The Association between Neutrophil-to-Lymphocyte Ratio and Glycemic Control in Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Abstract

Background:
Glycated hemoglobin (HbA1c) is a commonly used clinical marker to monitor the control of type 2 diabetes mellitus patients (T2DM). However, it is unable to identify the ongoing inflammatory changes in the body. These factors could be easily identified and monitored by the neutrophil-to-lymphocyte ratio (NLR). Therefore, this study is aimed at investigating the relationship between NLR and glycemic control in T2DM.

Method:
A comprehensive search of eligible studies was performed in various databases published until July 2021. A random effect model was used to estimate the standardized mean difference (SMD). A metaregression, subgroup, and sensitivity analysis were conducted to search for potential sources of heterogeneity.

Result:
A total of 13 studies were included in this study. Accordingly, the SMD of the NLR values between the poor and good glycemic control groups was 0.79 (95% CI, 0.46-1.12). Our study also showed that high NLR was significantly associated with poor glycemic control in T2DM patients (OR = 1.50, 95% CI: 1.30-1.93).

Conclusion:
The results of this study suggest an association between high NLR values and an elevated HbA1C in T2DM patients. Therefore, NLR should be considered a marker of glycemic control in addition to HbA1c in T2DM patients.

Full text

Review Article
The Association between Neutrophil-to-Lymphocyte Ratio and
Glycemic Control in Type 2 Diabetes Mellitus: A Systematic
Review and Meta-Analysis
Tiruneh Adane ,
1
Mulugeta Melku ,
1
Yilkal Belete Worku,
2
Alebachew Fasil ,
3
Melak Aynalem,
1
Amanuel Kelem,
4
and Solomon Getawa
1
1
Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and
Health Sciences, University of Gondar, Gondar, Ethiopia
2
Department of Internal Medicine, School of Medicine, College of Medicine and Health Sciences, University of Gondar,
Gondar, Ethiopia
3
Department of Clinical Chemistry, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences,
University of Gondar, Gondar, Ethiopia
4
Department of Medical Laboratory Sciences, Asrat Woldeyes Health Science Campus, Debre Berhan University,
Debre Berhan, Ethiopia
Correspondence should be addressed to Tiruneh Adane; tirunehadane01@gmail.com
Received 29 July 2022; Revised 18 April 2023; Accepted 26 May 2023; Published 3 June 2023
Academic Editor: Mark Yorek
Copyright © 2023 Tiruneh Adane et al. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
Background. Glycated hemoglobin (HbA1c) is a commonly used clinical marker to monitor the control of type 2 diabetes mellitus
patients (T2DM). However, it is unable to identify the ongoing inflammatory changes in the body. These factors could be easily
identified and monitored by the neutrophil-to-lymphocyte ratio (NLR). Therefore, this study is aimed at investigating the
relationship between NLR and glycemic control in T2DM. Method. A comprehensive search of eligible studies was performed
in various databases published until July 2021. A random effect model was used to estimate the standardized mean difference
(SMD). A metaregression, subgroup, and sensitivity analysis were conducted to search for potential sources of heterogeneity.
Result. A total of 13 studies were included in this study. Accordingly, the SMD of the NLR values between the poor and good
glycemic control groups was 0.79 (95% CI, 0.46-1.12). Our study also showed that high NLR was significantly associated with
poor glycemic control in T2DM patients (OR = 1:50, 95% CI: 1.30-1.93). Conclusion. The results of this study suggest an
association between high NLR values and an elevated HbA1C in T2DM patients. Therefore, NLR should be considered a
marker of glycemic control in addition to HbA1c in T2DM patients.
1. Introduction
Diabetes mellitus (DM) is a multifaceted metabolic disorder
that affects the body’s blood glucose levels [1]. Based on
insulin dependency, it can be classified into type 1 DM
(T1DM) and T2DM [2]. T2DM is an inflammatory disease
with immune system dysfunction [3]. Low-grade inflamma-
tion plays a significant role in the pathogenesis of T2DM,
particularly in the development of insulin resistance associ-
ated with obesity [4]. Chronic inflammation, indicated by
an elevated leukocyte count, may play a central role in the
development of diabetic macro- and microvascular compli-
cations [5]. Type 2 DM is also associated with changes in
serum levels of inflammatory markers like mean platelet vol-
ume (MPV) [6] and cytokines [7]. It is well known that
T2DM patients are recommended to maintain glycemic
Hindawi
Journal of Diabetes Research
Volume 2023, Article ID 3117396, 11 pages
https://doi.org/10.1155/2023/3117396

