Literature DB >> 28057046

Prognostic role of neutrophil-to-lymphocyte ratio in breast cancer: a systematic review and meta-analysis.

Josee-Lyne Ethier1,2, Danielle Desautels3, Arnoud Templeton4, Prakesh S Shah5,6, Eitan Amir7,8.   

Abstract

BACKGROUND: The presence of a high neutrophil-to-lymphocyte ratio (NLR) has been associated with increased mortality in several malignancies. Here, we quantify the effect of NLR on survival in patients with breast cancer, and examine the effect of clinicopathologic factors on its prognostic value.
METHODS: A systematic search of electronic databases was conducted to identify publications exploring the association of blood NLR (measured pre treatment) and overall survival (OS) and disease-free survival (DFS) among patients with breast cancer. Data from studies reporting a hazard ratio (HR) and 95% confidence interval (CI) or a P value were pooled in a meta-analysis. Pooled HRs were computed and weighted using generic inverse variance. Meta-regression was performed to evaluate the influence of clinicopathologic factors such as age, disease stage, tumor grade, nodal involvement, receptor status, and NLR cutoff on the HR for OS and DFS. All statistical tests were two-sided.
RESULTS: Fifteen studies comprising a total of 8563 patients were included. The studies used different cutoff values to classify high NLR (range 1.9-5.0). The median cutoff value for high NLR used in these studies was 3.0 amongst 13 studies reporting a HR for OS, and 2.5 in 10 studies reporting DFS outcomes. NLR greater than the cutoff value was associated with worse OS (HR 2.56, 95% CI = 1.96-3.35; P < 0.001) and DFS (HR 1.74, 95% CI = 1.47-2.07; P < 0.001). This association was similar in studies including only early-stage disease and those comprising patients with both early-stage and metastatic disease. Estrogen receptor (ER) and HER-2 appeared to modify the effect of NLR on DFS, because NLR had greater prognostic value for DFS in ER-negative and HER2-negative breast cancer. No subgroup showed an influence on the association between NLR and OS.
CONCLUSIONS: High NLR is associated with an adverse OS and DFS in patients with breast cancer with a greater effect on disease-specific outcome in ER and HER2-negative disease. NLR is an easily accessible prognostic marker, and its addition to established risk prediction models warrants further investigation.

Entities:  

Keywords:  Breast cancer; Disease-free survival; Meta-analysis; Neutrophil-to-lymphocyte ratio; Overall survival; Prognosis; Systematic review

Mesh:

Year:  2017        PMID: 28057046      PMCID: PMC5217326          DOI: 10.1186/s13058-016-0794-1

Source DB:  PubMed          Journal:  Breast Cancer Res        ISSN: 1465-5411            Impact factor:   6.466


Background

The short-term and long-term prognosis of breast cancer depends on patient and tumor factors such as age, disease stage, and biological factors such as grade and receptor status. However, the behavior of breast cancer is unpredictable, with markedly different clinical outcomes seen even amongst patients with similar classical prognostic factors [1]. Inflammatory cells and mediators in the tumor microenvironment are thought to play an important role in cancer progression, and may account for some of this variability [2]. The presence of an elevated peripheral neutrophil-to-lymphocyte (NLR) ratio, an indicator of systemic inflammation, has been recognized as a poor prognostic factor in various cancers [3]. In a previous meta-analysis of 100 studies of patients with unselected solid tumors, increased NLR was associated with decreased overall survival (OS) (hazard ratio (HR) 1.81; 95% confidence interval (CI) = 1.67–1.97; P < 0.001) [4]. This effect was observed in all disease sites, subgroups, and stages. However, this study was not specific to breast cancer, and did not examine the impact of prognostic factors such as estrogen receptor (ER) or progesterone receptor (PR) status, HER2 status, disease stage, or menopausal status. The aim of this study was to quantify the effect of peripheral blood NLR on OS and disease-free survival (DFS) in adult women with invasive breast cancer. We also examined the effect of clinicopathologic factors on the prognostic value of NLR.

Methods

Data sources and searches

This analysis was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [5]. The search strategy developed by Templeton et al. [4] was used with the addition of “breast neoplasms” and synonymous breast cancer-specific terms. An electronic search of the following databases was performed: Medline (host: OVID), Medline in Process, Medline Epub Ahead of Print (host: OVID), EMBASE (host: OVID), and Cochrane Database of Systematic Reviews. All databases were searched from January 2013 to April 2016, supplementing the initial systematic review that searched databases until different time points in 2013. Citation lists of retrieved articles were screened manually to ensure sensitivity of the search strategy. The full search strategy is described in Table 3 in Appendix 1.

Study selection

In order to reduce clinical heterogeneity, the following eligibility criteria were utilized: studies of adult women with breast cancer reporting on the prognostic impact of the peripheral blood NLR, where NLR was treated as a categorical variable; NLR collected prior to all treatment (surgery and/or systemic therapy); reporting of a multivariable HR for OS, and/or DFS or progression-free survival (PFS), and corresponding 95% CI and/or P value; available as a full-text publication; clinical trials, cohort studies, or case–control studies; and English-language publication. Case reports, conference proceedings, and letters to editors were excluded. Corresponding authors were contacted to clarify missing or ambiguous data. When multiple publications or data analyses were available from the same dataset and if clarification on potentially duplicate data could not be obtained, the study reporting the larger number of patients was retained and other studies were excluded. Studies only presenting data in graphic form without reporting a numerical value for HR were excluded. All titles identified by the search were evaluated, and all potentially relevant publications were retrieved in full. Two reviewers (JE and DD) independently reviewed full articles for eligibility based on inclusion criteria and data extraction, and disagreements were resolved by consensus. Three relevant articles identified in the previous systematic review were also included [4].

