Changes in the neutrophil to lymphocyte ratio as predictors of outcome in pediatric patients with central nervous system tumors undergoing surgical resection

Abstract

BACKGROUND:

Changes in neutrophil to lymphocyte ratio ( $\Delta$ NLR) have been used as a clinical tool for stratification and prognosis of patients with solid tumors, there is scarce evidence of their clinical relevance in patients with tumors of the central nervous system who have also undergone surgical resection.

OBJECTIVE:

Determine if ( $\Delta$ NLR) are associated with poor response to treatment and worse prognosis in pediatric patients with central nervous system tumors (CNST) who underwent surgical resection.

METHODS:

We performed a retrospective cohort study; demographic, clinical, and hematological variables were evaluated, Kaplan-Meier survival curves and Cox proportional hazards regression model were performed to evaluate prognosis.

RESULTS:

The $\Delta$ NLR cutoff value obtained through the third interquartile range was 4.30; The probability of survival and complete response to treatment was different between patients with high $\Delta$ NLR when compared to patients with low $\Delta$ NLR ( $p=$ 0.013, $p=<<$ 0.001, respectively). A high $\Delta$ NLR behaved as an independent predictor of worse Overall Survival (HR 2,297; 95% CI: 1,075–4.908, $p=$ 0.032).

CONCLUSION:

An elevated $\Delta$ NLR was a predictor of poor response to treatment and a prognostic factor for worse Overall Survival in pediatric patients with CNST undergoing surgical resection.

Keywords

Central nervous system tumors pediatric neutrophil-to-lymphocyte ratio prognostic factor survival tumor resection

1. Introduction

Cancer was the leading cause of death worldwide in children in 2018; the World Health Organization globally estimated 272,603 new cases of cancer diagnosed in children aged 0–19 years [1, 2]. In Mexico, the incidence of childhood cancer was 15.2/100,000 children and 1.8/100,000 in central nervous system tumors (CNST), which besides being the most frequent solid tumors in pediatrics, also rank first in cancer-associated mortality in children under the age of 15. In countries such as the United States, the mortality rate within this group of tumors has decreased, with a 5-year survival rate of 72.3% [3, 4], however, differences in childhood cancer survival rates among low and middle-income countries such as Mexico are known, where it ranges between 5 and 60% [2, 5].

In recent years, the link between cancer and the patients’ inflammatory condition has been studied, and certain patterns have been observed in systemic inflammation as well as in the tumor microenvironment. Inflammatory response plays an essential and very complex role in the initiation, promotion, malignant transformation, progression, invasion, and metastasis of cancer [6, 7, 8]. In this regard, different hematological markers that reflect the systemic inflammatory state and its relationship with various medical conditions have been studied; these include the C-reactive protein/albumin ratio, the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio and monocyte/lymphocyte ratio [6, 9, 10, 11, 12, 13]. These markers have already been studied in different types of cancer in multiple populations [14, 15, 16, 17, 18, 19, 20] and some of them have already been validated as part of the patient’s clinical management and prognosis in some kinds of malignancies such as kidney, lung and colorectal cancer [9, 21]. They have also been studied in some CNST such as glioma and craniopharyngioma [22, 23]. Besides the complex correlation between cancer and multiple inflammatory mechanisms, the inflammatory response to surgical trauma and the interactions it triggers at metabolic, endocrine, immunological, and hematological levels have also been reviewed [24, 25]; Cuthbertson first described the alterations occurring in response to trauma and divided them into the Ebb and Flow phases [26], since then, the study of the factors involved in each of these phases has deepened in greater detail. Differences have also been found in the response mechanisms that occur among adults and the pediatric population, in which the participation of IL-1 $\beta$ , IL-1ra, IL-6, IL-10 and TNF- $\alpha$ has been mainly described, along with a lower metabolic response to trauma [27]. It has become evident in recent years that in addition to inflammatory factors inherent to cancer or different types of tumors, the pre and postoperative inflammatory mechanisms also influence the oncological patients’ outcome [28, 29, 30, 31]. Few studies analyze the postoperative NLR and the prognosis of patients with solid tumors who underwent surgical resection [31, 32, 33, 34] hence, the study of this association will complement the knowledge in the field of hematological biomarkers in the pediatric population. Therefore, the objective of this study was to determine if changes in the NLR are associated with a poor response to treatment and a worse prognosis in pediatric patients with CNST who underwent surgical resection.

