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      Prognostic value of neutrophil-to-lymphocyte ratio in breast cancer


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          • A literature search was conducted using PubMed, Web of Science and CNKI.

          • Increased NLR was a strong predictor for overall survival and disease-free survival.

          • Subgroup analyses stratified by ethnicity, analysis method and metastasis were conducted.

          • NLR could be considered as a predictive factor for patients with breast cancer.


          Inflammation is an essential component of pathogenesis and progression of cancer. A high neutrophil-to-lymphocyte ratio (NLR) is considered as a prognostic indicator for breast cancer. This meta-analysis was conducted to establish the overall accuracy of the NLR test in the diagnosis of breast cancer. A comprehensive search of the literature was conducted by using PubMed, Web of Science and China National Knowledge Infrastructure (CNKI). Published studies dating up to July 2014 and 4,293 patients were enrolled in the present study. In order to evaluate the association between NLR and overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS) or cancer specific survival (CSS), the hazard ratios (HRs) and their 95% confidence intervals (CIs) were extracted. OS was the primary outcome. The results suggested that increased NLR was a strong predictor for OS with HR of 2.28 (95% CI = 1.08–4.80, P heterogeneity  < 0.001). Stratified analyses indicated that a high NLR appeared to be a negative prognostic marker in Caucasian populations (HR = 4.53, 95% CI = 3.11–6.60, P heterogeneity  = 0.096), multivariate analysis method (HR = 2.10, 95% CI = 1.52–2.89, P heterogeneity  = 0.591), and mixed metastasis (HR = 4.53, 95% CI = 3.11–6.60, P heterogeneity  = 0.096). Elevated NLR was associated with a high risk for DFS (HR = 1.38, 95% CI = 1.09–1.74, P heterogeneity  = 0.050) and in subgroups of multivariate analysis (HR = 1.64, 95% CI = 1.25–2.14, P heterogeneity  = 0.545) and mixed metastasis (HR = 1.99, 95% CI = 1.28–3.09, P heterogeneity  = 0.992). In summary, NLR could be considered as a predictive factor for patients with breast cancer.

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          Most cited references24

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          Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and publication bias.

          Publication bias is a major problem in evidence based medicine. As well as positive outcome studies being preferentially published or followed by full text publication authors are also more likely to publish positive results in English-language journals. This unequal distribution of trials leads to a selection bias in evidence l level studies, like systematic reviews, meta-analysis or health technology assessments followed by a systematic failure of interpretation and in clinical decisions. Publication bias in a systematic review occurs mostly during the selection process and a transparent selection process is necessary to avoid such bias. For systematic reviews/meta-analysis the PRISMA-statement (formerly known as QUOROM) is recommended, as it gives the reader for a better understanding of the selection process. In the future the use of trial registration for minimizing publication bias, mechanisms to allow easier access to the scientific literature and improvement in the peer review process are recommended to overcome publication bias. The use of checklists like PRISMA is likely to improve the reporting quality of a systematic review and provides substantial transparency in the selection process of papers in a systematic review. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
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            Predominant infiltration of macrophages and CD8(+) T Cells in cancer nests is a significant predictor of survival in stage IV nonsmall cell lung cancer.

            The purpose of this study was to investigate whether tumor-infiltrating immune cells in biopsy specimens can be used to predict the clinical outcome of stage IV nonsmall cell lung cancer (NSCLC) patients. The authors performed an immunohistochemical study to identify and count the number of CD68(+) macrophages, c-kit(+) mast cells, and CD8(+) T cells in both cancer nests and cancer stroma in pretreatment biopsy specimens obtained from 199 patients with stage IV NSCLC treated by chemotherapy, and then analyzed for correlations between the number of immune cells and clinical outcome, including chemotherapy response and prognosis. There was no correlation between the number of immune cells in either cancer nests or stroma and chemotherapy response. Patients with more tumor-infiltrating macrophages in cancer nests than in cancer stroma (macrophages, nests > stroma) had significantly better survival than nests stroma) showed significantly better survival than in nests < stroma cases (MST 388 days vs 256 days; P = .0070). The proportion of tumor-infiltrating macrophages or CD8(+) T cells between cancer nests and stroma became independent prognostic factors in the multivariate analysis. Neither the number of mast cells in nests nor in stroma correlated with the clinical outcome. Evaluation of the numbers of macrophages and CD8(+) T cells in cancer nests and stroma are useful biomarkers for predicting the prognosis of stage IV NSCLC patients treated with chemotherapy, but could fail to predict chemotherapy response. (c) 2008 American Cancer Society.
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              Tumour immunity: effector response to tumour and role of the microenvironment.

              Substantial evidence shows that inflammation promotes oncogenesis and, occasionally, participates in cancer rejection. This paradox can be accounted for by a dynamic switch from chronic smouldering inflammation promoting cancer-cell survival to florid, tissue-disruptive inflammatory reactions that trigger cancer-cell destruction. Clinical and experimental observations suggest that the mechanism of this switch recapitulates the events associated with pathogen infection, which stimulate immune cells to recognise danger signals and activate immune effector functions. Generally, cancers do not have danger signals and, therefore, they cannot elicit strong immune reactions. Synthetic molecules have been developed that mimic pathogen invasion at the tumour site. These compounds activate dendritic cells to produce proinflammatory cytokines, which in turn trigger cytotoxic mechanisms leading to cancer death. Simultaneously, dendritic cells capture antigen shed by dying cancer cells, undergo activation, and stimulate antigen-specific T and B cells. This process results in massive amplification of the antineoplastic inflammatory process. Thus, although anti-inflammatory drugs can prevent onset of some malignant diseases, induction of T cells specific for tumour antigen by active immunisation, combined with powerful activation signals within the cancer microenvironment, might yield the best strategy for treatment of established cancers.

                Author and article information

                FEBS Open Bio
                FEBS Open Bio
                FEBS Open Bio
                12 May 2015
                12 May 2015
                : 5
                : 502-507
                [a ]Department of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, China
                [b ]Central Laboratory, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
                [c ]Medical College, Southeast University, Nanjing, Jiangsu, China
                Author notes
                [* ]Corresponding author. Tel.: +86 025 52887003; fax: +86 025 52887034. shukwang@ 123456163.com

                Contributed equally to this work and should be considered as co-first authors.

                © 2015 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                : 25 March 2015
                : 4 May 2015
                : 7 May 2015
                Research article

                nlr, neutrophil-to-lymphocyte ratio,os, overall survival,dfs, disease-free survival,rfs, recurrence-free survival,css, cancer specific survival,hr, hazard ratio,ci, confidence interval,breast cancer,inflammation,nlr,prognosis


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