Data extraction

The following details were extracted from included studies using predesigned data abstraction forms: name of first author, year of publication, journal, number of patients included in analysis, median age, disease stage (nonmetastatic, metastatic, mixed (nonmetastatic and metastatic)), collection of data (prospective, retrospective), cutoff value used to define high NLR, number of patients with each breast cancer subtype, number of premenopausal and postmenopausal patients, and HRs and associated 95% CIs for OS, PFS, or DFS. Where more than one multivariable model was reported, HRs were extracted from models including the most participants.

Risk of bias assessment

Validity of included studies was assessed by two independent reviewers (J-LE and DD) using the Quality in Prognostic Studies (QUIPS) tool as described previously [6]. The QUIPS tool comprises 30 questions categorized into six domains (study participation, study attrition, prognostic factor measurement, outcome measurement, study confounding, and statistical analysis and reporting). Studies were rated according to each domain as being at low, moderate, or high risk of bias, based on the likelihood that they might alter the relationship between the prognostic factor and outcome.

Statistical analyses

Extracted data were pooled using RevMan 5.3 analysis software (Cochrane Collaboration, Copenhagen, Denmark). A meta-analysis was conducted for all included studies for each of the endpoints of interest if appropriate when clinical heterogeneity was minimal. The primary outcome of interest was OS, and intermediate endpoints such as PFS and/or DFS were secondary outcomes. Estimates for HRs were pooled and weighted by generic inverse variance, and were computed by fixed-effects or random-effects modeling. Heterogeneity was assessed using Cochran Q and I 2 statistics. If significant heterogeneity was present (I 2 > 50% or Cochran Q < 0.1), a random-effects model was used. Predefined subgroup analyses were conducted for disease stage (early, metastatic, mixed) using methods described by Deeks et al. [7] Meta-regression was performed to evaluate the effects of NLR cutoff, proportion of ER-positive patients, proportion of HER2-positive patients, proportion of triple-negative patients, median age, proportion of premenopausal patients, and proportion of patients with metastatic disease on the HR for OS and DFS. Meta-regression comprised a univariable linear regression weighted by individual study inverse variance and was performed using SPSS version 24 (IBM Corp, Armonk, NY, USA). A post-hoc meta-regression analysis testing the association between median duration of follow-up and the prognostic value of NLR was also performed. Multivariable meta-regression was not performed due to the small number of eligible studies leading to an undesirable risk of over-fitting. Publication bias was assessed by inspecting funnel plots visually. All statistical tests were two-sided, and statistical significance was defined as P < 0.05.

Results

Fifteen studies comprising a total of 8563 patients were included (Fig. 1). Characteristics of included studies are described in Table 1, and further details are included in Table 4 in Appendix 2. All studies collected data retrospectively, and all were published in 2012 or later. Ten studies included only patients with early-stage breast cancer, while five included both early and metastatic disease.
Fig. 1

Flow chart of study selection process. HR hazard ratio, NLR neutrophil-to-lymphocyte

Table 1

Characteristics of included studies

StudyYearNumber of patientsDisease stageNLR cutoff value
Overall survival
 Azab et al. [23]a 2012316Mixed3.3
 Azab et al. [13]a 2013437Mixed3.3
 Bozkurt et al. [24]201585Early2.0
 Dirican et al. [25]20151527Mixed4.0
 Forget et al. [10]2014720Early3.3
 Jia et al. [14]20151570Early2.0
 Koh et al. [8]2014157Early2.3
 Koh et al. [15]20151435Mixed5.0
 Nakano et al. [9]2015167Early2.5
 Noh et al. [26]a 2013442Early2.5
 Pistelli et al. [27]201590Early3.0
 Rimando et al. [28]2016461Mixed3.8
 Yao et al. [11]2014608Early2.6
Disease-free survival
 Asano et al. [12]201661Early3.0
 Bozkurt et al. [24]201585Early2.0
 Dirican et al. [25]20151527Mixed4.0
 Forget et al. [10]2014720Early3.3
 Hong et al. [29]2015487Early1.9
 Jia et al. [14]20151570Early2.0
 Koh et al. [8]2014157Early2.3
 Nakano et al. [9]2015167Early2.5
 Pistelli et al. [27]201590Early3.0

NLR neutrophil-to-lymphocyte

aIncluded in previous meta-analysis [4]

Flow chart of study selection process. HR hazard ratio, NLR neutrophil-to-lymphocyte Characteristics of included studies NLR neutrophil-to-lymphocyte aIncluded in previous meta-analysis [4]