standards based on epidemiological data to prevent, or at
least delay, the onset and progression of vascular complica-
tions [8].
The HbA1c measures average glycemia over about three
months and aids in determining the disease’s level of man-
agement [9]. Poorer outcomes during the course of the dis-
ease are associated with higher HbA1c levels [10]. One of
the most often utilized tests to check on the management
of DM is the HbA1c [11]. It is unable to identify the ongoing
inflammatory changes in the body, though. The neutrophil-
to-lymphocyte ratio (NLR) can easily identify and monitor
such conditions [12].
The NLR is a reliable biomarker of low-grade inflamma-
tion in various clinical conditions such as hypertension, met-
abolic syndrome, obesity, and lifestyle changes [13]. Elevated
NLR has also been reported in various inflammatory dis-
eases including type 2 diabetes mellitus [14], irritable bowel
disease [15], cancer [16], inflammatory bowel disease [17],
cardiac conditions [18], thyroiditis [19], and COVID-19
infection [20]. NLR has emerged as a novel indicator of sys-
temic inflammatory response in various diseases in recent
years. In many clinical settings, NLR is considered an inde-
pendent predictor of major morbidity, mortality, and long-
term survival [21]. Besides, it can also be used for population
screening, disease detection, and drug monitoring [22]. Neu-
trophils are the main branch of leukocytes in the blood-
stream. Initially, they respond rapidly to the inflammatory
stimuli, and the neutrophil count increases in circulation.
Instead, interleukin levels that increase in inflammatory con-
ditions cause lymphopenia and neutrophilia, together caus-
ing elevated NLR [23, 24].
NLR represents neutrophil and lymphocyte; the 2 com-
ponents of chronic inflammatory condition [25]. A high
neutrophil value is a marker of the ongoing, destructive,
nonspecificinflammatory process. Conversely, a low lym-
phocyte count indicates relatively inadequate immune regu-
lation as well as a quiescent immunity pathway [26]. Hence,
a high level of NLR can indicate the functional status of the
immune system in the course of chronic inflammation [27].
However, NLR is relatively more stable and less influenced
by physiological, pathological, and physical factors than
individual leukocyte parameters [28]. The NLR is a low cost,
widely available parameter that has been investigated as a
reliable proxy marker of systemic inflammation in a spec-
trum of chronic diseases [29, 30].
Recently, the relationship between DM and NLR has also
become a current issue of investigation [31]. Therefore, the
main aim of this systematic review and meta-analysis is to
investigate the potential role of NLR as an indicator of glyce-
mic control in T2DM patients.
2. Method
2.1. Design and Protocol Registration. This systematic review
and meta-analysis were conducted as per the 2020
PRISMA guidelines [32]. The protocol has been registered
in the International Prospective Register of Systematic
Reviews (PROSPERO), with the registration number
CRD42021273819.
2.2. Eligibility Criteria. Articles were included in the meta-
analysis if they met each of the following criteria: (1) cross-
sectional, case-control, and cohort studies published in
peer-reviewed journals evaluating the relationship between
NLR and glycemic control in T2DM patients; (2) full text
in English; (3) published online up to July 2021; and (4)
expressing NLR results as mean and standard deviation
(SD) and/or median and interquartile range (IQR). We
have excluded studies with (1) insufficient or ambiguous
data for meta-analysis; (2) overlapping or duplicate data;
and (3) poster presentations, reviews, case reports, and
editorial letters.
2.3. Search Strategy. We conducted a comprehensive search
of eligible studies in the PubMed/MEDLINE, Cochrane
Library, Google Scholar, Scopus, Web of Science, and
EMBASE published until July 2021. It was strengthened by
searching the reference lists of published articles to identify
relevant unpublished studies. The search strategy was based
on the combinations of keywords and medical subject head-
ing (MeSH) terms as follows: “neutrophil lymphocyte ratio”
or “NLR”or “neutrophil-to-lymphocyte ratio”AND “glyce-
mic control”or “glucose regulation”“level of HgA1C”AND
“DM”or “diabetes mellitus”or “Type 2 diabetes.”
2.4. Selection Process. Articles retrieved across the search
strategy were imported to EndNote X7 (Thomson Reuters).
After precluding duplicated articles, titles and abstracts were
independently screened by the two review authors (Solomon
Getawa and Tiruneh Adane). For articles considered to
appear pertinent during title/abstract screening, the full-
text was appraised for inclusion in this study. Available dis-
crepancies between the review authors were resolved
through consensus, and a third review author (Mulugeta
Melku) was involved if required.
2.5. Data Extraction. Relevant data from the included studies
was summarized into an Excel spreadsheet. The following
study characteristics were extracted from the included stud-
ies; name of the first author; year of publication; study set-
ting; duration of illness; mean age of the participants; and
the NLR value in the good and poor glycemic control
groups.
2.6. Outcomes of Interest. The main outcome of interest is
the comparison of the NLR value between poor and good
glycemic control groups (in the form of SMD) in T2DM
patients. Six studies divided diabetes control into three
groups: group A, with HbA1c 7% (excellent control), group
B, with HbA1c 7.0-9.0% (poor control), and group C, with
HbA1c 9% (worst control), while the remaining seven stud-
ies classified glycemic control into two groups. Those with
HbA1c ≤7% (regulated diabetes) were included in group 1,
and those with HbA1c >7% (unregulated diabetes) were
included in group 2. The secondary outcome is to investigate
the association between the NLR values and elevated HbA1c
in T2DM patients (in the form of an odd ratio).
2.7. Risk of Bias Measurement. A modified Newcastle-
Ottawa quality assessment scale was used to evaluate the
2 Journal of Diabetes Research

