔdNLR > 1 (HR = 2.61, 95% CI 1.7–4.01, p < 0.0001). Death was also best predicted by an NLR > 11 (HR = 2.25, 95% CI: 1.31–3.86, p = 0.003) followed by dNLR > 6.93 (HR = 1.89, 95% CI: 1.2–2.98, p = 0.005) and SII > 3700 (HR = 1.68, 95% CI: 1.13–2.49, p = 0.01). Conclusions: Dynamic changes of NLR, SII, and dNLR independently predict IMV need and death in critically ill COVID-19 patients.

scholarly journals The Systemic Inflammation Index on Admission Predicts In-Hospital Mortality in COVID-19 Patients

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5725 ◽  
Author(s):  
Alessandro G. Fois ◽  
Panagiotis Paliogiannis ◽  
Valentina Scano ◽  
Stefania Cau ◽  
Sergio Babudieri ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Systemic Inflammation ◽  
Cox Regression ◽  
Rapid Onset ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Kaplan Meier ◽  
Group Methods ◽  
Aggregate Index ◽  
Inflammatory State

Background. The rapid onset of a systemic pro-inflammatory state followed by acute respiratory distress syndrome is the leading cause of mortality in patients with COVID-19. We performed a retrospective observational study to explore the capacity of different complete blood cell count (CBC)-derived inflammation indexes to predict in-hospital mortality in this group. Methods. The neutrophil to lymphocyte ratio (NLR), derived NLR (dNLR), platelet to lymphocyte ratio (PLR), mean platelet volume to platelet ratio (MPR), neutrophil to lymphocyte × platelet ratio (NLPR), monocyte to lymphocyte ratio (MLR), systemic inflammation response index (SIRI), systemic inflammation index (SII), and the aggregate index of systemic inflammation (AISI) were calculated on hospital admission in 119 patients with laboratory confirmed COVID-19. Results. Non-survivors had significantly higher AISI, dNLR, NLPR, NLR, SII, and SIRI values when compared to survivors. Similarly, Kaplan–Meier survival curves showed significantly lower survival in patients with higher AISI, dNLR, MLR, NLPR, NLR, SII, and SIRI. However, after adjusting for confounders, only the SII remained significantly associated with survival (HR = 1.0001; 95% CI, 1.0000–1.0001, p = 0.029) in multivariate Cox regression analysis. Conclusions. The SII on admission independently predicts in-hospital mortality in COVID-19 patients and may assist with early risk stratification in this group.

Real world outcomes in advanced urothelial cancer and the role of neutrophil to lymphocyte ratio.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e16020-e16020
Author(s):  
Steven Yip ◽  
Jeenan Kaiser ◽  
Haocheng Li ◽  
Scott A. North ◽  
Daniel Yick Chin Heng ◽  
...  
Keyword(s):  
Real World ◽  
Cox Regression ◽  
Response Rates ◽  
Neutrophil To Lymphocyte Ratio ◽  
Second Line ◽  
First Line ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Line Setting

e16020 Background: Advanced urothelial carcinoma (UC) patients have a poor prognosis. In the first and second line UC treatment setting, we investigated real world outcomes and evaluated the prognostic role of the neutrophil to lymphocyte ratio (NLR). Methods: A retrospective analysis was performed on advanced UC patients treated with systemic therapy. Overall response rates (ORR), time to treatment failure (TTF) and overall survival (OS) were calculated. Cox regression analysis was performed to examine the association between baseline NLR (low NLR<3 vs high NLR≥3) and TTF and OS. Results: We evaluated 233 advanced UC patients. In the first line setting, the ORR was 25%. Median TTF and OS were 6.9 mo and 9 mo, respectively. Low baseline NLR was significantly associated with improved 8.3 mo median TTF, versus 5.8 mo for high NLR patients (p=0.05). Low NLR was significantly correlated with a longer median OS of 13.1 mo, in comparison to 8.2 mo in patients with high NLR (p=0.007). In the second line, an ORR of 22%, a median TTF of 4.1 mo and a median OS of 8 mo were observed. Low NLR in the second line was significantly associated with improved median TTF at 7.9 mo, versus 3.6 mo for patients with high NLR (p=0.03). Second line low NLR was also significantly associated with a longer median OS of 12.2 mo, in comparison to 6.8 mo in patients with high NLR (p=0.003). Conclusions: In this real world analysis of advanced UC patients, first line outcomes were lower than expected, while response rates in the second line compared favorably to the literature, suggesting a highly selected patient population actually receives second line treatment. A low baseline NLR in the first and second line is associated with improved TTF and OS and warrants further prospective evaluation. [Table: see text]

scholarly journals Neutrophil to Lymphocyte Ratio as Prognostic Indicator for Patients with Esophageal Squamous Cell Cancer