Overall survival

Thirteen studies comprising a total of 8015 patients reported adjusted HRs for OS. The median cutoff value for high NLR was 3.0 (range 2.0–5.0). Median follow-up was reported in 11 studies, and ranged from 1.8 to 7.2 years (mean 4.69 years) (Table 4 in Appendix 2). Overall, a NLR greater than the cutoff value was associated with worse OS (HR 2.56, 95% CI = 1.96–3.35; P < 0.001; see Fig. 2). There was statistically significant heterogeneity (Cochran Q = 0.009, I 2 = 55%). This seems to be largely influenced by one study which showed a large effect size [8]. However, the association between NLR and OS was maintained in a sensitivity analysis omitting this study (HR 2.42, 95% CI = 1.89–3.09; P < 0.001; Cochran Q = 0.03, I 2 = 48%), although statistically significant heterogeneity remained.
Fig. 2

Forest plots showing HRs for OS (a) and DFS (b) for neutrophil-to-lymphocyte ratio (NLR) greater than or less than the cutoff value. HRs for each study represented by squares: size of the square represents the weight of the study in the meta-analysis, and the horizontal line crossing the square represents the 95% confidence interval (CI). All statistical tests were two-sided

Forest plots showing HRs for OS (a) and DFS (b) for neutrophil-to-lymphocyte ratio (NLR) greater than or less than the cutoff value. HRs for each study represented by squares: size of the square represents the weight of the study in the meta-analysis, and the horizontal line crossing the square represents the 95% confidence interval (CI). All statistical tests were two-sided Exploratory analysis identified breast cancer stage as an important source of heterogeneity. Subgroup analysis showed that the association between NLR and OS was maintained in studies including only early-stage disease, as well as those comprised of patients with both early and metastatic disease (HR 2.98 vs 2.30 respectively; P for subgroup differences = 0.36). There was no statistical heterogeneity when the study driving heterogeneity in the main analysis [8] was omitted from the early stage subgroup (Cochran Q = 0.28, I 2 = 20%). Additionally, the effect of NLR on OS was retained (HR 2.56, 95% CI = 1.82–3.60; P < 0.001). Statistical heterogeneity remained among studies with mixed early and metastatic disease (Cochran Q = 0.01, I 2 = 69%). Adjustment for age differences between arms was examined in individual studies. In one study, patients were significantly older in the arm with low NLR, and it was unclear whether the multivariable model was adjusted for age [9]. In two other studies, the median age in each arm was not reported, and age did not seem to be included in the multivariable model [10, 11]. In a sensitivity analysis excluding these three studies, high NLR remained a significant predictor for shorter OS (HR 2.55, 95% CI = 2.59–8.26; P < 0.001). Table 2 presents the results of the meta-regression analysis. We did not identify any classical clinicopathologic factors that were effect modifiers for influence of NLR on OS. Additionally, the median duration of follow-up did not affect the association between high NLR and OS.
Table 2

Meta-regression for the association of clinicopathologic factors and the hazard ratio for disease-free and overall survival

VariableStudies included in analysisStandardized β coefficient P value
Overall survival
 Median age[8, 9, 11, 1315, 2628]0.0980.80
 ER positive[911, 13, 15, 2327]0.0840.81
 HER2 positive[811, 14, 15, 2327]–0.400.22
 Triple negative[8, 14, 24, 27]0.050.93
 Grade 1 or 2[8, 10, 14, 15, 2325]0.020.95
 Grade 3[8, 10, 14, 15, 2325]–0.020.95
 Stage 0–I[9, 13, 23, 25, 27, 28]0.680.14
 Stage II[9, 13, 23, 25, 27, 28]–0.300.56
 Stage III[9, 13, 25, 27, 28]–0.730.16
 Metastatic disease[811, 1315, 2428]–0.290.35
 Premenopausal[24, 25]0.040.95
 Nodal involvement[811, 1315, 2327]–0.040.90
 NLR cutoff value[8, 10, 1315, 23, 24]–0.290.33
 Median follow-up[811, 13, 14, 23, 2528]–0.160.64
Disease-free survival
 Median age[8, 9, 14, 27, 29]0.060.93
 ER positive[9, 10, 12, 24, 25, 27, 29]–0.770.04*
 HER2 positive[810, 12, 14, 24, 25, 27, 29]–0.790.01*
 Triple negative[8, 12, 14, 24, 27, 29]0.630.18
 Grade 1 or 2[810, 12, 14, 24, 25, 27, 29]–0.460.21
 Grade 3[810, 12, 14, 24, 25, 27, 29]0.460.21
 Stage 0–I[9, 25, 27, 29]0.460.54
 Stage II[9, 25, 27, 29]0.530.36
 Stage III[9, 25, 27, 29]–0.500.39
 Metastatic disease[25]–0.740.49
 Premenopausal[9, 12, 24, 25, 27]0.430.40
 Nodal involvement[810, 12, 14, 24, 25, 27, 29]0.250.52
 NLR cutoff value[810, 12, 14, 24, 25, 27, 29]–0.150.70
 Median follow-up[810, 12, 14, 25, 27, 29]–0.190.66

ER estrogen receptor, NLR neutrophil-to-lymphocyte

*Statistically significant at P < 0.05

Meta-regression for the association of clinicopathologic factors and the hazard ratio for disease-free and overall survival ER estrogen receptor, NLR neutrophil-to-lymphocyte *Statistically significant at P < 0.05 There was evidence of publication bias, with fewer smaller studies reporting lower magnitude associations between NLR and OS (Fig. 3).
Fig. 3