methodological quality of the included studies [33]. The tool
uses 3 sections (selection, comparability, and exposure) to
evaluate the quality of case-control studies. Moreover,
cohort and cross-sectional studies are also evaluated using
3 sections (selection, comparability, and outcome). Studies
with a score of 5 and above are considered high quality.
2.8. Statistical Analysis. Results are presented as SMDs with
an associated 95% CI. Statistical heterogeneity was measured
using the I2statistic, with results above 50% considered to be
indicative of statistical heterogeneity. A random effect model
was employed to estimate the pooled SMD considering the
high heterogeneity in the included studies. According to
the recommended protocol, studies that reported the NLR
value in the form of median and IQR were changed to mean
(SD) [34]. Subgroup analysis, metaregression, and sensitivity
analysis were conducted to search for potential sources of
heterogeneity. The existence of publication bias was assessed
qualitatively using funnel plots and quantitatively using the
Eggers regression test. A pvalue <0.05 was considered statis-
tically significant. Statistical analyses were performed using
STATA 11.0 software.
Records identied from:
Databases (n = 626)
Registers (n = 6)
Records removed before
screening:
Duplicate records
removed (n = 590)
Records removed for
other reasons (n = 8)
Records screened
(n = 34)
Reports assessed for
eligibility
(n = 22)
Reports excluded:
(i)
(iii)
(iv)
(ii)
2 = studies did not report the
outcome variable
3 studies don’t meet specic
inclusion criteria
3 = studies report the outcome
in the form of correlation
1 = used a HbA1c cut o value
of 7.5
Studies included in review
(n = 13)
IdenticationScreening
Include
Records excluded
(n = 12)
Figure 1: Flow chart of study selection.
Table 1: Descriptive summary of the included studies on the role of NLR as glycemic control in T2DM patients.
Author, publication year Country
Sample size NLR Duration of illness
Quality scoreGood
control
Poor
control Good control Poor control Good
control
Poor
control
Dudani et al., 2021 [35] India 40 20 2:06 ± 0:77 1:94 ± 0:61 ——Good
Devamsh and Raghavan, 2019 [36] India 33 33 2:49 ± 1:22:701 ± 1:56:93 ± 5:36:84 ± 3:6Satisfactory
Mendes et al., 2019 [37] Brazil 12 127 3:9±5:84:9±8:6Good
Gubbala et al., 2019 [12] India 53 69 2:79 ± 0:97 3:74 ± 1:18 6:2±4:28:9±6:8Good
Hussain et al., 2017 [38] Pakistan 110 110 2:0±0:52:62 ± 0:42 ——Very good
Kemba, 2017 [39] India 9 51 2:08 ± 0:59 2:48 ± 0:43 5:55 ± 3:33 5:94 ± 3:17 Good
Liaqat et al., 2020 [40] Pakistan 52 48 2±0:52:7±1:0 14 ± 20 17 ± 24 Satisfactory
Sefil et al., 2014 [41] Turkey 34 37 1:45 ± 0:56 1:97 ± 0:56 7 ± 6:36:5±5:9Very good
Kumar et al., 2020 [42] India 21 29 3:52 ± 1:22 5:02 ± 1:29 ——Good
Assulyn et al., 2020 [43] Israel 53 57 1:90 ± 0:65 2:06 ± 0:83 10 ± 6 14 ± 8 Very good
Alnabi and Hussain, 2020 [44] Syria 38 45 2:29 ± 0:22:98 ± 0:3——Good
Palella et al., 2020 [45] Italy 58 75 1:90 ± 0:82:28 ± 0:97 ——Good
Najeeb, 2019 [46] India 110 110 2:0±0:52:7±1:0——Very good
3Journal of Diabetes Research

3. Result
3.1. Study Selection. A total of 632 abstracts were screened
for inclusion. Of the abstracts screened, 598 were excluded
as not being relevant and/or duplicates, leaving 34 studies
for screening. Finally, 13 studies were included in the quali-
tative and quantitative analysis (Figure 1).
3.2. Study Characteristics. Thirteen studies containing 1,434
participants (623 having good glycemic control and 811 with
poor glycemic control) were included. Six studies were con-
ducted in India, 2 in Pakistan, 1 in Italy, 1 in Turkey, 1 in
Syria, 1 in Brazil, and 1 in Israel. Five studies followed a
cross-sectional study design, one case-control, one retro-
spective, and four observational studies. Two studies did
not report the study design. The results of the Modified
Newcastle-Ottawa quality assessment scale showed that very
good, good, and satisfactory results were found in 4, 7, and 2
studies, respectively. Their characteristics are summarized in
Table 1.
3.3. Pooled Mean NLR Value in Poor and Good Glycemic
Control T2DM Patients. In this study, we tried to determine
the pooled mean NLR value in the poor and good glycemic
control groups through the random effect model. As a result,
the pooled NLR was 2.64 (95% CI: 2.30-2.97) (Figure 2) and
2.15 (95% CI: 1.88-2.42), respectively (Figure 3).
3.4. The Association between NLR and Glycemic Control in
T2DM Patients. A total of 13 studies were included in this
meta-analysis to explore the association between NLR and
glycemic control in T2DM patients. The box plot comparing
the NLR value is shown in Figure 4.
A random effect model was applied because of the signif-
icant heterogeneity between studies (I2=86:9%). In the
pooled analysis, a significant increase in NLR was observed
in the poor control groups than the good control groups
(SMD = 0:79; 95% CI, 0.46-1.12; p<:001) (Figure 5).
3.5. High vs. Low NLR and Glycemic Control in T2DM
Patients. Five studies reported the odd ratio of a high NLR
as an independent predictor of poor and/or worse glycemic
control in T2DM patients. The pooled OR was 1.70 (95%
CI: 1.50, 1.93) with no heterogeneity (I2=0:0%; pvalue =
0.559) (Figure 6).
3.6. Subgroup Analysis. To explore the sources of heteroge-
neity, subgroup analysis was carried out according to the
duration of illness. Accordingly, the NLR values were 0.70
(95% CI: 0.33, 1.07) and 0.55 (95% CI: -0.12, 1.22) for dura-
tions of less than 10 years and above 10 years, respectively
(Figure 7).
3.7. Sensitivity Analysis. Sensitivity analyses were performed
to evaluate the robustness of the results. One study was
Note: Weights are from random eects analysis
Overall (I2 = 0.0%, p = 0.644)
Palella et al 2020
Najeeb et al 2019
Akin et al 2019
Hussain et al 2017
Demirtas et al 2015
Author, year
Kemba et al 2017
Liaqat et al 2020
Dudani et al 2021
Assulyn et al 2020
Devamsh et al 2019
Gubbala et al 2019
Mendes et al 2019
Alanabi et al 2020
Kumar et al 2020
Sel et al 2014
of publication
2.54 (2.23, 2.84)
2.28 (0.38, 4.18)
2.70 (0.74, 4.66)
2.21 (1.29, 3.13)
2.62 (1.80, 3.44)
1.78 (0.58, 2.98)
2.48 (1.64, 3.32)
2.70 (0.74, 4.66)
1.94 (0.74, 3.14)
2.06 (0.43, 3.69)
2.70 (–0.24, 5.64)
3.74 (1.43, 6.05)
4.90 (–11.96, 21.76)
2.98 (2.39, 3.57)
5.02 (2.49, 7.55)
1.97 (0.87, 3.07)
Mean (95% CI)
100.00
2.56
2.41
10.89
13.64
6.46
13.01
2.41
6.46
3.49
1.07
1.73
0.03
26.73
1.45
7.67
Weight
%
Figure 2: A forest plot displaying the pooled estimate of NLR value among poor glycemic groups.
4 Journal of Diabetes Research