2. Material and methods

2.1 Study subjects characteristics

We performed a retrospective cohort study, demographic, clinical, and hematological variables were obtained and evaluated from the medical record department and the institutional electronic database. All patients derived from the Oncology department at the National Institute of Pediatrics and underwent surgical resection as part of the initial oncological management. The inclusion criteria were: patients aged from 1 month to 17 years at the time of diagnosis with a high or low-grade CNST confirmed by biopsy, who had hematological analysis both before any medical or surgical intervention and after the surgical procedure. Patients with previous neoplasia or resection, autoimmune or hematological disease, active infection, no hematological parameters before steroid treatment, or any medication that affected inflammatory conditions and antineoplastic treatment (including radiotherapy or chemotherapy) before surgery, were excluded. All patients included were part of a study that was approved by the institutional committees, under the registration INP 061/2018 and the experiments were undertaken with the understanding and written consent of each subject, and that the study conforms with The Code of Ethics of the World Medical Association (Declaration of Helsinki), printed in the British Medical Journal (July 18th, 1964).

2.2 Data collection

Data was collected between 2017–2019 from the medical records and the institutional electronic database; hematological parameters were obtained pre and post-surgical; the pre-surgery values were collected prior to any medical intervention and the post-surgery values during the recovery period and before any oncological adjuvant therapy including chemotherapy or radiotherapy. NLR was defined as the absolute neutrophil count (/mm3) divided by the absolute lymphocyte count (/mm3). Additionally, we obtained the difference between the NLRs, the post-surgery NLR was the minuend, and the pre-surgery NLR the subtrahend, the difference between them was defined as delta NLR ( $\Delta$ NLR).

2.3 Response to treatment

In order to evaluate response to treatment, we used the Response Assessment in Neuro-Oncology Criteria (RANO) [35], which considers complete response (CR) as the complete disappearance of all measurable and not measurable lesions sustained for at least four weeks without new injuries; partial response (PR) as the decrease $\geqslant$ 50% in the sum of perpendicular diameters of all measurable lesions compared with baseline for at least four weeks; progression disease (PD) as an increase $\geqslant$ 25% in the sum of perpendicular diameters of injuries compared with the smallest tumor measurement, either at baseline or best response on stable; stable disease (SD): does not qualify for CR, PR or PD. In the present study, only patients with CR were considered as responders, while PR, SD, and PD were considered as non-responders.

2.4 Follow-up and survival

Follow-up was defined as the period between the patient’s first contact with the Institute up to the latest monitoring evidence or death.

Overall Survival (OS) was defined as the probability to surviving from the diagnosis of death or until the loss of patient monitoring.

2.5 Statistical analysis

Kaplan-Meier curves were used to represent the response to treatment and survival estimates and were compared with the log-rank test to determine the difference in survival probabilities for patients with different $\Delta$ NLR cutoff values. $P$ values $<$ 0.05 were considered as statistically significant. Univariate and multivariate analyses were performed using the Cox proportional hazards model to identify those variables that were significant for independently predicting the duration of survival. The results were considered statistically significant if the 95% confidence intervals (95% CI) excluded the null value. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) 22.0 version (IBM Corp., Armonk, New York, USA) [36].

3. Results

3.1 Cohort overview

From all the patients diagnosed with CNST during the study period, 106 met the selection criteria at the beginning; however, 13 had no hematological data to obtain the NLR differential, and seven patients were under chemotherapy treatment, and therefore it was not possible to assess response to treatment.

The final cohort consisted of 86 patients; the median age was seven years (8 months to 17 years range). According to gender, $N=$ 40 (46.5%) were female and $N=$ 46 (53.5%) male. The most frequent diagnosis was medulloblastoma $N=$ 27 (31.4%), followed by astrocytoma $N=$ 25 (29.1%). Regarding the risk degree based on the histopathological diagnosis, $N=$ 58 (67.4%) presented a high-risk tumor, and $N=$ 28 (32.6%) a low-risk tumor. Table 1 presents the distribution of patients included in this study according to their histopathological diagnosis.