Funnel plots of HR for OS (a) and DFS (b) for high NLR ratio (horizontal axis) and the standard error (SE) for the HR (vertical axis). Each study is represented by one circle. Vertical line represents the pooled effect estimate

Funnel plots of HR for OS (a) and DFS (b) for high NLR ratio (horizontal axis) and the standard error (SE) for the HR (vertical axis). Each study is represented by one circle. Vertical line represents the pooled effect estimate

Disease-free survival

Nine studies comprising 4864 patients reported HRs for DFS. All studies included only patients with nonmetastatic disease. The median cutoff value for high NLR was 2.5 (range 1.9–4.0). Median length of follow-up was reported in eight studies, ranging from 1.8 to 7.2 years (mean 4.5 years) (Table 4 in Appendix 2). Overall, a NLR greater than the cutoff value was associated with worse DFS (HR 1.74, 95% CI = 1.47–2.07; P < 0.001; see Fig. 2). There was no evidence of statistically significant heterogeneity (Cochran Q = 0.14, I 2 = 35%). Adjustment for age differences between arms was examined in individual studies. Two studies had significant age differences between arms and no clear model adjustment for age, including one study where patients were significantly older in the arm with low NLR [9] and one study where the same group was significantly younger [12]. Another study did not report the median age in each arm and did not adjust for age in the multivariable model [10]. In a sensitivity analysis excluding these three studies, high NLR remained a significant predictor for shorter DFS (HR 1.69, 95% CI = 1.40–2.03; P < 0.001). All studies reported the number of patients with HER2-positive disease, while seven of nine studies included data on ER status (Table 4 in Appendix 2). Meta-regression analysis is presented in Table 2. Results showed that ER and HER2 positivity were negative effect modifiers of the association between NLR and DFS, indicating that the NLR has a greater prognostic value in breast cancers that are ER-negative and/or HER2-negative. The proportion of patients with triple-negative or metastatic disease, median age, disease stage, histologic tumor grade, presence of nodal involvement, premenopausal status, median duration of follow-up, and NLR cutoff value did not affect the association between high NLR and DFS. There was evidence of publication bias, with fewer smaller studies reporting lower magnitude associations between NLR and DFS (Fig. 3). The risk of bias in individual studies is summarized in Figure 4 in Appendix 3. Overall, risk of bias was low, particularly in the domains of study attrition, prognostic factor measurement, outcome measurement, and statistical analysis and reporting. There was a low–moderate risk of bias for the study participation domain due to lack of completeness in description of the baseline study sample in three studies [8, 13, 14]. Risk of bias was moderate with regards to study confounding, because four studies failed to adequately detail covariates included in adjusted models [8, 10, 12, 15].

Discussion

High NLR is associated with poor survival in patients diagnosed with several types of cancer [4]. Here we performed a breast cancer-specific meta-analysis, including 15 studies comprising 8563 patients, and found a significant prognostic effect for NLR on both OS and DFS. While there was evidence of publication bias, potentially indicating bias towards publication of positive studies, the overall risk of bias was low, as assessed with the QUIPS tool. The magnitude of effect on DFS was highest in ER-negative and HER2-negative subtypes. However, this finding does not rule out an effect in ER-positive or HER2-positive subgroups. Rather, the finding indicates a greater magnitude of effect in ER-negative and/or HER2-negative breast cancers. It is possible that the smaller magnitude of effect seen in ER-positive and/or HER2-positive disease relates to the relatively short duration of follow-up of included studies; recurrences occur later in follow-up with ER-positive disease compared with ER-negative disease. However, in a post-hoc meta-regression analysis, median follow-up did not significantly alter the association of NLR with either DFS or OS. Unfortunately, a stratified meta-regression based on ER status was not possible. Some uncertainty therefore remains about the effect of duration of follow-up on subgroups defined by receptor expression. Despite a greater magnitude of association between NLR and DFS in certain subgroups, patient and disease characteristics did not significantly alter the magnitude of effect of NLR on OS. The negative prognostic effect of NLR on OS was consistent in all clinicopathologic groups and was not influenced by the duration of follow-up in individual studies. One possible explanation for this is that a proportion of breast cancer patients die of causes other than breast cancer, especially cardiovascular disease [16, 17]. Increased NLR has been associated with higher coronary heart disease mortality [18]. The competing risks of cardiovascular and breast cancer deaths may have led to difficulty in exploring the influence of breast cancer-specific characteristics on OS. While the association between increased NLR and poor outcomes is not fully understood, it has been proposed that high NLR may be indicative of inflammation. In particular, neutrophils have been shown to inhibit the immune system and promote tumor growth by suppressing the activity of lymphocytes and T-cell response [19, 20]. Increased lymphocytic tumor infiltration has also been associated with improved DFS in ER-negative/HER2-negative breast cancer [21]. In our study, we found a greater magnitude of effect on DFS in patients with ER-negative and/or HER2-negative disease. However, while this indicates the potential importance of lymphocyte activity, the association between increased tumor-infiltrating lymphocytes and peripheral blood lymphocytes remains unclear. Furthermore, the greater magnitude of association in patients with ER-negative and/or HER2-negative breast cancers was not seen with triple-negative disease. This observation may be due to the relatively small number of studies reporting outcomes in patients with triple-negative breast cancer; the majority of studies identified patients based on independent subgroups based on ER and HER2 status. While there are several clinicopathologic factors associated with increased risk of recurrence and/or mortality in patients with breast cancer, the NLR is an inexpensive, readily available prognostic marker, and may allow refinement of risk estimates within disease stages and subgroups. Future studies using NLR in combination with other prognostic markers could potentially identify lower risk patients in whom treatment de-escalation may be appropriate. Furthermore, whether NLR is predictive of response to treatment or provides additional information in cases where risk stratification models exist, such as the 21-gene assay in node-negative ER-positive/HER2-negative disease, is unknown. However, previous research showed no association between NLR and the 21-gene assay recurrence score, indicating that the poor outcomes in patients with high NLR cannot be explained by the proliferation of ER signaling [22]. Further studies examining whether NLR may help refine established prognostic scores are therefore warranted.