sequentially omitted at a time to assess its effect on the over-
all outcome. As a result, no apparent change occurred in the
NLR value when an individual study was omitted, confirm-
ing that the results were stable (Table 2).
3.8. Metaregression. A metaregression was conducted to
explore the effect of continuous covariates on differences in
the NLR value between poor and good glycemic control
groups. The continuous covariates included in the analysis
were the year of publication and the duration of illness.
Accordingly, any of the covariates show no effect on the
pooled SMD of the NLR values (Table 3).
3.9. Publication Bias. A funnel plot and Eggers regression
tests were performed to explore the presence of publication
bias. A visual inspection of the funnel plot shows no diver-
gence from the expected shape (Figure 8); suggesting the
absence of publication bias. This is also confirmed by using
the Egger tests; pvalue = 0.86 (Table 4).
4. Discussion
This systematic review and meta-analysis is aimed at inves-
tigating the association between NLR value and glycemic
control in T2DM patients. The findings demonstrated that
the mean NLR value in the poor group was significantly
higher than that of the good glycemic control group
(SMD = 0:79; 95% CI, 0.46-1.12; p<:001). This study also
showed that a high NLR value was significantly associated
with poor glycemic control in T2DM patients (OR = 1:50
(95% CI: 1.30-1.93)). This study confirms that the NLR value
increased as the HbA1c level worsened and could be a good
Note: Weights are from random eects analysis
Overall (I2 = 0.0%, p = 0.990)
Mendes et al 2019
Author, year
Kumar et al 2020
Hussain et al 2017
Dudani et al 2021
Sel et al 2014
Alanabi et al 2020
Palella et al 2020
of publication
Kemba et al 2017
Assulyn et al 2020
Liaqat et al 2020
Najeeb et al 2019
Devamsh et al 2019
Akin et al 2019
Dermitas et al 2015
Gubbala et al 2019
2.13 (1.88, 2.39)
3.90 (–7.47, 15.27)
3.52 (1.13, 5.91)
2.00 (1.02, 2.98)
2.06 (0.55, 3.57)
1.45 (0.35, 2.55)
2.29 (1.90, 2.68)
1.90 (0.33, 3.47)
Mean (95% CI)
2.08 (0.92, 3.24)
1.90 (0.63, 3.17)
2.00 (1.02, 2.98)
2.00 (1.02, 2.98)
2.49 (0.14, 4.84)
2.06 (1.08, 3.04)
1.89 (0.52, 3.26)
2.79 (0.89, 4.69)
100.00
0.05
%
1.18
7.00
2.95
5.58
43.72
2.73
Weight
5.02
4.14
7.00
7.00
1.21
7.00
3.57
1.86
Figure 3: A forest plot displaying the pooled estimate of NLR value among good glycemic groups.
1
2
3
4
5
NLR
NLR comparison
Good glycemic control
Poor glycemic control
Figure 4: Box plot displaying the comparison of NLR value in the
poor and good glycemic control groups.
5Journal of Diabetes Research

