Systemic Inflammation and Activation of Haemostasis Predict Poor Prognosis and Response to Chemotherapy in Patients with Advanced Lung Cancer

Moik, Florian; Zöchbauer‐Müller, Sabine; Posch, Florian; Pabinger, Ingrid; Ay, Cihan

doi:10.3390/cancers12061619

Cited by 28 publications

(28 citation statements)

References 49 publications

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“…The detection methods used in the studies include immunoturbidimetry assay [ 15 – 27 ], latex assay [ 1 , 28 – 30 ], and enzyme-linked immunosorbent assay (ELISA) [ 9 , 31 – 36 ]. Since different detection methods may affect the level of D-dimer, we conducted a subgroup analysis to further analyze the impact of different detection methods on the prognosis.…”

Section: Resultsmentioning

confidence: 99%

The D-dimer level predicts the prognosis in patients with lung cancer: a systematic review and meta-analysis

Cao

Wang

et al. 2021

J Cardiothorac Surg

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Objective Although the significance of increased plasma D-dimer levels in activating coagulation and fibrinolysis has been reported, it is still controversial whether it can be used to predict the prognosis of lung cancer patients. This meta-analysis was performed to explore the beneficial role of plasma D-dimer as a prognostic factor in lung cancer patients according to a larger sample capacity. Materials and methods MEDLINE, EMBASE, and Cochrane Central databases were searched from inception to January 2021. The data are mainly hazard ratio(HR) with 95% confidence interval (CI) and Kaplan–Meier survival curves. The publication bias was examined by Egger’s test. Results Finally, a total of 28 studies, enrolling 8452 patients were included in the current meta-analysis. Our results showed that the OS (HR = 1.742, 95%CI:1.542–1.969, P < 0.001) and PFS (HR = 1.385, 95%CI:1.169–1.641, P = 0.003) in the high D-dimer group were significantly lower than those in the low D-dimer group. Subgroup analysis suggested that localization, detection methods and disease stage had an important effect on the prognosis. Conclusion This meta-analysis revealed that the high plasma D-dimer level leads to lower survival than in the low D-dimer level, which might provide an important clue for high plasma D-dimer level as an independent factor of poor prognosis in patients with lung cancer.

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Section: Resultsmentioning

confidence: 99%

The D-dimer level predicts the prognosis in patients with lung cancer: a systematic review and meta-analysis

Cao

Wang

et al. 2021

J Cardiothorac Surg

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“…Plasma D-dimer is a small cross-linked protein generated from fibrin degradation and is an essential indicator of coagulation dysfunction (2,(9)(10)(11). It has critical implications for the exclusion of cancer-related thrombosis clinically (12).…”

Section: Introductionmentioning

confidence: 99%

Application of an elevated plasma D-dimer cut-off value improves prognosis prediction of advanced non-small cell lung cancer

Chen¹,

Li²,

Li³

et al. 2020

Ann Transl Med

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Background: Tumor-related coagulation dysfunction has been reported to be closely associated with poor prognosis. The present study is aimed to evaluate the prognostic prediction of an elevated plasma D-dimer cut-off value in advanced non-small cell lung cancer (NSCLC).Methods: A total of 233 patients initially diagnosed with advanced NSCLC were retrospectively analyzed, an elevated plasma cut-off value 981 ng/mL of D-dimer, which was instead of the clinical cut-off value 500 mg/mL, was used to determine the high and low. Univariate analysis using the Kaplan-Meier method and log-ranking test, and the multivariate analysis using the Cox proportional hazard regression model were performed.Results: Results showed when using the D-dimer value of 500 ng/mL as an evaluation standard, there was no significant difference in gender, age, smoking status, histopathology and overall survival rate between normal D-dimer (≤500 ng/mL) and high D-dimer (>500 ng/mL) group. However, when the evaluation standard for plasma D-dimer was set at 981 ng/mL, the age distribution of the high D-dimer (>981 ng/mL) group was significantly different from the normal D-dimer (≤981 ng/mL) group. Moreover, the overall survival rate in the high D-dimer (>981 ng/mL) group was significantly lower than that in the normal D-dimer (≤981 ng/mL) group. Conclusions:The present study implied that increasing the plasma D-dimer cut-off value to 981 ng/mL is more beneficial to prognosis prediction in advanced NSCLC.