Table 1
Frequency of central nervous system tumors in the study cohort

Tumor	Frequency	Percentage
Medulloblastoma	27	31.4
Astrocytoma	25	29.1
Ependymoma	17	19.8
Glioblastoma	4	4.7
Brainstem glioma	3	3.5
Primitive neuroectodermal tumor	3	3.5
Pineoblastoma	2	2.3
Germinoma	1	1.2
Atypical teratoid rhabdoid tumor	1	1.2
Choroid plexus carcinoma	1	1.2
Neuroglial tumor	1	1.2
Meningioma	1	1.2

3.2 Determining the cutoff value for

\Delta

NLR

The cutoff value was determined from the $\Delta$ NLR interquartile ranges and corresponded to those patients who had a $\Delta$ NLR above the third interquartile range (Q3), which value was 4.30. $\Delta$ NLR was analyzed as a continuous variable, and patients were dichotomized according to the Q3 value. $N=$ 21 of 86 patients had a $\Delta$ NLR $\geqslant$ 4.30.

3.3 Association between $\Delta$ NLR and response to treatment

By evaluating response to treatment using RANO criteria, $N=$ 26 (30.2%) of the patients presented CR, $N=$ 8 (9.3%) PR, $N=$ 16 (18.6%) SD and $N=$ 36 (41.9%) PD.

During the follow-up period, patients with a high $\Delta$ NLR ( $\geqslant$ 4.30) had a mean response time of 43.65 months (95% CI 34.16–53.14) compared to patients who had a low $\Delta$ NLR ( $<$ 4.30), whose mean response time was 112.20 months (95% CI 93.50–130.94). The probability of complete response to treatment was different in patients with a high $\Delta$ NLR when compared to those with a low $\Delta$ NLR, $p=<<$ 0.001 (Fig. 1).

Figure 1.

Comparison of $\Delta$ NLR response to treatment probability curves in pediatric patients with central nervous system tumors.

3.4 Association between

\Delta

NLR and survival

From all patients, $N=$ 29 (33.7%) were deceased, $N=$ 11 (12.8%) were with support for life quality, and $N=$ 46 (53.5%) remained alive during the follow-up period. During this follow-up period, patients with a high $\Delta$ NLR had a mean survival of 33.40 months (95% CI 23.96–42.97) compared to patients who had a low $\Delta$ NLR, whose mean survival was 102.18 months. (95% CI 82.42–121.95). The probability of survival was different in those patients with high $\Delta$ NLR when compared to those with low $\Delta$ NLR, $p=$ 0.013 (Fig. 2).

Figure 2.

Comparison of $\Delta$ NLR survival probability curves in pediatric patients with central nervous system tumors.

3.5 Univariate and multivariate analysis for overall survival (OS)

A high $\Delta$ NLR remained as a risk factor for mortality in both univariate (HR 2.359 95% CI 0.991–4.673, $p=$ 0.018) and multivariate analyses (HR 2.297 95% CI 1.075–4.908, $p=$ 0.032). Age ( $>$ 5 years) was found to be a risk factor for mortality in univariate analysis (HR 2.134 95% CI 1.060–4.295, $p=$ 0.034); however, this was not reproduced in the multivariate analysis. Neither gender nor histopathological risk degree were shown to be risk factors for mortality in our cohort in neither analysis. As an additional feature, ifosfamide, carboplatin and etoposide scheme were shown to be risk factors for mortality in both univariate and multivariate analyses (HR 3.83 95% CI 1,868–7,888, $p=$ 0.000 and HR 4.090 95% CI 1,737–9,628, $p=$ 0.001 respectively). The univariate and multivariate analyses are presented in Table 2.

Table 2
Univariate and Multivariate analysis for overall survival using the Cox proportional hazards model

	Univariate analysis			Multivariate analysis
	HR	95% CI	$P$ value	HR	95% CI	$P$ value
Age $>$ 5 years	2.134	1.060–4.295	0.034	1.573	0.764–3.239	0.219
Gender	1.184	0.636–2.206	0.594	1.195	0.631–2.263	0.585
Tumor grade risk	2.152	0.991–4.673	0.053	0.920	0.369–2.295	0.858
$\Delta$ NLR $\geqslant$ 4.30	2.359	1.161–4.795	0.018	2.297	1.075–4.908	0.032
ICE scheme	3.839	1.868–7.888	0.000	4.090	1.737–9.628	0.001

HR: Hazard ratio. CI: Confidence interval. $\Delta$ NLR: delta neutrophil-to-lymphocyte ratio. ICE: Ifosfamide, carboplatin, etoposide.