marker for assessing glycemic control in addition to HbA1c.
The increase in NLR in T2DM patients probably showed the
inflammatory burden of the disease.
In line with previous studies, this study showed that the
NLR value could be used as a marker of diabetic control level
besides the HbA1c level in T2DM patients [47, 48]. It can be
associated with the negative effects of neutrophils on endo-
thelial damage and the antiatherosclerotic role of lympho-
cytes [49]. Chronic inflammation in T2DM progresses with
leukocyte recruitment to the vascular environment in
response to oxidative stress and the production of proin-
flammatory cytokines [50]. The power of the NLR value as
an inflammatory factor stems from both a reduction in the
lymphocyte count and an increase in the neutrophil count
Note: Weights are from random eects analysis
Overall (I2 = 90.3%, p = 0.000)
Palella et al 2020
Liaqat et al 2020
Dermitas et al 2015
Mendes et al 2019
ID
Study
Devamsh et al 2019
Najeeb et al 2019
Alanabi et al 2020
Assulyn et al 2020
Sel et al 2014
Kumar et al 2020
Akin et al 2019
Hussain et al 2017
Dudani et al 2021
Gubbala et al 2019
Kemba et al 2017
0.69 (0.37, 1.01)
0.42 (0.08, 0.77)
0.90 (0.48, 1.31)
–0.17 (–0.43, 0.08)
0.12 (–0.47, 0.71)
SMD (95% CI)
0.16 (–0.33, 0.64)
0.89 (0.61, 1.16)
2.66 (2.07, 3.26)
0.21 (-0.16, 0.59)
0.93 (0.44, 1.42)
1.19 (0.58, 1.80)
0.31 (0.07, 0.55)
1.34 (1.05, 1.64)
–0.17 (–0.70, 0.37)
0.87 (0.49, 1.24)
0.88 (0.15, 1.60)
100.00
7.05
6.82
7.33
6.09
Weight
%
6.54
7.27
6.07
6.95
6.51
6.01
7.37
7.22
6.32
6.95
5.51
.10 1 10
Figure 5: A forest plot showing SMD of the NLR value between good and poor glycemic control in DM patients.
Note: Weights are from random eects analysis
Overall (I2 = 0.0%, p = 0.559)
Sel et al 2014
Kumar et al 2020
Study
Hussain et al 2017
ID
Liaqat et al 2020
Najeeb et al 2019
1.70 (1.50, 1.93)
1.41 (1.10, 1.81)
2.35 (0.29, 18.71)
1.81 (1.41, 2.32)
1.81 (1.41, 2.32)
1.81 (1.41, 2.32)
100.00
24.91
0.36
%
24.91
Weight
24.91
24.91
OR (95% CI)
1.81 (1.41, 2.32)
1.1 1 10
Figure 6: Pooled OR of high NLR value in DM patients.
6 Journal of Diabetes Research

[51]. Neutrophils rapidly respond to inflammatory stimuli
and increase their number in circulation. Studies showed
that there is an increased expression of activation markers
like CD11b/CD18 on monocytes and neutrophils in T2DM
patients, resulting in increased neutrophil adhesiveness to
the endothelium, independent of fasting glucose levels [52,
53]. Leucocytes in DM patients may also be activated by lep-
tin and advanced glycation end products [54]. Activated leu-
cocytes then contribute to systemic inflammation and
endothelial damage by releasing reactive oxygen species
through neutrophils and cytokines [55]. In addition, the rel-
ative number of regulatory T cells compared to helper T cells
is reduced in patients with DM [56]. Increased interleukin
levels during inflammation cause lymphopenia [23] and
Note: Weights are from random eects analysis
.
.
Overall (I2 = 82.1%, p = 0.000)
Sel et al 2014
Akin et al 2019
ID
Assulyn et al 2020
Liaqat et al 2020
Kembaet al 2017
Gubbala et al 2019
Study
Subtotal (I2 = 87.2%, p = 0.000)
Less than 10 year
Above 10 year
Dermitas et al 2015
Subtotal (I2 = 71.7%, p = 0.029)
Devamsh et al 2019
0.48 (0.16, 0.79)
0.93 (0.44, 1.42)
0.31 (0.07, 0.55)
SMD (95% CI)
0.21 (–0.16, 0.59)
0.90 (0.48, 1.31)
0.88 (0.15, 1.60)
0.87 (0.49, 1.24)
0.51 (–0.03, 1.04)
–0.17 (–0.43, 0.08)
0.45 (0.09, 0.82)
0.16 (–0.33, 0.64)
100.00
11.56
14.73
Weight
13.10
12.61
8.66
13.10
%
59.56
14.57
40.44
11.66
13.10
0.1 1 10
Figure 7: Subgroup analysis stratified by duration of DM.
Table 2: Sensitivity analysis.
Excluded studies SMD (95% CI) Heterogeneity
I2pvalue
Dudani et al., 2021 [35] 0.87 (0.54-1.19) 86% ≤0.001
Devamsh and Raghavan, 2019 [36] 0.84 (0.50-1.19) 87% ≤0.001
Mendes et al., 2019 [37] 0.84 (0.50-1.18) 87.3% ≤0.001
Gubbala et al., 2019 [12] 0.79 (0.42-1.15) 88% ≤0.001
Hussain et al., 2017 [38] 0.74 (0.40-1.08) 85.5% ≤0.001
Kemba, 2017 [39] 0.79 (0.44-1.13) 88% ≤0.001
Liaqat et al., 2020 [40] 0.78 (0.43-1.14) 88% ≤0.001
Sefil et al., 2014 [41] 0.78 (0.43-1.13) 88% ≤0.001
Kumar et al., 2020 [42] 0.76 (0.42-1.11) 87.8% ≤0.001
Assulyn et al., 2020 [43] 0.84 (0.50-1.19) 86.5% ≤0.001
Alnabi and Hussain, 2020 [44] 0.66 (0.39-0.92) 79.1% ≤0.001
Palella et al., 2020 [45] 0.83 (0.47-1.18) 87.3% ≤0.001
Najeeb, [46] 0.67 (0.32-1.02) 90.7% ≤0.001
Combined 0.79 (0.46-1.12) 86.9% ≤0.001
7Journal of Diabetes Research

