Background
Diffuse large B cell lymphoma (DLBCL) is the most commonly occurring form of lymphoma, which occupies approximately 30–40% of preliminary diagnosed non-Hodgkin’s lymphomas (NHL). Despite the survival outcome of DLBCL patients has significantly improved [
1] by the addition of rituximab immunotherapy to standard cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) chemotherapy (R-CHOP) [
2], approximately thirty percent patients with advanced stage of DLBCL remain intractable and the disease could relapse [
3]. Prognostic assessment is important for designing of individualized therapy in DLBCL on the basis of accurate estimation of outcome.
A number of prognostic factors [
4] have been studied, such as gene expression profiling [
5], immunohistochemistry-based detection of prognostic biomarkers [
6] and early interim analysis with positron emission tomography [
7] following the initiation of R-CHOP therapy. However, many of these prognostic means are costly, difficult to perform, or not easily interpreted. Therefore, another prognostic models for DLBCL, which are inexpensive, widely available, and easily interpreted, are urgently needed for clinicians.
Recently, numerous studies have demonstrated that the ratio of different kinds of peripheral blood cells can be used to predict prognosis of lymphoma [
8,
9], such as lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), etc. Moreover, previous studies [
10‐
13] have showed the relationship between increased pretreatment NLR and poor prognosis in different tumors. However, due to the divergence in the study design and sample size, direct impact of NLR level on DLBCL patients’ survival and tumor’s clinicopathological parameters remains inconclusive. In this study, we searched PubMed and Embase and Web of Science databases for the relevant studies and performed a meta-analysis in order to determine the association between NLR and some clinicopathological parameters, as well as the prognostic role of NLR in DLBCL.
Materials and methods
Search strategy and selection of studies
This meta-analysis was carried out in accordance with the standard guidelines for meta-analyses and systematic reviews of tumor marker prognostic studies [
14,
15]. Relevant studies published before September, 2017 (date last searched), were identified through electronic searches using PubMed, Embase, and Web of Science databases. The following search terms were used: (1) “DLBCL” (e.g. “diffuse large B cell lymphoma” “B cell lymphoma” “lymphoma”); (2) “NLR” (e.g. “neutrophil to lymphocyte ratio” “neutrophil lymphocyte ratio” “neutrophil-to-lymphocyte ratio”); (3) “prognosis” (e.g. “outcome” “survival” “mortality” “recurrence”). Electronic searches were supplemented by scanning reference lists of articles identified for all relevant studies.
Studies were considered eligible if they met the following criteria: (1) patients were histopathologically diagnosed with DLBCL according to World Health Organization criteria [
16]; (2) correlation of pretreatment NLR with overall survival (OS) or progression free survival (PFS) was reported; (3) Studies failing to report hazard ratio (HR) and 95% confidence interval (CI) were included with sufficient data for estimation [
17]; (4) exclusion of abstracts, letters, reviews, case reports, and multiple published reports. When there were several reports concerning the same cohort we included the high quality and most recent publication in our meta-analysis.
All initially identified studies were screened of titles and/or abstracts; then full texts were retrieved for studies that satisfied all selection criteria. Each study was independently assessed for inclusion by two reviewers (Mu and Ai) and discrepancies within the reviewing pair were resolved by the third party (Sun and Hu).
Data collection and extraction
We used a predesigned data abstraction form to extract relevant information. The following details were extracted: (1) the family name of first author, year of publication, country (region) of the population studied, sample size, patient age, gender, follow-up period; (2) clinicopathological parameters including Ann Arbor stage, etc.; (3) survival data including OS and PFS/EFS; (4) cut-off value for defining “elevated NLR”. OS was defined as the interval between the medical treatment and the death of patient or the last follow-up. PFS was calculated from the date of treatment until the detection of the recurrence tumor or death from any cause.
Quality assessment
A quality assessment was independently performed in each of the included studies by two reviewers (Fan and Qin) using the Newcastle–Ottawa Quality Assessment Scale (NOS) [
18]. This scale uses a star system (with a maximum of nine stars) to evaluate a study in three domains: selection of participants, comparability of study groups, and the ascertainment of outcomes of interest. We judged studies that received a score of seven or more stars to be at low risk of bias, and those that scored less than seven to be at high risk of bias. This cut-off point was chosen according to the distribution of relative quality scores of all included studies. Any disagreement was resolved by the third party (Sun and Hu).
Statistical analysis
HR and 95% CI were obtained directly from each literature or from estimation according to the methods by Parmer et al. [
17]. The combined rate (odds ratio, OR) and its 95% CI were used to evaluate the strength of association between NLR and clinicopathological parameters.
Heterogeneity among included studies was checked by the χ2-based Q test and I2 test. If there was no significant heterogeneity between studies (p > 0.10, I2 < 40%), the fixed-effect model was used. Otherwise, the random-effects model was chosen. All statistical tests were two sided and the significance level was set at 5%.