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“…He et al considered that the imaging biomarkers extracted by tumor mutational burden could effectively predict the therapeutic effect of immune checkpoint inhibitors in advanced NSCLC patients [ 59 ]. Moik et al demonstrated that inflammation and hemostasis could serve as biomarkers for unfavorable prognosis and poor therapy response in advanced lung cancer patients [ 60 ]. Perrone et al found that hypercholesterolemia implies a low-grade inflammatory state that could distinguish the best beneficiaries of immunotherapy in NSCLC [ 61 ].…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of a Tumor Microenvironment-Related Gene Signature for Prognostic Prediction in Advanced-Stage Non-Small-Cell Lung Cancer

Zhang

Shi

Zhao

et al. 2021

BioMed Research International

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The development of immunotherapy has greatly changed the advanced-stage non-small-cell lung cancer (NSCLC) treatment landscape. The complexity and heterogeneity of tumor microenvironment (TME) lead to discrepant immunotherapy effects among patients at the same pathologic stages. This study is aimed at exploring potential biomarkers of immunotherapy and accurately predicting the prognosis for advanced NSCLC patients. RNA-seq data and clinical information on stage III/IV NSCLC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). In TCGA-NSCLC with stage III/IV ( n = 192 ), immune scores and stromal scores were calculated by using the ESTIMATE algorithms. Univariate, LASSO, and multivariate Cox regression analyses were performed to screen prognostic TME-related genes (TMERGs) and constructed a gene signature risk score model. It was validated in external dataset including GSE41271 ( n = 91 ) and GSE81089 ( n = 36 ). Additionally, a nomogram incorporating TMERG signature risk score and clinical characteristics was established. Further, we accessed the proportion of 22 types of tumor-infiltrating immune cells (TIIC) from the CIBERSORT website and analyzed the difference between two risk groups. OS of patients with high immune/stromal scores were higher (log-rank P = 0.044 /log-rank P = 0.048 ). Multivariate Cox regression identified six prognostic TMERGs, including CD200, CHI3L2, CNTN1, CTSL, FYB1, and SLC52A1. We developed a six-gene risk score model, which was validated as an independent prognostic factor for OS (HR: 3.32, 95% CI: 2.16-5.09). Time-ROC curves showed useful discrimination for TCGA-NSCLC cohort (1-, 2-, and 3-year AUCs were 0.718, 0.761, and 0.750). The predictive robustness was validated in the external dataset. The C-index and 1-, 2-, and 3-year AUCs of nomogram were the largest, which demonstrated the nomogram had the greatest predictive accuracy and effectiveness and could be used for clinical guidance. Besides, the increased infiltration of T cells regulatory (Tregs) and macrophages M2 in the high-risk group suggested that chronic inflammation may reduce survival probability in patients with advanced NSCLC. We conducted a comprehensive analysis of the tumor microenvironment and identified the TMERG signature, which could predict prognosis accurately and provide a reference for the personalized immunotherapy for advanced NSCLC patients.

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Systemic Inflammation and Activation of Haemostasis Predict Poor Prognosis and Response to Chemotherapy in Patients with Advanced Lung Cancer

Cited by 28 publications

References 49 publications

The D-dimer level predicts the prognosis in patients with lung cancer: a systematic review and meta-analysis

The D-dimer level predicts the prognosis in patients with lung cancer: a systematic review and meta-analysis

Application of an elevated plasma D-dimer cut-off value improves prognosis prediction of advanced non-small cell lung cancer

Identification and Validation of a Tumor Microenvironment-Related Gene Signature for Prognostic Prediction in Advanced-Stage Non-Small-Cell Lung Cancer

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