neutrophilia [24], together resulting in a high NLR value. It
is associated with microvascular and macrovascular compli-
cations of DM and metabolic impairment [57].
The current study showed that the NLR is significantly
related to the level of hyperglycemia in T2DM patients.
Previous research has linked high NLR levels to elevated
HbA1c levels in T2DM [31, 41]. Clinicians measure the
long-term glycemic control in DM patients using the
HbA1c test. However, HbA1c may be affected by a variety
of genetic, hematologic, and illness-related factors. Hemo-
globinopathies, certain anemia, and disorders associated
with accelerated red cell turnover, such as malaria, are the
most common important factors affecting HbA1c levels
worldwide [58]. Furthermore, recent blood transfusion,
use of erythropoiesis-stimulating drugs, end-stage kidney
disease, and pregnancy may cause discrepancies between
the HbA1C result and the patient’s true mean glycaemia
[59]. The NLR has been identified as a potential marker
to determine inflammation in various cardiac and noncar-
diac disorders because it has a superior predictive, diagnos-
tic, and discriminative ability than the total WBC count
[36]. It is a simple and inexpensive test for assessing
inflammation that is obtained by dividing the absolute neu-
trophil to absolute lymphocyte count [60].
Aside from diabetes, the NLR value is used to predict the
prognosis of other inflammatory diseases, including cardio-
vascular disease [61], gestational diabetes mellitus [62],
chronic obstructive pulmonary disease [63], hypertension
[64], and colorectal cancer [65]. It has also proven its useful-
ness in the stratification of mortality in major cardiac events,
as a strong prognostic factor in several types of cancer, or as
a predictor and marker of inflammatory or infectious
pathologies (such as pediatric appendicitis) and postopera-
tive complications [66]. Increased NLR values and the risk
of cardiovascular events are explained by neutrophils secret-
ing inflammatory mediators that can cause vascular wall
degeneration [67] and lymphocytes regulating the inflam-
matory response and acting as antiatherosclerotic agents
[68]. Increased neutrophil and decreased lymphocyte count
in hypertensive complications such as neuropathy, cardio-
myopathy, and retinopathy occurred due to inflammatory
response developed in the arterial walls due to elevated pres-
sures [69, 70]. Recent evidence has shown that a high NLR
value can be used to predict inhospital and postdischarge
mortality in chronic obstructive pulmonary disease patients
[63]. Elevated NLR and poor prognosis have been reported
in different cancer patients due to inflammation-associated
elevation of tumor-associated neutrophils or neutrophils
which infiltrate tumors [71, 72].
Subgroup analysis of this study revealed that the dura-
tion of diabetes had no statistically significant difference in
NLR value to predict glycemic control in diabetic patients.
The findings were consistent with previous research [38,
41]. Though the pooled estimate did not show a significant
difference in NLR between the poor and good glycemic con-
trol groups, studies by Chittawar et al. and Gubbala et al.
found that the duration of T2DM and NLR were signifi-
cantly involved in determining the glycemic control of DM
patients [12, 73]. This is because T2DM patients are more
likely to develop microvascular complications, which result
in higher blood pressure, NLR, creatinine, and albumin
levels as the illness progresses [73].
The current study has some strengths and limitations.
The strength of the study is its comprehensive literature
search by the two independent authors to extract all avail-
able published articles. To the best of our knowledge, this
is the first systematic review and meta-analysis to address
the association between NLR and glycemic control in
T2DM patients. Even though we did metaregression, sub-
group, and sensitivity analysis, the heterogeneity was high.
This might be due to the inclusion of studies only in the
English language. Besides, the study cannot address the
prognostic and diagnostic role of NLR in the glycemic con-
trol of T2DM patients.
5. Conclusions and Recommendations
The results of this study showed that there was a higher NLR
value in poor glycemic control patients than in their coun-
terparts. This suggests an association of high NLR values
0
.1
.2
.3
.4
se (SMD)
0 .5 1 1.5 2 2.5
SMD
Funnel plot with pseudo 95% condence limits
Figure 8: Publication bias.
Table 4: Egger’s test.
Standard
effect Coefficient Standard
error p>t
jj
(95%
confidence
interval)
Slope 0.90 0.60 1.50 0.16 -0.42, 2.23
Bias -0.51 2.8 -0.18 0.86 -6.77, 5.74
Table 3: Metaregression.
Variables Coefficient (95% CI) pvalue
Year of publication 0.016 (-0.197,0.23) 0.870
Duration of illness
(poor glycemic control) 0.003 (-0.09, 0.092) 0.933
Duration of illness
(good glycemic control) 0.002 (-0.12, 0.13) 0.965
8 Journal of Diabetes Research