Conclusion

High NLR is associated with an adverse OS and DFS in patients with breast cancer, and its prognostic value is consistent among different clinicopathologic factors such as disease stage and subtype. NLR is an easily accessible prognostic marker, and its addition to established risk prediction models warrants further investigation.
Table 3

Search strategya

NumberSearchesResultsType
1exp Breast Neoplasms/241,242Advanced
2(breast? adj6 cancer*).mp,kw.203,097Advanced
3(breast? adj6 neoplas*).mp,kw.241,382Advanced
4(breast? adj6 carcin*).mp,kw.62,218Advanced
5(breast? adj6 tumo?r*).mp,kw.46,556Advanced
6(breast? adj6 adenocarcin*).mp,kw.4642Advanced
7(breast? adj6 adeno-carcin*).mp,kw.10Advanced
8(breast? adj6 sarcoma*).mp,kw.1271Advanced
9(breast? adj6 dcis).mp,kw.1258Advanced
10(breast? adj6 ductal).mp,kw.16,064Advanced
11(breast? adj6 infiltrating).mp,kw.1418Advanced
12(breast? adj6 intraductal).mp,kw.2294Advanced
13(breast? adj6 lobular).mp,kw.4044Advanced
14(breast? adj6 medullary).mp,kw.383Advanced
15(breast? adj6 comedo*).mp,kw.75Advanced
16(breast? adj6 metast*).mp,kw.26,054Advanced
17(breast? adj2 malignan*).mp,kw.4962Advanced
18(breast? adj6 onco*).mp,kw.3338Advanced
19(mammar* adj6 cancer*).mp,kw.5493Advanced
20(mammar* adj6 neoplas*).mp,kw.21,985Advanced
21(mammar* adj6 carcin*).mp,kw.11,584Advanced
22(mammar* adj6 tumo?r*).mp,kw.18,026Advanced
23(mammar* adj6 adenocarcin*).mp,kw.2958Advanced
24(mammar* adj6 adeno-carcin*).mp,kw.3Advanced
25(mammar* adj6 sarcoma*).mp,kw.384Advanced
26(mammar* adj6 ductal).mp,kw.937Advanced
27(mammar* adj6 intraductal).mp,kw.117Advanced
28(mammar* adj6 infiltrating).mp,kw.201Advanced
29(mammar* adj6 lobular).mp,kw.151Advanced
30(mammar* adj6 medullary).mp,kw.19Advanced
31(mammar* adj6 comedo*).mp,kw.6Advanced
32(mammar* adj6 metast*).mp,kw.2554Advanced
33(mammar* adj6 malignan*).mp,kw.1506Advanced
34(mammar* adj6 dcis).mp,kw.61Advanced
35(ductal adj6 situ).mp,kw.6301Advanced
36(ductal adj6 carcino*).mp,kw.25,790Advanced
37(paget?? adj6 breast?).mp,kw.367Advanced
38(paget?? adj6 nipple?).mp,kw.363Advanced
39phyllodes.mp,kw.1876Advanced
40phylloides.mp,kw.206Advanced
41cystosarcoma*.mp,kw.603Advanced
42DCIS.mp,kw.3401Advanced
43or/1-40318,397Advanced
44exp Ovarian Neoplasms/71,707Advanced
45(ovar* adj6 cancer*).mp,kw.44,037Advanced
46(ovar* adj6 neoplas*).mp,kw.71,929Advanced
47(ovar* adj6 tumo?r*).mp,kw.24,113Advanced
48(ovar* adj6 malignan*).mp,kw.7601Advanced
49(ovar* adj6 metasta*).mp,kw.5781Advanced
50(ovar* adj6 carcin*).mp,kw.18,742Advanced
51(ovar* adj6 adenocarcin*).mp,kw.2966Advanced
52(ovar* adj6 adeno-carcin*).mp,kw.12Advanced
53(ovar* adj6 choriocarcin*).mp,kw.217Advanced
54(granulosa adj6 cancer*).mp,kw.54Advanced
55(granulosa adj6 tumo?r*).mp,kw.2699Advanced
56(granulosa adj6 neoplas*).mp,kw.173Advanced
57(granulosa adj6 malignan*).mp,kw.142Advanced
58(granulosa adj6 metasta*).mp,kw.111Advanced
59(granulosa adj6 carcin*).mp,kw.118Advanced
60(granulosa adj6 adenocarcin*).mp,kw.45Advanced
61(granulosa adj6 adeno-carcin*).mp,kw.0Advanced
62OGCTs.mp,kw.28Advanced
63HBOC.mp,kw.650Advanced
64Luteoma*.mp,kw.203Advanced
65Sertoli-Leydig*.mp,kw.1039Advanced
66Thecoma*.mp,kw.1013Advanced
67(theca* adj6 tumo?r*).mp,kw.493Advanced
68(ovar* adj6 dysgerminoma?).mp,kw.467Advanced
69androblastoma*.mp,kw.321Advanced
70arrhenoblastoma*.mp,kw.349Advanced
71arrheno-blastoma*.mp,kw.1Advanced
72Meig*.mp,kw.2152Advanced
73or/44-7293,590Advanced
74exp Endometrial Neoplasms/17,416Advanced