4. Discussion

In the present study, we found that patients who had a high $\Delta$ NLR value had a decreased probability of response to treatment and OS compared to those patients who had a low $\Delta$ NLR during the follow-up period. In our univariate analysis, a high $\Delta$ NLR, age over 5 years, and patients with ICE (Ifosfamide, Carboplatin, Etoposide) scheme were found to be risk factors for mortality; in the multivariate analysis, a high $\Delta$ NLR and patients with ICE scheme were found to be associated with reduced OS.

Pierscianek et al. [22] conducted a systematic review of the markers that have proven to be predictively useful in adult patients with glioma. Among these, they included the NLR, which was placed in the top 10 of the most promising biomarkers with a II level of evidence. One of the main objectives that have been set while studying these markers is their identification and subsequent incorporation into staging and prognosis scales since this is a parameter that is routinely available at a very low cost and requires no more than a blood biometry.

Most studies assessing hematological indexes, including the NLR, have focused on the preoperative values. Nevertheless, Li et al. [37] evaluated the preoperative and the postoperative NLR values of patients with cellular hepatocarcinoma undergoing resection and found similar values in the preoperative NLR, in both the recurrence and the non-recurrence groups; this was not found in the postoperative NLR, which values differed between the recurrence and non-recurrence groups, $p=$ 0.019. Shibutani et al. [38] evaluated the postoperative inflammatory markers of 254 patients with stage II/III colorectal cancer undergoing surgical resection and found that the OS was significantly worse in the group of patients with an elevated postoperative NLR (NLR $>$ 3), $p=$ 0.0006. (HR 3.597 95% CI 1.643–7.875, $p=$ 0.001 in their multivariate analysis).

Although some studies have associated NLR with clinical stage, OS, and prognosis in different types of cancer, there is limited information regarding NLR behavior in CNST, within this particular group of tumors, studies have focused mainly on gliomas in adults. Another notable feature is that the vast majority of studies that have been published to date have been directed to the Caucasian and Asian populations [11, 39], which means there is little data regarding these parameters in our population and the cutoff values for pediatric patients. Azab et al. [40] evaluated different NLR cutoff values in healthy patients and found differences by population so that the black non-Hispanic and Hispanic groups had significantly lower average NLR values (NLR 1.76, 95% CI 1.71–1.81 and NLR 2.08, 95% CI 2.04–2.12 respectively) when compared to the white non-Hispanic group (NLR 2.24, 95% CI 2.19–2.28), $p=$ 0.0001.

Several authors, even studying the same kind of tumor, have differed in the NLR cutoff value, as it is the case of Zhou et al. [41], Yersal et al. [42], Wang et al. [43] and Han et al. [44] who assigned a cutoff value of 4, while Lopes et al. 2018 [45] and Kaya et al. [46] assigned a value of 5, all of them examining the NLR association with glioblastoma multiforme.

For a single tumor type, different NLR values have been determined; such values reveal a directly proportional correlation with the tumor histopathological risk degree. Bao et al. [47], based on a 2.5 cutoff value in a 219-patient cohort with glioma, found that NLR has an association with both tumor grade and OS in univariate and multivariate analyses ( $p=$ 0.000). Ghandi et al. [48] in a case-control study of glioma patients, found that the NLR value is directly proportional to tumor grade and inversely proportional to OS by using an NLR cutoff value of 2.7 ( $p=$ $<$ 0.0001). Zheng et al. [49] studied 750 patients with glioma, 44 with acoustic neuroma and 271 with meningioma; they found a directly proportional relationship between different values of NLR and tumor grade at 1.56, 1.79, 2.19 and 3.61 for I, II, III and IV grades, respectively; they obtained statistical significance by comparing glioma versus non-glioma (AUC 0.722, 95% CI 0.697–0.747) and glioblastoma (IV grade glioma) versus other grades of glioma (AUC 0.811, 95% CI 0.778–0.844).

Research on NLR in children with CNST is limited; however, Yalon et al. [50] reported a significantly higher NLR in pediatric patients with brain tumors (NLR 4.59) compared to the healthy controls group (NLR 2.96), $p=$ 0.025. Moreover, Wilson et al. [51] observed patterns in preoperative NLR of 116 pediatric patients with different CNST undergoing resection, being lower in tumor grades 1 and 2 (NLR 2.29 $\pm$ 0.59) when compared to grades 3 and 4 (NLR 3.20 $\pm$ 0.76), $p=$ 0.069. None of these studies evaluated survival or response to treatment.

