The currently study demonstrated that the pre-treatment PLR is an independent prognostic factor for OS. Moreover, patients diagnosed as PSCCE with the low PLR may have superior OS than those with the high PLR. NLR was also correlated with OS and TLC, NLR, as well as PLR were uncorrelated with other clinicopathologic factors. As far as we know, this is the first study to analysis the pre-treatment TLC, NLR and PLR in the prediction of OS in patients with PSCCE.
Recently, the systemic inflammation involved in the process of tumorigenesis . Chronic inflammation trigger molecular cascades in tumor cells, which promote tumor invasion and immune cell evasion . The cancer-related inflammation recruiting T lymphocytes and activating chemokines, forming a immunosuppressive microenvironment, results in the inhibited antitumor immunity followed by which promoting tumor growth and metastasis [20, 22]. Theoretically, after inflammatory cytokines release, the blood cells including neutrophil, lymphocyte, platelet and so on proliferate and differentiate on the instant. It is well known that Neutrophils produce angiogenic cytokines and induce angiogenesis in tumor cells. Neutrophilia is frequently found in cancer patients and is associated with a poor prognosis . In antitumor immune reactions, lymphocytes induce tumor cell apoptosis and suppress tumor cell proliferation and metastasis . Platelet contributes a lot in tumor growth, infiltration and dissemination . The activation of platelets can lead to the release of angiogenic growth factors. Also, their adherence to tumor micro-vessels may enhance the vascular permeability . Many studies have reported that cancer produce interleukin-1, and interleukin-6, granulocyte colony-stimulating factor, as well as tumor necrosis factor-alpha, which may cause neutrophilia. The neutrophilia and thrombocytosis always symbolize a nonspecific response to the cancer-related inflammation [22, 28]. Above all, systemically inflammatory biomarkers such as the TLC, NLR, and PLR are expected to predict tumor prognosis. Systemic chemotherapy, radiotherapy or post-operative stress response will inevitably influence the count of hematological components. Thus, we assess the potential prognostic value of TLC, NLR and PLR in patients with PSCCE who are newly diagnose.
In previous studies, the utility of inflammation biomarkers as a prognostic factor was investigated in various types of solid tumors. Chen and K. Raghav et al demonstrated high NLR was an independent poor prognostic marker in colorectal cancer . Suzuki R et al identified low TLC and high NLR was associated with inferior survival in the extensive-stage small-cell lung cancer . Luo et al indicated high PLR was an independent prognostic indicator of short OS in patients of early stage non-small cell lung cancer who received SABR . Ye et al reported that both high NLR and PLR were correlated with poor survival in patients of nasopharyngeal carcinoma . A meta-analysis by H. Yodying et al showed elevated pretreatment NLR and PLR were remarkably associated with unfavorable OS of Esophageal Cancer . In patients undergoing surgery for esophageal squamous cell cancer, PLR was revealed as an independent prognostic factor, moreover, a significant different survival was found between patients with high NLR group and low NLR group . The results were similar to our analysis. Likewise, Feng et al suggested that PLR should be superior to NLR as a predictive factor in esophageal squamous cell cancer . In addition, others reported that NLR was regarded as an independent prognostic factor for patients with PSCCE . This is mainly because of different inclusion criteria and a various cutoff value of NLR. In the current study, the patients who underwent surgery preceded by neoadjuvant therapy or only accepted chemoradiotherapy and the patients who diagnosed as distant metastasis were included in the analysis. Wang and Liu et al suggested the cut-off value to be 2.97 by the ROC analysis and the area under the curve was 0.702, with the same methods, the cut-off value of this study was calculated as 2.37 and the area under the curve was 0.713. To date, there is no recognizably optimal cut off point of inflammatory biomarkers. Future researches are needed.
Such limitations that retrospective study, a small sample size and the date from a single institution must be taken into consideration in our study. In addition, other biomarkers of the systemic inflammatory response, for example C-reactive protein, fibrinogens, albumin were not included in the analysis. Therefore, large, prospective, multi-center and randomized controlled trials are required to confirm our results.