Dataset Information

The value of red blood cell distribution width, neutrophil-to-lymphocyte ratio, and hemoglobin-to-red blood cell distribution width ratio in the progression of non-small cell lung cancer.

ABSTRACT: BACKGROUND:Lung cancer is the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) accounting for 85% of all lung cancer cases. Inflammation has been proven to be one of the characteristics of malignant tumors. Chronic inflammatory response mediated by cytokines in the tumor microenvironment is an important factor in tumorigenesis. The purpose of this study was to observe and evaluate the value of red blood cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), and hemoglobin-to-red blood cell distribution width ratio (HRR) in the progression of NSCLC. METHODS:A total of 245 patients with NSCLC, 97 patients with benign pulmonary nodules, and 94 healthy volunteers were included in this study. Factors, such as age, gender, smoking history, histological type, lymph node metastasis, distant metastasis, TNM stage, and differentiation degree were statistically analyzed. The correlation of RDW, NLR, and HRR of patients with NSCLC with other clinical experimental parameters were also analyzed. Then, the diagnostic value of RDW, NLR, and HRR in the progression of NSCLC was evaluated. RESULTS:RDW, NLR, and HRR could be used to distinguish patients with NSCLC from healthy controls (p < 0.05). In addition, only the RDW in the NSCLC group with III-IV stage was significantly different from that in the benign pulmonary nodules group (p = 0.033), while NLR and HRR could significantly distinguish patients with NSCLC and benign pulmonary nodules (p < 0.001). RDW and NLR were positively correlated with NSCLC stage, whereas HRR was negatively correlated with NSCLC stage. RDW, NLR, and HRR were also significantly associated with the differentiation degree of NSCLC (p < 0.05). The ROC curve analysis showed that the combination of RDW with NLR, HRR, and CEA could show significantly higher diagnostic value than any one marker alone (AUC = 0.925, 95% CI: 0.897-0.954, and sensitivity and specificity of 79.60% and 93.60%, respectively). CONCLUSION:RDW, NLR, and HRR can be utilized as simple and effective biomarkers for the diagnosis and evaluation of NSCLC progression.

SUBMITTER: Chen JL

PROVIDER: S-EPMC7446848 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The value of red blood cell distribution width, neutrophil-to-lymphocyte ratio, and hemoglobin-to-red blood cell distribution width ratio in the progression of non-small cell lung cancer.

Chen Jin-Liang JL Wu Jin-Nan JN Lv Xue-Dong XD Yang Qi-Chang QC Chen Jian-Rong JR Zhang Dong-Mei DM

PloS one 20200824 8

<h4>Background</h4>Lung cancer is the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) accounting for 85% of all lung cancer cases. Inflammation has been proven to be one of the characteristics of malignant tumors. Chronic inflammatory response mediated by cytokines in the tumor microenvironment is an important factor in tumorigenesis. The purpose of this study was to observe and evaluate the value of red blood cell distribution width (RDW), neutrophil-to ...[more]

PMID: 32833961

Similar Datasets

Project description:BackgroundHigher red blood cell distribution width (RDW) levels are associated with mortality in patients with chronic obstructive pulmonary disease (COPD). However, more convincing evidence is still lacking, and the relationship between hemoglobin-to-red blood cell distribution width ratio (HRR) and mortality in patients with COPD remains unclear.MethodsThis study is a prospective cohort study that includes 3,745 adult patients with COPD from the National Health and Nutrition Examination Survey (NHANES) database spanning from 1999 to 2018 in the United States. COX proportional hazards regression analysis, Kaplan-Meier survival curves and restricted cubic spline models were employed to investigate the association of RDW and HRR levels with mortality. Time-dependent receiver operating characteristic curve (ROC) analysis was conducted to evaluate the accuracy of RDW and HRR in predicting mortality in patients with COPD.ResultsHigher RDW level was positively associated with increased risk of all-cause mortality (HR = 1.16, 95% CI = 1.11-1.21, P < 0.001), cardiovascular disease (CVD) mortality (HR = 1.13, 95% CI = 1.06-1.21, P < 0.001), and chronic lower respiratory disease (CLRD) related mortality (HR = 1.15, 95% CI = 1.05-1.25, P = 0.003) after adjusting for various potential confounders. HRR was inversely associated with all-cause mortality (HR = 0.14, 95% CI = 0.08-0.25, P < 0.001), CVD mortality (HR = 0.12, 95% CI = 0.05-0.31, P < 0.001). HRR has no significant correlation with CLRD-related mortality. The time-dependent ROC curve showed that RDW exhibited area under the curves (AUCs) of the 5- and 10-year survival rates were 0.707 and 0.714 for all-cause mortality and 0.686 and 0.698, respectively, for CVD mortality. HRR yielded AUCs of the 5- and 10-year survival rates were 0.661 and 0.653 for all-cause mortality and 0.654 and 0.66, respectively, for CVD mortality.ConclusionHigher RDW levels were positively associated with an increased risk of mortality in patients with COPD. HRR levels were negatively correlated with the risk of all-cause and CVD mortality. The predictive value of HRR for mortality in these patients is lower than that of RDW.

Project description:BackgroundIn patients with ischemic stroke, low hemoglobin-to-red blood cell distribution width ratio (HRR) was associated with an increased risk of mortality. However, it was unknown in the non-traumatic subarachnoid hemorrhage (SAH) population. The purpose of this study was to examine the association between baseline HRR and in-hospital mortality in patients with non-traumatic SAH.MethodsNon-traumatic SAH patients were screened out of the Medical Information Mart for Intensive IV (MIMIC-IV) database between 2008 and 2019. The Cox proportional hazard regression models were utilized to analyze the association between baseline HRR and in-hospital mortality. Restricted cubic splines (RCS) analysis was utilized to determine the relationship curve between hospital mortality and the HRR level and examine the threshold saturation effect. We further applied Kaplan-Meier survival curve analysis to examine the consistency of these correlations. The interaction test was used to identify subgroups with differences.ResultsA total of 842 patients were included in this retrospective cohort study. Compared with individuals with lower HRR Q1 ( ≤ 7.85), the adjusted HR values in Q2 (7.86-9.15), Q3 (9.16-10.16), and Q4 (≥10.17) were 0.574 (95% CI: 0.368-0.896, p = 0.015), 0.555 (95% CI: 0.346-0.890, p = 0.016), and 0.625 (95% CI: 0.394-0.991, p = 0.045), respectively. The association between the HRR level and in-hospital mortality exhibited a non-linear relationship (p < 0.05). The threshold inflection point value of 9.50 was calculated using RCS analysis. When the HHR level was lower than 9.50, the risk of in-hospital mortality rate decreased with an adjusted HR of 0.79 (95% CI: 0.70-0.90, p = 0.0003). When the HRR level was higher than 9.50, the risk of in-hospital mortality almost hardly increased with the increase in the HRR level (adjusted HR = 1.18, 95% CI: 0.91-1.53, p = 0.2158). K-M analysis showed that patients with low HRR levels had significantly higher in-hospital mortality (p < 0.001).ConclusionThere was a non-linear connection between the baseline HRR level and in-hospital mortality. A low level of HRR could increase the risk of death in participants with non-traumatic SAH.

Dataset Information

The value of red blood cell distribution width, neutrophil-to-lymphocyte ratio, and hemoglobin-to-red blood cell distribution width ratio in the progression of non-small cell lung cancer.

Publications

The value of red blood cell distribution width, neutrophil-to-lymphocyte ratio, and hemoglobin-to-red blood cell distribution width ratio in the progression of non-small cell lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets