Esophageal cancer is the seventh most frequent cancer worldwide, representing the 3.2% of all cancers, with a very high morality (5.3% of all deaths for cancer) (1). The 5-year survival in USA is 19.2%, showing that, despite the improvements in treatments and diagnostic tools, the prognosis remains poor. Therefore, the study and analysis of new prognostic factors is of paramount importance in order to provide the adequate treatment solution for each patient. As known, inflammatory response plays a key role in tumor growth (2) and a number of inflammation factors has been proposed as promising prognostic markers.
Measurable blood parameters that reflect the systemic inflammatory response includes C-reactive protein, cytokines, leucocytes and their subtypes, platelets (3). Recently, neutrophils-lymphocyte ratio (NLR) has been proposed as a prognostic indicator in several tumours. It is an easily measurable parameter consisting of the ratio of circulating blood neutrophils and lymphocytes. Neutrophils are a consistent part of peritumoral inflammatory cell infiltrate, named tumour-associated neutrophils (TANs). The infiltrate seems to be a direct result of cancer cell’s activity, suggesting that the presence of these neutrophils is related to tumour growth (4).
A meta-analysis of all available studies about NLR in all solid tumors, in 2014, showed that high NLR is associated with poor survival in many tumours, including gastroesophageal tumours, with a trend for the association of high NLR with worse OS to be greater for metastatic than non-metastatic disease (5). Small studies with cancer patients showed that chemotherapy can normalize elevated NLR early after the introduction of treatment and that patients with normalized NLR may have improved outcome (6,7).
The role of NLR in esophageal cancer has been investigated in several studies (Table 1), but its clinical relevance remains unclear (8). Most of the studies focus on preoperative NLR, and did not evaluate its evolution in postoperative period. The links between recurrence, immunosuppression and postoperative complications and infections remain unclear, as well as the role played by chemotherapy-related immunosuppression in the ratio normalization. A recent meta-analysis suggested that a lower preoperative NLR is associated with an improved survival in esophageal cancer patients, but their subgroup analysis about treatment modality and disease-free survival were inconclusive, obtaining non–statistically significant results (HR 1.20, P=0.27 and HR 1.54, P=0.20 respectively) (9).
In this context, the aim of our systematic review and meta-analysis is to assess the predictive value of pre-treatment NLR in forecasting the outcome of esophageal cancer patients. Furthermore, we have considered some sub-analyses in order to identify the differences in predicting the outcome of different treatment modalities and histological types.
We searched PubMed, Embase, Web of Science and Cochrane online databases with the following keywords: (“NLR”[All Fields] OR ((“neutrophils”[MeSH Terms] OR “neutrophils”[All Fields] OR “neutrophil”[All Fields]) AND (“lymphocytes”[MeSH Terms] OR “lymphocytes”[All Fields] OR “lymphocyte”[All Fields]))) AND (“oesophageal neoplasms”[All Fields] OR “esophageal neoplasms”[MeSH Terms] OR (“esophageal”[All Fields] AND “neoplasms”[All Fields]) OR “esophageal neoplasms”[All Fields]) in February 2017. Reference list of original articles and review articles were considered as additional source of information. We also searched the PROSPERO database. The literature search was restricted to articles published in English language, without restrictions about the year of publication.
The inclusion criteria we used are adapted from the REporting recommendations for tumour MARKer prognostic studies criteria (REMARK) (12). Inclusion criteria for the primary analysis were: (I) both prospective and observational studies reporting prognostic data on NLR in esophageal cancer patients without gender or anagraphic limitation; every stage of disease, histotype and treatment were considered; (II) studies reporting dichotomized data: comparison of low NLR and high NLR; (III) availability of HR including 95% CIs and P values (preferred) or Kaplan-Meier curves about overall survival (OS) or progression free survival (PFS) or disease free survival (DFS).
Two investigators extracted the data independently (G Pirozzolo, M Scarpa). To avoid systematic biases two authors independently reviewed all eligible studies until a complete concordance was reached for all assessed variables. Disagreements were resolved by discussion, with the participation of a third author (MI van Berge Henegouwen). Extracted data were: demographic data, patient’s characteristics, methodological data, OS HR, DFS HR, PFS HR, and postoperative complications. HR were extracted both from multivariate and univariate analysis, preferring data from multivariate analysis when available. When HR was not declared, it has been extracted from Kaplan-Meyer curves following the method described by Parmar (13).
Two investigators assessed retrieved articles quality according with the Newcastle-Ottawa scale for assessing the quality of non-randomized studies in meta-analysis. Studies with less than 5 stars in the Newcastle-Ottawa assessment were not included in our meta-analysis. We assessed the possibility of publication bias by graphical evaluation of symmetry in a funnel plot.
Extracted data were analysed using RevMan 4.3 analysis software. Generic inverse variance was used to pool hazard ratios. We used both Fixed-Effect model and Random-Effect model, depending on heterogeneity. Heterogeneity, assessed using I2 statistic, was considered relevant when >30%. Statistical significance was considered relevant when P<0.001.
After combined search, we identified 587 studies. After evaluation of titles and abstracts, we identified 29 full text. One study was excluded because it showed NLR as a continuous data (14). Two studies were excluded because they showed duplicate data (15,16). Six studies were excluded because of the lack of data on survival (HR and related cut-off) (14,17-21) and one of these did not report any survival data (20). The remaining 20 studies, including 6,457 patients, were all included in the analysis. None of the considered studies were excluded after qualitative assessment. The study selection diagram is reported in Figure 1. All studies were published between 2011 and 2017. Included studies characteristics are reported in Table 1. One study considered NLR both as a continuous data and as a dichotomized data but, in the second case, did not report HR (22). For three studies, including this one, we extracted HR from Kaplan-Meier curves using the method described by Parmar (23,24).
Nineteen studies had a retrospective design or reported a retrospective analysis of prospectively collected data. Only one study had a prospective design, reporting data from a phase III study (Real-2 study) (18,25).
In fourteen studies the main treatment was surgery (8,15,23,24,26-34) in three was neoadjuvant chemoradiation (NCRT) followed by surgery (22,24,35); in three was definitive chemoradiation (DCRT) (18,36,37). In one study the time of sampling was post-treatment (8). Chemotherapy treatment schemes, as reported in Table 1, are mainly 5-FU based or Cisplatin based. In 9 studies, having surgery as main treatment, the presence of preoperative or postoperative treatments was an exclusion criterion (8,15,23,24,28,31,33,38). Quality assessment is reported in Table 1: all selected studies were considered adequate, following our inclusion criteria. The funnel plot also showed substantial symmetry between the included studies.
Patients characteristics are reported in Table 2. Based on available data both adenocarcinoma (AC) and squamous cell carcinoma (SCC) are represented. One study included only AC patients (26); 13 studies included only SCC patients (8,15,23,24,28-30,32-34,37-39); the remaining studies considered both.
Mid-upper esophagus and lower esophagus-gastroesophageal junction were both well represented (3,000 and 2,784 patients respectively), but a sub-analysis based on tumor location was unfeasible for the lack of data.
NLR cut-off values
The NLR cut-off value ranges from 1.7 to 5 (mean 3.2). Different cut-offs were reported in the included studies: in 6 papers the cut-off was determined using receiver operating characteristic curves (C-index) (18,28,29,32,36,38), in other cases they mostly referred to literature, but the method of selection was unclear.
As previously reported three included study did not showed the OS HR as a dichotomized data, in this case HR has been extracted from Kaplan-Meier curves (22,24). All remaining OS HR are taken from multivariate analysis with the exception of one study (8) which OS HR is taken from univariate analysis. We pooled all OS HR, as showed in Figure 2. The comparison about overall survival of all included studies showed: HR 1.78 (95% CI: 1.46–1.93, P<0.00001, I2 =68%). We also performed sub-analysis considering the following parameters: main treatment modality, histotype, blood sample timing, cut-off method (ROC curve or obtained from existing literature). The results of quantitative synthesis, summarized in Table 3, did not show significant differences with the previous analysis, confirming the NLR predictive relevance.
Progression-free survival and disease-free survival
Ten studies reported data on PFS or DFS (18,23,26-28,31,36,38). We pooled these studies to obtain a sub-analysis for PFS and DFS (Figure 3). About DFS our analysis showed a 1.75 HR (95% CI: 1.35–2.26, P<0.00001, I2 =71%). The PFS HR is 1.66 (95% CI: 1.43–1.93, P<0.00001, I2 =0%).
The emerging role of systemic inflammation in postoperative complications and survival is a topic of research in several solid tumours (5,40,41). The present meta-analysis results showed a significant association between survival and systemic inflammation in esophageal cancer, considering NLR as an independent predictive marker. This parameter is relatively cheap, easy to evaluate in most medical centres and, being a ratio, the different ranges between laboratories have a limited impact.
If compared with the previous meta-analysis on the same argument (9) our study, including more data, reached more conclusive results. Furthermore, we considered as many variables as possible in performing a sub-analysis, such as treatment modality and histotype. Our analysis showed higher NLR is a significant prognostic marker of worse survival (Figure 2). This data is confirmed both in overall and in sub-analysis results. Interestingly NLR predicts survival independently of histotype (Table 3). Similarly, the treatment modality sub-analysis showed almost analogue results for the considered subgroups. The cut-off sub-analysis showed significant result for both considered methods, however some studies did not report the source of the cut-off threshold. A sub-analysis which considered tumor location and patients’ origin was unfeasible for lack of data, but it would have clarified possible geographic and anatomic differences. Similarly, a sub-analysis which considered NRL and survival rates per stage of disease was unfeasible, but would have been very useful in order to stratify the risk of worst prognosis per stage.