with an elevated HbA1c in T2DM patients. Therefore, NLR
should be considered a marker of glycemic control in addi-
tion to HbA1C in T2DM patients.
Abbreviations
DM: Diabetes mellitus
HbA1c: Plasma glycated hemoglobin
IL-6: Interleukin-6
NLR: Neutrophil-to-lymphocyte ratio
SMD: Standardized mean difference
T2DM: Type 2 diabetes mellitus.
Data Availability
All data generated or analyzed during this study are included
in this published article.
Conflicts of Interest
The authors declare that they have no competing interests.
Authors’Contributions
Tiruneh Adane designed the study, did the searching, statis-
tical analysis, and draft of the manuscript. Mulugeta Melku
designed the study, performed the statistical analysis, and
reviewed the manuscript. Yilkal Belete Worku designed the
study, conducted the statistical analysis, and reviewed the
manuscript. Melak Aynalem, Amanuel Kelem, and Aleba-
chew Fasil designed the study, performed the statistical anal-
ysis, and reviewed the manuscript. Solomon Getawa
designed the study, conducted the quality appraisal, and
reviewed the manuscript. All the authors critically revised
the paper and agreed to be accountable for all aspects of
the work.
References
[1] S. Tsalamandris, A. S. Antonopoulos, E. Oikonomou et al.,
“The role of inflammation in diabetes: current concepts and
future perspectives,”European Cardiology Review, vol. 14,
no. 1, pp. 50–59, 2019.
[2] American Diabetes Association, “Diagnosis and classification
of diabetes mellitus,”Diabetes Care, vol. 27, supplement_1,
pp. s5–s10, 2004.
[3] S. Liu, H. Zheng, X. Zhu et al., “Neutrophil-to-lymphocyte
ratio is associated with diabetic peripheral neuropathy in type
2 diabetes patients,”Diabetes Research and Clinical Practice,
vol. 130, pp. 90–97, 2017.
[4] M. Y. Donath and S. E. Shoelson, “Type 2 diabetes as an
inflammatory disease,”Nature Reviews Immunology, vol. 11,
no. 2, pp. 98–107, 2011.
[5] A. Abdel-Moneim, M. Semmler, E. S. Abdel-Reheim, M. I.
Zanaty, and W. Addaleel, “Association of glycemic status
and interferon-γproduction with leukocytes and platelet indi-
ces alterations in type2 diabetes,”Diabetes & Metabolic Syn-
drome: Clinical Research & Reviews, vol. 13, no. 3, pp. 1963–
1969, 2019.
[6] G. Aktas, M. Z. Kocak, T. T. Duman et al., “Mean platelet vol-
ume (mpv) as an inflammatory marker in type 2 diabetes mel-
litus and obesity,”Bali Medical Journal, vol. 7, no. 3, 2018.
[7] M. Z. Kocak, G. Aktas, E. Erkus et al., “Neuregulin-4 is associ-
ated with plasma glucose and increased risk of type 2 diabetes
mellitus,”Swiss Medical Weekly, vol. 43, 2019.
[8] Care, D., “6. Glycemic targets: standards of medical care in dia-
betes—2019,”Diabetes Care, vol. 42, Supplement_1, pp. s61–
s70, 2019.
[9] Organization WHO, Glycated haemoglobin (HBA 1c) for the
diagnosis of diabetes, World Health Organization, Geneva,
Switzerland, 2011.
[10] C. L. Rohlfing, H. M. Wiedmeyer, R. R. Little, J. D. England,
A. Tennill, and D. E. Goldstein, “Defining the relationship
between plasma glucose and HbA
1c
: analysis of glucose pro-
files and HbA
1c
in the diabetes control and complications
trial,”Diabetes Care, vol. 25, no. 2, pp. 275–278, 2002.
[11] T. J. Lyons and A. Basu, “Biomarkers in diabetes: hemoglobin
A1c, vascular and tissue markers,”Translational Research,
vol. 159, no. 4, pp. 303–312, 2012.
[12] F. Sefil, K. T. Ulutas, R. Dokuyucu et al., “Investigation of neu-
trophil lymphocyte ratio and blood glucose regulation in
patients with type 2 diabetes mellitus,”Journal of Evidence
Based Medicine and Healthcare, vol. 6, no. 50, pp. 3137–
3140, 2019.
[13] F. Imtiaz, K. Shafique, S. S. Mirza, Z. Ayoob, P. Vart, and
S. Rao, “Neutrophil lymphocyte ratio as a measure of systemic
inflammation in prevalent chronic diseases in Asian popula-
tion,”International Archives of Medicine, vol. 5, no. 1, pp. 2–
6, 2012.
[14] S. Bilgin, G. Aktas, M. Zahid Kocak et al., “Association
between novel inflammatory markers derived from hemogram
indices and metabolic parameters in type 2 diabetic men,”The
Aging Male, vol. 23, no. 5, pp. 923–927, 2020.
[15] G. Aktaş, T. T. Duman, B. Atak et al., “Irritable bowel syn-
drome is associated with novel inflammatory markers derived
from hemogram parameters,”Family Medicine and Primary
Care Review, vol. 22, no. 2, pp. 107–110, 2020.
[16] B. M. Atak, G. B. Kahveci, S. Bilgin, O. Kurtkulagi, and M. A.
Kosekli, “Platelet to lymphocyte ratio in differentiation of
benign and malignant thyroid nodules,”Experimental Bio-
medical Research, vol. 4, no. 2, pp. 148–153, 2021.
[17] E. Posul, B. Yilmaz, G. Aktas, and M. Kurt, “Does
neutrophil-to-lymphocyte ratio predict active ulcerative coli-
tis?,”Wiener Klinische Wochenschrift, vol. 127, no. 7-8,
pp. 262–265, 2015.
[18] H. Keskin, Y. Kaya, K. Cadirci et al., “Elevated neutrophil-
lymphocyte ratio in patients with euthyroid chronic autoim-
mune thyreotidis,”Endocrine Regulations, vol. 50, no. 3,
pp. 148–153, 2016.
[19] G. Aktas, M. Sit, O. Dikbas et al., “Elevated neutrophil-to-
lymphocyte ratio in the diagnosis of Hashimoto's thyroiditis,”
Revista da Associação Médica Brasileira, vol. 63, no. 12,
pp. 1065–1068, 2017.
[20] G. Aktas, “Hematological predictors of novel coronavirus
infection,”Revista da Associação Médica Brasileira, vol. 67,
suppl 1, pp. 1-2, 2021.
[21] Y. Solak, M. I. Yilmaz, A. Sonmez et al., “Neutrophil to lym-
phocyte ratio independently predicts cardiovascular events in
patients with chronic kidney disease,”Clinical and Experimen-
tal Nephrology, vol. 17, no. 4, pp. 532–540, 2013.
9Journal of Diabetes Research