2017 ◽  
Vol 32 (4) ◽  
pp. 409-414 ◽  
Author(s):  
Guo-Dong Gao ◽  
Bo Sun ◽  
Xian-Bin Wang ◽  
Shi-Meng Wang
Keyword(s):  
Overall Survival ◽  
Squamous Cell ◽  
Cox Regression ◽  
Cell Cancer ◽  
Prognostic Indicator ◽  
Neutrophil To Lymphocyte Ratio ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Leukocyte Counts ◽  
Clinical Records

Background This study aimed to evaluate the correlation between neutrophil to lymphocyte ratio (NLR) with overall survival (OS) of esophageal squamous cell carcinoma (ESCC) patients. Method Records of patients with diagnosed ESCC were reviewed. Leukocyte counts and patients' characteristics were extracted from their clinical records to calculate NLR. Correlation between NLR and baseline characteristics with overall survival (OS) was then analyzed using Cox regression. The patients were then separated into higher and lower NLR groups according to median NLR. OS was further compared between the 2 groups. Results A total of 1281 patients were included in the study. Cox regression analysis showed a significant correlation of NLR with OS of ESCC patients. The median pretreatment NLR was identified as 2.86. Higher NLR was associated with worse prognosis in terms of OS. Conclusions Pretreatment NLR is independently associated with OS of ESCC patients. Therefore, NLR may be used as a predictive indicator for pretreatment evaluation and adjustment of treatment regimen.

scholarly journals Establishment of a Prognostic Model for Hepatocellular Carcinoma Based on Endoplasmic Reticulum Stress-Related Gene Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Peng Liu ◽  
Jinhong Wei ◽  
Feiyu Mao ◽  
Zechang Xin ◽  
Heng Duan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Endoplasmic Reticulum ◽  
Regression Analysis ◽  
Endoplasmic Reticulum Stress ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Cancer Genome ◽  
Survival Prediction ◽  
Training Cohort ◽  
Cox Regression Analysis

Hepatocellular carcinoma (HCC) is one of the most common types of cancer worldwide and its incidence continues to increase year by year. Endoplasmic reticulum stress (ERS) caused by protein misfolding within the secretory pathway in cells and has an extensive and deep impact on cancer cell progression and survival. Growing evidence suggests that the genes related to ERS are closely associated with the occurrence and progression of HCC. This study aimed to identify an ERS-related signature for the prospective evaluation of prognosis in HCC patients. RNA sequencing data and clinical data of patients from HCC patients were obtained from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC). Using data from TCGA as a training cohort (n=424) and data from ICGC as an independent external testing cohort (n=243), ERS-related genes were extracted to identify three common pathways IRE1, PEKR, and ATF6 using the GSEA database. Through univariate and multivariate Cox regression analysis, 5 gene signals in the training cohort were found to be related to ERS and closely correlated with the prognosis in patients of HCC. A novel 5-gene signature (including HDGF, EIF2S1, SRPRB, PPP2R5B and DDX11) was created and had power as a prognostic biomarker. The prognosis of patients with high-risk HCC was worse than that of patients with low-risk HCC. Multivariate Cox regression analysis confirmed that the signature was an independent prognostic biomarker for HCC. The results were further validated in an independent external testing cohort (ICGC). Also, GSEA indicated a series of significantly enriched oncological signatures and different metabolic processes that may enable a better understanding of the potential molecular mechanism mediating the progression of HCC. The 5-gene biomarker has a high potential for clinical applications in the risk stratification and overall survival prediction of HCC patients. In addition, the abnormal expression of these genes may be affected by copy number variation, methylation variation, and post-transcriptional regulation. Together, this study indicated that the genes may have potential as prognostic biomarkers in HCC and may provide new evidence supporting targeted therapies in HCC.