75(endometr* adj6 neoplas*).mp,kw.17,866Advanced
76(endometr* adj6 cancer*).mp,kw.15,307Advanced
77(endometr* adj6 tumo?r*).mp,kw.5128Advanced
78(endometr* adj6 carcino*).mp,kw.12,730Advanced
79(endometr* adj6 adenocarcin*).mp,kw.5361Advanced
80(endometr* adj6 adeno-carcin*).mp,kw.9Advanced
81(endometr* adj6 sarcoma*).mp,kw.1230Advanced
82(endometr* adj6 malignan*).mp,kw.2300Advanced
83(endometr* adj6 metast*).mp,kw.1337Advanced
84(endometr* adj6 onco*).mp,kw.370Advanced
85(endometr* adj6 choriocarcin*).mp,kw.88Advanced
86or/74-8531,774Advanced
87Uterine Cervical Neoplasms/65,130Advanced
88(cervi* adj6 cancer*).mp,kw.41,277Advanced
89(cervi* adj6 neoplas*).mp,kw.69,153Advanced
90(cervi* adj6 tumo?r*).mp,kw.7715Advanced
91(cervi* adj6 malignan*).mp,kw.3006Advanced
92(cervi* adj6 metast*).mp,kw.6612Advanced
93(cervi* adj6 onco*).mp,kw.1280Advanced
94(cervi* adj6 carcin*).mp,kw.24,588Advanced
95(cervi* adj6 adenocarcin*).mp,kw.2945Advanced
96(cervi* adj6 adeno-carcin*).mp,kw.9Advanced
97(cervi* adj6 squamous*).mp,kw.7833Advanced
98(cervi* adj6 adenosquamous*).mp,kw.211Advanced
99(cervi* adj6 adeno-squamous*).mp,kw.2Advanced
100(cervi* adj6 sarcoma*).mp,kw.661Advanced
101(cervi* adj6 small cell*).mp,kw.364Advanced
102(cervi* adj6 large cell*).mp,kw.78Advanced
103(cervi* adj6 neuroendocrine*).mp,kw.195Advanced
104(cervi* adj6 neuro-endocrine*).mp,kw.2Advanced
105(cervi* adj6 choriocarcin*).mp,kw.112Advanced
106SCCC.mp,kw.46Advanced
107or/87-10690,890Advanced
10873 or 86 or 107199,155Advanced
109exp Lymphocytes/461,529Advanced
110lymphocyte?.mp,kw.554,948Advanced
111(lymphoid adj2 cell?).mp,kw.22,666Advanced
112(killer adj4 cell?).mp,kw.51,337Advanced
113(nk adj2 cell?).mp,kw.31,413Advanced
114(lak adj2 cell?).mp,kw.2650Advanced
115b-lymphocyte?.mp,kw.93,264Advanced
116t-lymphocyte?.mp,kw.290,882Advanced
117b-lymphoid.mp,kw.2219Advanced
118t-lymphoid.mp,kw.1196Advanced
119(plasm adj2 cell?).mp,kw.31Advanced
120plasmacyte?.mp,kw.341Advanced
121(immune adj3 cell?).mp,kw.58,743Advanced
122(immunocompetent adj2 cell?).mp,kw.3494Advanced
123immnunocyte?.mp,kw.0Advanced
124immnuno-cyte?.mp,kw.0Advanced
125lymph cell?.mp,kw.184Advanced
126null cell?.mp,kw.3404Advanced
127immunological* competent cell?.mp,kw.153Advanced
128immunoreactive cell?.mp,kw.6231Advanced
129immuno-reactive cell?.mp,kw.18Advanced
130prolymphocyte?.mp.218Advanced
131pro-lymphocyte?.mp.3Advanced
132or/109-131648,538Advanced
133Neutrophils/77,202Advanced
134neutrophil*.mp,kw.135,327Advanced
135(cell? adj2 le).mp,kw.868Advanced
136(leukocyte? adj3 polymorphonuclear).mp,kw.14,471Advanced
137pmn granulocyte?.mp,kw.52Advanced
138pmn leukocyte?.mp,kw.400Advanced
139(poly morphou* adj2 granulocyte?).mp,kw.0Advanced
140(polynuclear adj3 leukocyte?).mp,kw.71Advanced
141or/133-140139,999Advanced
142(neutrophil? adj6 lymphocyte?).mp,kw.8790Advanced
143NLR.mp,kw.1729Advanced
144132 and 14126,722Advanced
145or/142-14427,810Advanced
146exp Cohort Studies/1,522,637Advanced
147exp Prognosis/1,240,142Advanced
148exp Morbidity/425,952Advanced
149exp Mortality/309,548Advanced
150exp survival analysis/214,369Advanced
151exp models, statistical/311,009Advanced
152prognos*.mp,kw.603,945Advanced
153predict*.mp,kw.1,026,266Advanced
154course*.mp,kw.467,535Advanced
155diagnosed.mp,kw.361,373Advanced
156cohort*.mp,kw.388,862Advanced
157death?.mp,kw.646,834Advanced
158or/146-1574,572,550Advanced
159108 and 145 and 15864Advanced
16043 and 145 and 158122Advanced
161159 or 160184Advanced
162limit 161 to yr = “2013-Current”85Advanced