Similarly, very few studies have evaluated changes in the behavior of NLR, for instance, Guo et al. [52] observed a substantial increase in NLR on patients with inoperable non-small-cell lung cancer when comparing pre and post-chemotherapy moments. $\Delta$ NLR was also found to be an independent prognostic factor for OS in their multivariate analysis ( $p=$ 0.012), as well as for progression-free survival ( $p=$ 0.036) with a cutoff value of $-$ 2.24. Başer et al. [53] studied a patient cohort with post-cardiac arrest syndrome treated with targeted hypothermia, with a $\Delta$ NLR cutoff value of 13.5, they found an association between $\Delta$ NLR and OS in multivariate analysis (OR 0.96, 95% CI 0.94–0.99, $p=$ 0.008).

Our results differ from those described by Li et al. [54] as their results showed that a $\Delta$ NLR $>$ 0 was associated with a survival of 98.4%, 96.9%, and 95.3% compared to those patients who had a $\Delta$ NLR $<$ 0 with a survival of 98.2%, 90.7% and 83.6% at postoperative year 1, 3 and 5, respectively, ( $p=$ 0.002) in a cohort of 354 patients with colorectal cancer stage I to III. Nevertheless, Peng et al. [55] evaluated $\Delta$ NLR using the same cutoff value by taking the pre and postoperative times in 189 patients with hepatocellular carcinoma; those patients who had a $\Delta$ NLR $>$ 0 had an OS of 92.7%, 70.0%, and 53.0%, which was lower compared to the group of patients who had a $\Delta$ NLR $<$ 0 whose OS was 96.2%, 87.5%, and 75.9% at year 1, 3, and 5, respectively, ( $p=$ 0.003); As in the present study, their multivariate analysis revealed $\Delta$ NLR as an independent prognostic factor for survival (HR 2.637 95% CI 1.356–5.128, $p=$ 0.004) and in its case, for recurrence-free survival (HR 2.372 95% CI 1.563–3.601, $p=$ $<$ 0.001).

Although mortality association according to the chemotherapy scheme has been understudied, Viñal et al. [56] studied a cohort of 79 patients with soft-tissue sarcoma treated with high doses of ifosfamide/epirubicin, 95% of whom underwent surgical treatment, finding that patients with a lower than average NLR (NLR $<$ 2.83) had a longer period of the progression-free disease (HR 0.42 95% CI 0.22–0.81), metastasis-free survival, (HR 0.67 95% CI 0.48–0.94) and OS (HR 0.39 95% CI 0.17–0.87) than those above that value. Pan et al. [57] in a 73-patient group with small-cell lung cancer found that those patients with an NLR $\geqslant$ 3.80 had an increased disease-free survival ( $p=$ 0.021) and OS ( $p=$ 0.042) when treated with etoposide/cisplatin compared to those treated with etoposide/carboplatin. Park et al. [58] studied a group of 66 patients with locally advanced small-cell lung cancer who were treated with concomitant chemo-radiotherapy based on paclitaxel/carboplatin or docetaxel/cisplatin; when comparing post-chemoradiotherapy NLR, the group with a NLR $>$ 3.12 had worse 2-year OS (25.8% vs 68.2%, $p<$ 0.001), 2-year locoregional progression-free survival (12.9% vs. 33.8%, $p=$ 0.010), and 2-year metastasis-free survival (22.6% vs. 38.2%, $p=$ 0.030) when compared with the low NLR group.

The mechanisms that are involved in linking a high NLR value with a poor prognosis or response are not entirely clear, in addition to the disorders that we may find at a cellular and immunological level within the tumor microenvironment and the typical systemic response of the oncological processes, we must also consider the metabolic, inflammatory and immunological alterations in response to surgical trauma [6, 9, 24, 27, 28, 59]. The neutrophilia and lymphopenia state, in addition to altering the anti-tumor immune response and contributing to tumor progression, it joins the effects of the metabolic response to trauma, which magnitude and perpetuation along with all of the above factors, have been associated with prognosis in response and survival of patients in different oncological conditions [31, 32, 33, 34, 60]. It is essential, as described by Park et al. [61] to look for markers that will allow us to monitor the balance between the pro/anti-inflammatory, pro/anti-tumor and innate/acquired immunity responses since the staging of patients is based on the histopathological or invasive characteristics of the biopsied tumor and the individual inflammatory response in each patient is not considered; therefore, the inflammatory processes that are taking place in response to surgical trauma could be interpreted through these changes occurring in the NLR, which we could potentially use for staging every single patient considering their individual response and not only the tumor’s features.