scholarly journals Neutrophil to Lymphocyte Ratio Predicts Adverse Cardiovascular Outcome in Peritoneal Dialysis Patients Younger than 60 Years Old

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yingsi Zeng ◽  
Zijun Chen ◽  
Qinkai Chen ◽  
Xiaojiang Zhan ◽  
Haibo Long ◽  
...  
Keyword(s):  
Peritoneal Dialysis ◽  
Cox Regression ◽  
Neutrophil To Lymphocyte Ratio ◽  
Forest Plot ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Increased Risk ◽  
The Relationship ◽  
Cvd Mortality ◽  
New Onset

Background. Neutrophil to lymphocyte ratio (NLR) is a new inflammatory marker; the relationship between NLR and adverse cardiovascular (CV) prognosis has been gradually emphasized in the general population. However, their association in peritoneal dialysis (PD) patients remains unclear. Methods. From January 1, 2010, to May 31, 2017, a total of 1652 patients were recruited. NLR was categorized in triplicates: NLR≤2.74, 2.74<NLR≤3.96, and NLR>3.96. Kaplan-Meier cumulative incidence curve and multivariable COX regression analysis were used to determine the relationship between NLR and the incidence of adverse CV outcome, while a competitive risk model was applied to assess the effects of other outcomes on adverse CV prognosis. Besides, forest plot was investigated to analyze the adverse CV prognosis in different subgroups. Results. During follow-up, 213 new-onset CV events and 153 CV disease (CVD) deaths were recorded. Multivariable COX regression models showed that the highest tertile of NLR level was associated with increased risk of CV events (HR=1.39, 95%CI=1.01‐1.93, P=0.046) and CVD mortality (HR=1.81, 95%CI=1.22‐2.69, P=0.003), while compared to the lowest tertile. Competitive risk models showed that the differences in CV event (P<0.001) and CVD mortality (P=0.004) among different NLR groups were still significant while excluding the effects of other outcomes. In subgroups, with each 1 increased in the NLR level, adjusted HR of new-onset CV event was 2.02 (95%CI=1.26−3.23, P=0.003) and CVD mortality was 2.98 (95%CI=1.58−5.62, P=0.001) in the younger group (age<60 years). Conclusions. NLR is an independent risk factor for adverse CV prognosis in PD patients younger than 60 years old.

Prognostic value of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with colorectal cancer.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 551-551 ◽  
Author(s):  
Jae Hyun Kim ◽  
Seun Ja Park
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Value ◽  
Cox Regression ◽  
Neutrophil To Lymphocyte Ratio ◽  
Platelet To Lymphocyte Ratio ◽  
Poor Overall Survival ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Kaplan Meier ◽  
Independent Risk Factors

551 Background: Inflammatory response plays an important role in the pathogenesis of cancer. Some evidence has suggested that elevations in the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are associated with decreased survival in various types of cancer. In this study, we aimed to evaluate the prognostic value of the NLR and PLR in patients with colorectal cancer (CRC). Methods: Between August 1995 and December 2010, medical records from a total of 2,004 patients with CRC were retrospectively reviewed. The values of simple inflammatory markers including NLR and PLR in predicting the long-term outcomes of these patients were evaluated using Kaplan-Meier curves and multivariate Cox regression models. Results: The median follow-up duration was 42 months (interquartile range, 19 – 69). The estimation of NLR and PLR was based on the time of diagnosis. In multivariate Cox regression analysis, high NLR ( ≥ 2.6) [hazard ratio (HR) 2.251, 95% confidence interval (CI) 1.570-3.228, p < 0.001] and high PLR ( ≥ 155) [HR 1.473, 95% CI 1.019 – 2.128, p = 0.039] were independent risk factors predicting poor overall survival (OS) in CRC patients. Combined high NLR and PLR was also an independent risk factor predicting poor OS in patients with CRC [HR 2.316, 95% CI 1.529 – 3.508, p < 0.001]. Conclusions: In this study, we identified that high NLR ( ≥ 2.6), high PLR ( ≥ 155), and combined high NLR and PLR are useful prognostic factors to predict OS in CRC patients.