aOvid MEDLINE®, 1946–April week 2 2016

Table 4

Detailed characteristics of included studies

AuthorYearNumber of patientsDisease stageNLR cutoff valueMedian age (years)Breast cancer subtype (%)Grade (%)Postmenopausal (%)Median follow-up (years)
ER+HER-2+Triple negativeGrade 1–2Grade 3
Asano et al. [12]201661Early3.0n/a001007228363.1
Azab et al. [23]2012316Mixed3.3n/a8317n/a7030n/a3.8
Azab et al. [13]2013437Mixed3.36476n/an/an/an/an/a5
Bozkurt et al. [24]201585Early2.0n/a00100316969n/a
Dirican et al. [25]20151527Mixed4.0n/a6817n/a8020442.5
Forget et al. [10]2014720Early3.3n/a849n/a6139n/a5.8
Hong et al. [29]2015487Early1.9556721197327424.6
Jia et al. [14]20151570Early2.047n/a22146238n/a6.6
Koh et al. [8]2014157Early2.344n/a008020n/a1.8
Koh et al. [15]20151435Mixed5.05255361005644n/an/a
Nakano et al. [9]2015167Early2.5587818n/a8020257.2a
Noh et al. [26]2013442Early2.5507129187129n/a5.9
Pistelli et al. [27]201590Early3.053001001090404.5
Rimando et al. [28]2016461Mixed3.85874n/an/a5149n/a5.1
Yao et al. [11]2014608Early2.653662516n/an/a483.5

ER estrogen receptor, n/a not available, NLR neutrophil-to-lymphocyte

aMean follow-up

  26 in total

1.  Usefulness of the neutrophil-to-lymphocyte ratio in predicting short- and long-term mortality in breast cancer patients.

Authors:  Basem Azab; Vijaya R Bhatt; Jaya Phookan; Srujitha Murukutla; Nina Kohn; Terenig Terjanian; Warren D Widmann
Journal:  Ann Surg Oncol       Date:  2011-06-03       Impact factor: 5.344

2.  Immunosuppression by activated human neutrophils. Dependence on the myeloperoxidase system.

Authors:  A el-Hag; R A Clark
Journal:  J Immunol       Date:  1987-10-01       Impact factor: 5.422

3.  Prognostic significance of the ratio of absolute neutrophil to lymphocyte counts for breast cancer patients with ER/PR-positivity and HER2-negativity in neoadjuvant setting.

Authors:  Young Wha Koh; Hee Jin Lee; Jin-Hee Ahn; Jong Won Lee; Gyungyub Gong
Journal:  Tumour Biol       Date:  2014-07-02

4.  Predicting the role of the pretreatment neutrophil to lymphocyte ratio in the survival of early triple-negative breast cancer patients.

Authors:  Oktay Bozkurt; Halit Karaca; Veli Berk; Mevlude Inanc; Ayse Ocak Duran; Ersin Ozaslan; Mahmut Ucar; Metin Ozkan
Journal:  J BUON       Date:  2015 Nov-Dec       Impact factor: 2.533

5.  Intraoperative use of ketorolac or diclofenac is associated with improved disease-free survival and overall survival in conservative breast cancer surgery.

Authors:  P Forget; C Bentin; J P Machiels; M Berliere; P G Coulie; M De Kock
Journal:  Br J Anaesth       Date:  2014-01-23       Impact factor: 9.166

6.  Elevated preoperative neutrophil-to-lymphocyte ratio predicts poor disease-free survival in Chinese women with breast cancer.

Authors:  Jin Hong; Yan Mao; Xiaosong Chen; Li Zhu; Jianrong He; Weiguo Chen; Yafen Li; Lin Lin; Xiaochun Fei; Kunwei Shen
Journal:  Tumour Biol       Date:  2015-10-21

7.  The potential role of neutrophils in promoting the metastatic phenotype of tumors releasing interleukin-8.

Authors:  Joseph E De Larco; Beverly R K Wuertz; Leo T Furcht
Journal:  Clin Cancer Res       Date:  2004-08-01       Impact factor: 12.531

Review 8.  Hallmarks of cancer: the next generation.

Authors:  Douglas Hanahan; Robert A Weinberg
Journal:  Cell       Date:  2011-03-04       Impact factor: 41.582

9.  Utility of pre-treatment neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as prognostic factors in breast cancer.