5. Conclusions

An elevated $\Delta$ NLR was predictive of poor response to treatment and was a prognostic factor for worse overall survival in pediatric patients CNST. The behavior of $\Delta$ NLR could be used in a future as an easy-access tool that might be incorporated into clinical practice with a significant impact on the study of response to treatment and survival in pediatric patients with CNST undergoing surgical resection. Therefore, it is proposed as an inexpensive, reproducible, and widely accessible instrument.

Author contributions

Conception: LT, MC, and CS.

Interpretation and analysis of data: AF, PS and MC.

Preparation of the manuscript: AF, LT and MC.

Revision for important intellectual content: AU, DM, AA, AF and LH.

Supervision: LT, MC, AA, MZ and CS.

Ethics statement

The protocol for this study was approved by the institutional committees, under reference number INP 061/2018 and the experiments were undertaken with the understanding and written consent of each subject, and that the study conforms with The Code of Ethics of the World Medical Association (Declaration of Helsinki), printed in the British Medical Journal (July 18th, 1964).

Footnotes

Acknowledgments

The group of authors would like to thank Citlaltepetl Salinas Lara PhD and the Program of Medicine for Education, Development, and Scientific Research of Iztacala (MEDICI) for supporting the collaboration between the medical interns and researchers, and we would like to thank the PhD Juan Luis Chavez for their support in reviewing the English style. The present study was funded by Program E022 of the National Institute of Pediatrics.

Conflict of interest

The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

World Health Organization, Global initiative for Childhood Cancer, (2018). https://www.who.int/cancer/childhood-cancer/en/ [Accessed December 22, 2019].

World Health Organization, Global Cancer Observatory, Estimated Cancer Incidence, Mortality and Prevalence Worldwide in 2018, (2018). http://gco.iarc.fr/ [Accessed December 22, 2019].

Siegel

R.L.

Miller

K.D.

and Jemal

, Cancer Statistics, CA Cancer J Clin 70 (2020), 7–30.

Johnson

K.J.

et al., Childhood brain tumor epidemiology: a brain tumor epidemiology consortium review, Cancer Epidemiol Biomarkers Prev 23 (2014), 2716–36.

Rivera

et al., The burden of childhood cancer in Mexico: Implications for low- and middle-income countries, Pediatr Blood Cancer 64 (2016), 1–7.

Song

X.D.

et al., Advances in research on the interaction between inflammation and cancer, J Int Med Res (2019), 1–12.

et al., Interstitial flow promotes macrophage polarization toward an M2 phenotype, Mol Biol Cell 29 (2018), 1927–1940.

Oudin

M.J.

and Weaver

V.M.

, Physical and chemical gradients in the tumor microenvironment regulate tumor cell invasion, migration, and metastasis. Cold Spring, Harb Symp Quant Biol 81 (2016), 189–205.

Dolan

R.D.

et al., The role of the systemic inflammatory response in predicting outcomes in patients with operable cancer: Systematic review and meta-analysis, Crit Rev Oncol Hematol 116 (2017), 134–146.

10.

Erre

G.L.

et al., Meta-analysis of neutrophil-to-lymphocyte and platelet-to lymphocyte ratio in rheumatoid arthritis, Eu J Clin Invest 1 (2018), e13037: 1–11.

11.

Paliogiannis

et al., Associations between the neutrophil-to-lymphocyte and the platelet-to-lymphocyte ratios and the presence and severity of psoriasis: a systematic review and meta-analysis, Clin Exp Med 19 (2019), 37–45.

12.

Angkananard

et al., Neutrophil lymphocyte ratio and cardiovascular disease risk: A systematic review and meta-analysis, Biomed Res Int 2703518 (2018), 1–11.

13.

Liu

et al., Neutrophil-lymphocyte ratio predicts the outcome of intracerebral hemorrhage: A meta-analysis, Medicine (Baltimore) 98 (2019), e16211.

14.

Templeton

A.J.

et al., Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis, J Natl Cancer Inst 106 (2014), 1–11.

15.

Cho

J.K.

et al., Optimal cutoff of pretreatment neutrophil-to-lymphocyte ratio in head and neck cancer patients: a meta-analysis and validation study, BMC Cancer 18 (2018), 969.