The mechanisms by which NLR is related to survival in esophageal cancer and other solid tumours are still unclear. The increased number of neutrophils in the peritumoral inflammatory cell infiltrate (TANs) can inhibit the antitumor activity of natural killer (NK) and activated T cells (4,42). Moreover, many cytokines (TNF, IL-1, IL-6) and VEGF, produced as result of neutrophils activation, may enhance tumour growth (43). The complexity of this relationship, which may seem paradoxical, could be summarized as follows: tumours produces inflammatory cytokines and chemokines and are infiltrated by leukocytes, but advanced neoplasms are associated with a defective systemic immune response (44). The role of neutrophil infiltration in tumor growth is controversial. Increasing experimental evidence indicate that neutrophils may directly or indirectly influence the tumor fate through the release of a wide array of molecules able to exert either pro-tumor or anti-tumor functions depending on the microenvironment milieu, including cytokines (45). Both human and murine activated neutrophils can produce and release is TRAIL, a trans-membrane/soluble molecule involved in tumor cell killing and autoimmunity (46,47). On the other hand, TANs have been shown to chemoattractants Tregs in a mouse model of cancer, mainly via CCL17 (47,48). Because neutrophil depletion, in this model, was shown to reduce Tregs recruitment and, consequently, tumor growth, data provide, for the first time, a clear link between TANs and Tregs, acting together to impair antitumor immunity (47,48). In fact, cancer immunoediting, mainly mediated by CD8 and CD4 T cells, macrophages, and NK cells, may lead to cancer cell destruction (cancer immunosurveillance) with complete cancer cells elimination, to an equilibrium phase or to an escape phase when cancer cells overcome immune defences and spread within the whole organism (49). A prevalence of neutrophils granulocytes over lymphocytes might be interpreted as a rough marker of immunosurveillance failure.
Few studies focused on the NLR variation through the neoadjuvant treatment. They are more difficult to interpreter because, even if there is not enough data within the included studies, there might be a direct effect of chemotherapy on the level of neutrophils and on lymphocytes ones. On the other hand, we analysed preoperative NLR and a time frame of at least 6–8 weeks should have provided the patients’ bone marrow time enough to recover. In any case, the effect of neoadjuvant systemic treatment on lowering NLR, improving, at the same time, survival has been shown in solid tumors (6,7,50,51). We found three studies which consider this effect in esophageal cancer (14,22,35). Noble showed that neutrophils count is statistically significantly lower in those patients who underwent neoadjuvant treatment, and that increasing NLR is an independent prognostic factor for reduced OS at multivariate analysis (22). Hyder et al., excluded from the qualitative analysis for the lack of data, showed that NLR increase is associated with a worse OS, but, on the other hand, with an improvement of PFS (14). In the third study, the survival analysis on NLR variations is incomplete due to the low number of patients with a NLR higher than the cut-off after the neoadjuvant treatment (35). These data are still largely unclear and, considering the relevance of neoadjuvant treatment on esophageal cancer, such as rectal cancer, this correlation should be evaluated in further research. In fact, there are not enough evidences in the included studies to confirm a decrease of NLR during neoadjuvant treatment is related to the decline of tumor load. It is even possible the opposite, a rise in NLR due to enhanced cell apoptosis during chemotherapy.
There are a number of limitations in our study. The major bias is the retrospective design of almost all included studies. The heterogeneity about treatment modalities, patients’ characteristics, duration of follow-up, samples timing and cut-off threshold are other sources of bias. Besides, several studies investigated NLR relevance as a prognostic marker for non-oncological diseases, mostly heart disease (52,53). Finally, neutrophils and lymphocytes are, by their very nature, easily influenced by inflammatory and infectious phenomena. All these conditions could have a confounding effect on NLR prognostic interpretation. In fact, one of the strengths of NLR is the fact that is a ratio, so different ranges between laboratories should have limited impact. On the contrary, we observed a widespread in cut-off values. These divergent cut off values may be due to heterogeneity on cut-off definition or heterogeneity in patient populations (age, sex, geographical origin, exposition) or heterogeneity in stage and histology of the disease or a mix of them.
In conclusion, our meta-analysis showed high NLR to be a predictor of adverse survival in esophageal cancer, both in SCC and in adenocarcinoma and therefore it could be promising as a factor predicting outcome. Further studies are needed to better define NLR role in therapeutic and diagnostic scenarios and use it to predict survival in preoperative setting. However, our analysis, suggests an actual use of this marker in clinical practice, also considering its negligible cost. NLR should be evaluated at the time of diagnosis and before surgery.
Conflicts of Interest: The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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