Authors:  C-H Koh; N Bhoo-Pathy; K-L Ng; R S Jabir; G-H Tan; M-H See; S Jamaris; N A Taib
Journal:  Br J Cancer       Date:  2015-05-28       Impact factor: 7.640

10.  Usefulness of pretreatment neutrophil to lymphocyte ratio in predicting disease-specific survival in breast cancer patients.

Authors:  Hany Noh; Minseob Eomm; Airi Han
Journal:  J Breast Cancer       Date:  2013-03-31       Impact factor: 3.588

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  168 in total

Review 1.  The Multifaceted Nature of Tumor Microenvironment in Breast Carcinomas.

Authors:  Laura Annaratone; Eliano Cascardi; Elena Vissio; Ivana Sarotto; Ewa Chmielik; Anna Sapino; Enrico Berrino; Caterina Marchiò
Journal:  Pathobiology       Date:  2020-04-23       Impact factor: 4.342

2.  Relationship Between FDG Uptake and the Platelet/lymphocyte Ratio in Patients With Breast Invasive Ductal Cancer.

Authors:  Takaaki Fujii; Shoko Tokuda; Yuko Nakazawa; Sasagu Kurozumi; Sayaka Obayashi; Reina Yajima; Ken Shirabe
Journal:  In Vivo       Date:  2020 May-Jun       Impact factor: 2.155

3.  Pretreatment neutrophil/lymphocyte, platelet/lymphocyte, lymphocyte/monocyte, and neutrophil/monocyte ratios and outcome in elderly breast cancer patients.

Authors:  B Losada; J A Guerra; D Malón; C Jara; L Rodriguez; S Del Barco
Journal:  Clin Transl Oncol       Date:  2018-11-30       Impact factor: 3.405

4.  Association of neutrophil-to-lymphocyte ratio and risk of cardiovascular or all-cause mortality in chronic kidney disease: a meta-analysis.

Authors:  Guangyu Ao; Yushu Wang; Xin Qi; Fengping Wang; Huitao Wen
Journal:  Clin Exp Nephrol       Date:  2020-10-06       Impact factor: 2.801

5.  Tumor Mutation Burden and Depression in Lung Cancer: Association With Inflammation.

Authors:  Daniel C McFarland; Devika R Jutagir; Andrew H Miller; William Breitbart; Christian Nelson; Barry Rosenfeld
Journal:  J Natl Compr Canc Netw       Date:  2020-04       Impact factor: 11.908

6.  Predictive Factors of Eribulin Activity in Metastatic Breast Cancer Patients.

Authors:  Rita De Sanctis; Elisa Agostinetto; Giovanna Masci; Emanuela Ferraro; Agnese Losurdo; Alessandro Viganò; Lidija Antunovic; Monica Zuradelli; Rosalba Maria Concetta Torrisi; Armando Santoro
Journal:  Oncology       Date:  2018-07-23       Impact factor: 2.935

7.  Low neutrophil-lymphocyte ratio correlates with extended survival in patients with metastatic breast cancer who achieved clinically complete response following multidisciplinary therapy: A retrospective study.

Authors:  Haruko Takuwa; Wakako Tsuji; Yoshihiro Yamamoto; Masayuki Shintaku; Fumiaki Yotsumoto
Journal:  Oncol Lett       Date:  2018-03-01       Impact factor: 2.967

8.  The neutrophil-to-lymphocyte ratio as a novel independent prognostic factor for multiple metastatic lung tumors from various sarcomas.

Authors:  Hiromasa Yamamoto; Kei Namba; Haruchika Yamamoto; Tomohiro Toji; Junichi Soh; Kazuhiko Shien; Ken Suzawa; Takeshi Kurosaki; Shinji Otani; Mikio Okazaki; Seiichiro Sugimoto; Masaomi Yamane; Katsuhito Takahashi; Toshiyuki Kunisada; Takahiro Oto; Shinichi Toyooka
Journal:  Surg Today       Date:  2020-08-03       Impact factor: 2.549

9.  Prognostic role for the derived neutrophil-to-lymphocyte ratio in early breast cancer: a GEICAM/9906 substudy.

Authors:  A J Templeton; Á Rodríguez-Lescure; A Ruíz; E Alba; L Calvo; M Ruíz-Borrego; A Santaballa; C A Rodríguez; C Crespo; M Ramos; J M Gracia-Marco; A Lluch; I Álvarez; M I Casas; M Sánchez-Aragó; R Caballero; E Carrasco; E Amir; M Martin; A Ocaña
Journal:  Clin Transl Oncol       Date:  2018-05-15       Impact factor: 3.405

10.  Oral Capecitabine-Vinorelbine is Associated with Longer Overall Survival When Compared to Single-Agent Capecitabine in Patients with Hormone Receptor-Positive Advanced Breast Cancer.

Authors:  Claudio Vernieri; Michele Prisciandaro; Federico Nichetti; Riccardo Lobefaro; Giorgia Peverelli; Francesca Ligorio; Emma Zattarin; Maria Silvia Cona; Pierangela Sepe; Francesca Corti; Sara Manglaviti; Marta Brambilla; Barbara Re; Antonino Belfiore; Giancarlo Pruneri; Luigi Celio; Gabriella Mariani; Giulia Valeria Bianchi; Licia Rivoltini; Giuseppe Capri; Filippo de Braud
Journal:  Cancers (Basel)       Date:  2020-03-06       Impact factor: 6.639

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