A two-stage dose–response meta-analysis was conducted to assess whether NLR was associated with higher risks of mortality from DLBCL, based on specific cut-off values, distribution of death cases and person years, and adjusted HRs with 95% CIs. We use the generalized least square regression described by Orsini et al. [
19] to calculate the specific-study linear trend and 95% CIs for higher NLR within each study from the natural logs of adjusted HRs and 95% CIs, and pooled HRs and 95% CIs were obtained under the random-effects model. We approximately derived person years from follow-up duration and the number of participants at each NLR level. The midpoint of the higher NLR category was set at 1.2 times the lower boundary (specific cut-off value in each study). And we set the lower boundary to zero in the lower NLR category. We evaluated a potential curve linear association between NLR and risks of mortality from DLBCL, using restricted cubic splines with three knots at percentiles 10, 50, and 90% of the distribution [
20].
Because characteristics of populations, ascertainment of cut-off value and adjustments for confounding factors were not consistent between studies, we further conducted a sensitivity analysis by removing one or several studies to explore possible explanations for heterogeneity and to examine the influence of various exclusion criteria on the overall risk estimate.
Assessment of publication bias was first evaluated by the Begg’s funnel plot, and then performed for each of the pooled study groups using Egger’s bias indicator test [
21]. All analyses were carried out using STATA statistical software package version 14.0 (STATA, College Station, TX).
Discussion
Recently, several studies have shed light on the association between NLR and prognosis of cancer patients. However, these results are not comparable because of the heterogeneity on design and population, and the diversity in cut-off values defining “elevated NLR”. A previous meta-analysis combining 9 studies has shown that NLR was a significant indicator for poor OS and PFS from a total of 2297 individuals [
32]. Our study is an updated meta-analysis covering a total of 11 published studies with 2515 patients reporting the independent prognostic role of NLR in DLBCL patients treated with R-CHOP. Moreover, we conducted a dose–response meta-analysis to assess the association between NLR and risk of mortality from DLBCL among different cut-off values in the included studies. Because OS and PFS/EFS are correlated with each other, the 3-level random-effect meta-analysis model is applied to assess the prognostic role of NLR in DLBCL patients.
Several recent studies have demonstrated that the inflammatory nature of a tumor’s microenvironment is a critical component of tumor initiation, growth, and progression [
33,
34]. Furthermore, a variety of systemic inflammatory biomarkers have been identified and studied in patients with DLBCL, such as NLR [
35], serum LDH [
36], serum C-reactive protein (CRP) [
37], serum albumin [
38], etc. NLR has the advantage of low economic cost and wide availability, thereby drawing increasing attention. Mechanically, an elevated NLR is usually caused by neutrophilia and lymphopenia. Neutrophilia may lead to secretion of vascular endothelial growth factor (VEGF) and suppression of cytolytic activity of immune cells such as lymphocytes, natural killer cells, and activated T cells, thus accelerating tumor progression [
39,
40]. Lymphopenia indicates disease severity and is linked to the immune escape of tumor cells from tumor-infiltrating lymphocytes (TILs) [
41,
42]. Therefore, an elevated NLR generates a favorable immune microenvironment, thereby correlating to poor prognosis of patients.
The meta-analysis had some limitations that called for cautious interpretation of the results. First, only 11 studies published in full-text were included in this meta-analysis. Some information was missed and individual patient data were unattainable, which might decrease the accuracy of the results. Second, the cut-off value defining high NLR varied among individual studies (Table
1), which may have contributed to heterogeneity. Third, differences of paper quality and sample size across the studies might cause bias in the meta-analysis although subgroup analysis and meta regression did not show the paper quality or sample size as the resource of heterogeneity. Forth, most of the included studies reported positive results, therefore our results might overestimate the prognostic significance of NLR to some degree. However, there was no significant publication bias of the enrolled studies on OS or PFS/EFS.
Despite the above limitations, our meta-analysis supports the values of NLR as a promising independent risk factor of survival in DLBCL patients. NLR can be easily obtained from routine blood tests, thus intermediate assessments about changes in NLR during therapy were simply available. Keam et al. revealed that a reduction in NLR after R-CHOP therapy in patients with high pre-NLR was associated with better prognosis. Therefore, combining NLR with the IPI score helps to identify higher risk patients who need additional consolidation therapy, such as autologous stem cell transplantation. That is, NLR can help personalize the treatment intensity, as well as aftercare schedule, in order to increase the likelihood of early detection.
Conclusion
Here, we searched electronic databases for relevant studies, and enrolled 11 studies with a total of 2515 patients for meta-analysis, drawing a conclusion that patients with higher NLR were more likely to have poorer prognosis than those with lower NLR. Taken together, the results from our meta-analysis suggest that NLR gains a prognostic value for patients with DLBCL. More multi-center prospective cohorts are warranted to further validate the role of the NLR in DLBCL.
Authors’ contributions
SM and LA collected and analyzed the data, wrote the paper; FF and YQ extracted and analyzed the data; CS and YH conceived and designed this study, analyzed the data, wrote the paper; and all authors reviewed the paper. All authors read and approved the final manuscript.
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