16.

Zeng

et al., Prognostic value of neutrophil to lymphocyte ratio and clinicopathological characteristics for multiple myeloma. A meta-analysis, Medicine (Baltimore) 97 (2018), e12678: 1–9.

17.

Guo

et al., Prognostic role of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in prostate cancer: a meta-analysis of results from multivariate analysis, Int J Surg 60 (2018), 216–223.

18.

Duan

Pan

and Yang

, Preoperative elevated neutrophil-to-lymphocyte ratio (NLR) and derived NLR are associated with poor prognosis in patients with breast cancer: A meta-analysis, Medicine (Baltimore) 97 (2018), e13340, 1–10.

19.

Zhang

et al., Prognostic role of neutrophil-lymphocyte ratio in esophageal cancer: A systematic review and meta-analysis, Medicine (Baltimore) 97 (2018), e13585, 1–10.

20.

Zhao

and Zheng

, Prognostic significance of elevated preoperative neutrophil-to-lymphocyte ratio for patients with colorectal cancer undergoing curative surgery: A meta-analysis, Medicine (Baltimore) 98 (2019), e14126, 1–10.

21.

Kumar

et al., The neutrophil-lymphocyte ratio and its utilization for the management of cancer patients in early clinical trials, Br J Cancer 112 (2015), 1157–1165.

22.

Pierscianek

et al., Blood-Based Biomarkers in High Grade Gliomas: a Systematic Review, Mol Neurobiol 56 (2019), 6071–6079.

23.

Chen

et al., The diagnostic value of preoperative inflammatory markers in craniopharyngioma: a multicenter cohort study, J Neurooncol 138 (2018), 113–122.

24.

Şimşek

H.U.

and Cantürk

N.Z.

, Response to trauma and metabolic changes: posttraumatic metabolism, Ulus Cerrahi Derg 30 (2014), 153–159.

25.

Hastings

Krepska

and Roodenburg

, The metabolic and endocrine response to trauma, Anaesthesia and Intensive Care Medicine 15 (2014), 432–435.

26.

Cuthbertson

D.P.

, The disturbance of metabolism produced by bony and non-bony injury, with notes on certain abnormal conditions of bone, Biochemical J 24 (1930), 1244–1263.

27.

McHoney

Eaton

and Pierro

, Metabolic response to surgery in infants and children, Eur J Pediatr Surg 19 (2009), 275–285.

28.

Dolan

R.D.

et al., The role of the systemic inflammatory response in predicting outcomes in patients with operable cancer: Systematic review and meta-analysis, Sci Rep 7 (2017), 16717.

29.

McSorley

S.T.

et al., Postoperative systemic inflammatory response, complication severity, and survival following surgery for colorectal cancer, Ann Surg Oncol 23 (2016), 2832–2840.

30.

Matsuda

et al., Correlation between intense postoperative inflammatory response and survival of esophageal cancer patients who underwent transthoracic esophagectomy, Ann Surg Oncol 22 (2015), 4453–4460.

31.

Hoshimoto

et al., Validation and clinical usefulness of pre- and postoperative systemic inflammatory parameters as prognostic markers in patients with potentially resectable pancreatic cancer, Pancreatology 20 (2019), 239–246.

32.

Shibutani

et al., The prognostic significance of a postoperative systemic inflammatory response in patients with colorectal cancer, World J Surg Oncol 13 (2015), 1–8.

33.

et al., Postoperative neutrophil-to-lymphocyte ratio plus platelet-to-lymphocyte ratio predicts the outcomes of hepatocellular carcinoma, J Surg Res 198 (2015), 73–79.

34.

Jang

W.S.

et al., The prognostic significance of postoperative neutrophil-to-lymphocyte ratio after radical prostatectomy for localized prostate cancer, Oncotarget 8 (2017), 11778–11787.

35.

Chukwueke

U.N.

and Wen

P.Y.

, Use of the response assessment in neuro-oncology (RANO) criteria in clinical trials and clinical practice, CNS Oncology 8 (2019), CNS28.

36.

IBM Corp, Released in 2013. IBM SPSS Statistics for Windows, Version 220. Armonk, NY: IBM Corp.

37.

et al., Postoperative neutrophil-to-lymphocyte ratio plus platelet-to-lymphocyte ratio predicts the outcomes of hepatocellular carcinoma, J Surg Res 198 (2015), 73–79.