scholarly journals Identification of Long Noncoding RNA Biomarkers for Hepatocellular Carcinoma Using Single-Sample Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiaoqing Yu ◽  
Jingsong Zhang ◽  
Rui Yang ◽  
Chun Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Single Sample ◽  
Survival Prediction ◽  
Prediction Ability ◽  
Cox Regression Analysis ◽  
Score Model ◽  
Function Enrichment

Objective. Many studies have found that long noncoding RNAs (lncRNAs) are differentially expressed in hepatocellular carcinoma (HCC) and closely associated with the occurrence and prognosis of HCC. Since patients with HCC are usually diagnosed in late stages, more effective biomarkers for early diagnosis and prognostic prediction are in urgent need. Methods. The RNA-seq data of liver hepatocellular carcinoma (LIHC) were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs and mRNAs were obtained using the edgeR package. The single-sample networks of the 371 tumor samples were constructed to identify the candidate lncRNA biomarkers. Univariate Cox regression analysis was performed to further select the potential lncRNA biomarkers. By multivariate Cox regression analysis, a 3-lncRNA-based risk score model was established on the training set. Then, the survival prediction ability of the 3-lncRNA-based risk score model was evaluated on the testing set and the entire set. Function enrichment analyses were performed using Metascape. Results. Three lncRNAs (RP11-150O12.3, RP11-187E13.1, and RP13-143G15.4) were identified as the potential lncRNA biomarkers for LIHC. The 3-lncRNA-based risk model had a good survival prediction ability for the patients with LIHC. Multivariate Cox regression analysis proved that the 3-lncRNA-based risk score was an independent predictor for the survival prediction of patients with LIHC. Function enrichment analysis indicated that the three lncRNAs may be associated with LIHC via their involvement in many known cancer-associated biological functions. Conclusion. This study could provide novel insights to identify lncRNA biomarkers for LIHC at a molecular network level.

scholarly journals Predictive value of lymphocyte-to-monocyte ratio (LMR) and neutrophil-to-lymphocyte ratio (NLR) in patients with oesophageal cancer undergoing concurrent chemoradiotherapy

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Ke-Jie Li ◽  
Xiao-Fang Xia ◽  
Meng Su ◽  
Hui Zhang ◽  
Wen-Hao Chen ◽  
...  
Keyword(s):  
Oesophageal Cancer ◽  
Concurrent Chemoradiotherapy ◽  
Cox Regression ◽  
Treatment Options ◽  
Neutrophil To Lymphocyte Ratio ◽  
Regression Analyses ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Lymphocyte To Monocyte Ratio

Abstract Background and objectives The survival rate of patients with advanced oesophageal cancer is very low and can vary significantly, even among patients with the same TNM stage. It is important to look for indicators that are economical and readily available to predict overall survival. The aim of this study was to determine whether lymphocyte-to-monocyte ratio (LMR) and neutrophil-to-lymphocyte ratio (NLR) could be potential predictors of survival in patients with advanced oesophageal squamous cell carcinoma (ESCC) undergoing concurrent chemoradiotherapy. Methods Differences in survival among 204 patients with advanced oesophageal cancer who underwent concurrent chemoradiotherapy were collected and analysed. Univariate and multivariate COX regression analyses were used to investigate the association between blood inflammatory markers and patient survival before treatment. Results Univariate COX regression analyses showed that a history of alcohol use, neutrophil count, LMR, NLR, tumour length, and N stage were significantly associated with the survival of tumour patients receiving concurrent chemoradiotherapy. Multivariate COX regression analysis showed that NLR and LMR were predictors of outcome in tumour patients receiving chemoradiotherapy. According to receiver operating characteristic (ROC) curve analysis, the AUC of LMR and NLR was 0.734 and 0.749, and the best cutoff point for LMR and NLR was 3.03 and 2.64, respectively. Conclusions LMR and NLR can be used to predict the survival of patients with advanced oesophageal cancer receiving concurrent chemoradiotherapy, thereby providing clinicians with suggestions for further treatment options.

Sign in / Sign up

Export Citation Format

Share Document