38.

Shibutani

et al., The prognostic significance of a postoperative systemic inflammatory response in patients with colorectal cancer, World J Surg Oncol 13 (2015), 194: 1–8.

39.

Wang

D.P.

et al., Prognostic significance of preoperative systemic cellular inflammatory markers in gliomas: A systematic review and meta-analysis, Clin Transl Sci 13 (2020), 179–188.

40.

Azab

Camacho

and Taioli

, Average values and racial differences of neutrophil lymphocyte ratio among a nationally representative sample of United States subjects, PloS One 9 (2014), 1–6.

41.

Zhou

X.W.

et al., Significance of the prognostic nutritional index in patients with glioblastoma: A retrospective study, Clin Neurol Neurosurg 151 (2016), 86–91.

42.

Yersal

Ö.

et al., Prognostic significance of pre-treatment neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with glioblastoma, Mol Clin Oncol 9 (2018), 453–458.

43.

Wang

P.F.

et al., Preoperative inflammation markers and IDH mutation status predict glioblastoma patient survival, Oncotarget 8 (2017), 50117–50123.

44.

Han

et al., Pre-treatment neutrophil-to-lymphocyte ratio is associated with neutrophil and T-cell infiltration and predicts clinical outcome in patients with glioblastoma, BMC cancer 15 (2015), 1–10.

45.

Lopes

et al., Influence of neutrophil-lymphocyte ratio in prognosis of glioblastoma multiforme, J Neurooncol 136 (2018), 173–180.

46.

Kaya

et al., Prognostic significance of indicators of systemic inflammatory responses in glioblastoma patients, Asian Pac J Cancer Prev 18 (2017), 3287–3291.

47.

et al., Preoperative hematologic inflammatory markers as prognostic factors in patients with glioma, World Neurosurg 119 (2018), e710–e716.

48.

Gandhi

et al., Underestimated prognostic indicators in diffuse glioma, Int J Mol Cell Med 7 (2018), 111–118.

49.

Zheng

et al., Diagnostic value of preoperative inflammatory markers in patients with glioma: a multicenter cohort study, J Neurosurg 129 (2018), 583–592.

50.

Yalon

et al., Elevated NLR may be a feature of pediatric brain cancer patients, Front Oncol 30 (2019), 1–5.

51.

Wilson

et al., Pre-operative neutrophil count and neutrophil-lymphocyte count ratio (NLCR) in predicting the histological grade of paediatric brain tumours: a preliminary study, Acta Neurochir 160 (2018), 793–800.

52.

Guo

et al., Prognostic value of delta inflammatory biomarker-based nomograms in patients with inoperable locally advanced NSCLC, Int Immunopharmacol 72 (2019), 395–401.

53.

Başer

et al., Changes in neutrophil-to-lymphocyte ratios in postcardiac arrest patients treated with targeted temperature management, Anatol J Cardiol 18 (2017), 215–222.

54.

et al., The dynamic change of neutrophil to lymphocyte ratio can predict clinical outcome in stage I-III colon cancer, Sci Rep 8 (2018), 1–8.

55.

Peng

et al., Neutrophil to lymphocyte ratio changes predict small hepatocellular carcinoma survival, Journal of Surgical Research 192 (2014), 402–408.

56.

Viñal

et al., Prognostic value of neutrophil-to-lymphocyte ratio and other inflammatory markers in patients with high-risk soft tissue sarcomas, Clin Transl Oncol 22 (2020), 1849–1856.

57.

Pan

et al., Cisplatin or carboplatin Neutrophil to lymphocyte ratio may serve as a useful factor in small cell lung cancer therapy selection, Oncol Lett 18 (2019), 1513–1520.

58.

Park

E.Y.

et al., Prognostic value of neutrophil-to-lymphocyte ratio in locally advanced non-small cell lung cancer treated with concurrent chemoradiotherapy, Radiat Oncol J 37 (2019), 166–175.

59.

Brandau

Dumitru

and Lang

, Protumor and antitumor functions of neutrophil granulocytes, Semin Immunopathol 35 (2013), 163–176.

60.

M.X.

et al., Prognostic role of neutrophil-to-lymphocyte ratio in colorectal cancer: a systematic review and meta-analysis, Int J Cancer 134 (2014), 2403–2413.

61.