[22] M. Hussain, M. Saeed, M. Z. M. Babar, M. A. Atif, and
L. Akhtar, “Nebivolol attenuates neutrophil lymphocyte ratio:
a marker of subclinical inflammation in hypertensive
patients,”International Journal of Hypertension, vol. 2017,
Article ID 7643628, 6 pages, 2017.
[23] K. P. Chung, H. T. Chang, S. C. Lo et al., “Severe lymphopenia
is associated with elevated plasma interleukin-15 levels and
increased mortality during severe sepsis,”Shock, vol. 43,
no. 6, pp. 569–575, 2015.
[24] T. M. Fonseka, R. S. McIntyre, J. K. Soczynska, and S. H. Ken-
nedy, “Novel investigational drugs targeting il-6 signaling for
the treatment of depression,”Expert Opinion on Investiga-
tional Drugs, vol. 24, no. 4, pp. 459–475, 2015.
[25] T. Xu, Z. Weng, C. Pei et al., “The relationship between
neutrophil-to-lymphocyte ratio and diabetic peripheral neu-
ropathy in type 2 diabetes mellitus,”Medicine, vol. 96,
no. 45, p. e8289, 2017.
[26] B. Azab, J. Daoud, F. B. Naeem et al., “Neutrophil-to-lympho-
cyte ratio as a predictor of worsening renal function in diabetic
patients (3-year follow-up study),”Renal Failure, vol. 34, no. 5,
pp. 571–576, 2012.
[27] P. Luo, Y. Huang, T. Xu, Y. Ji, N. Yu, and L. He, “Relationship
between hyperuricemia and neutrophil-to-lymphocyte ratio
in type 2 diabetes mellitus,”International Journal of Clinical
and Experimental Pathology, vol. 9, no. 10, pp. 10833–10838,
2016.
[28] S. Balta, E. Kurtoglu, U. Kucuk, S. Demirkol, and C. Ozturk,
“Neutrophil–lymphocyte ratio as an important assessment
tool,”Expert Review of Cardiovascular Therapy, vol. 12,
no. 5, pp. 537-538, 2014.
[29] J. S. Lee, N. Y. Kim, S. H. Na, Y. H. Youn, and C. S. Shin, “Ref-
erence values of neutrophil-lymphocyte ratio, lymphocyte-
monocyte ratio, platelet-lymphocyte ratio, and mean platelet
volume in healthy adults in South Korea,”Medicine, vol. 97,
no. 26, p. e11138, 2018.
[30] M. Moosazadeh, I. Maleki, R. Alizadeh-navaei et al., “Normal
values of neutrophil-to-lymphocyte ratio, lymphocyte-to-
monocyte ratio and platelet-to-lymphocyte ratio among Ira-
nian population: results of Tabari cohort,”Caspian Journal of
Internal Medicine, vol. 10, no. 3, pp. 320–325, 2019.
[31] S. Akin, Z. Aydin, G. Yilmaz, M. Aliustaoglu, and O. Keskin,
“Evaluation of the relationship between glycaemic regulation
parameters and neutrophil-to-lymphocyte ratio in type 2 dia-
betic patients,”Diabetes, vol. 7, no. 1, pp. 91–96, 2019.
[32] M. J. Page, J. E. Mckenzie, P. M. Bossuyt et al., “The prisma
2020 statement: an updated guideline for reporting systematic
reviews,”BMJ, vol. 372, 2021.
[33] G. Wells, B. Shea, D. O’connell et al., “Newcastle–Ottawa qual-
ity assessment scale—case control studies,”Ottawa: Ottawa
Hospital Research Institute, vol. 2, no. 1, pp. 1-2, 2017.
[34] S. P. Hozo, B. Djulbegovic, and I. Hozo, “Estimating the mean
and variance from the median, range, and the size of a sample,”
BMC Medical Research Methodology, vol. 5, no. 1, pp. 1–10,
2005.
[35] S. Dudani, S. Poodury, and S. Mangalesh, “Study of
neutrophil-lymphocyte ratio (NLR) in recent onset type 2 dia-
betes mellitus,”Atherosclerosis, vol. 10, no. 1, pp. 11–16, 2021.
[36] D. Gn and L. Raghavan, “Study of neutrophil lymphocyte ratio
in patients with type 2 diabetes mellitus and its correlation
with glycemic control,”International Journal of Advances in
Medicine, vol. 6, no. 5, pp. 1637–1641, 2019.
[37] B. B. Mendes, A. C. R. Oliveira, and K. C. D. Alcântara, “Com-
parison of the neutrophil-to-lymphocyte and platelet-to-
lymphocyte ratios in normoglycemic and hyperglycemic sub-
jects,”Einstein (São Paulo), vol. 17, 2018.
[38] M. Hussain, M. Z. M. Babar, L. Akhtar, and M. S. Hussain,
“Neutrophil lymphocyte ratio (NLR): a well assessment tool
of glycemic control in type 2 diabetic patients,”Pakistan Jour-
nal of Medical Sciences, vol. 33, no. 6, pp. 1366–1370, 2017.
[39] S. S. Madhavi Kemba, “Neutrophil-lymphocyte ratio: a risk
predictor in patients with type 2 diabetes mellitus,”Interna-
tional Journal of Physiology, vol. 5, no. 1, p. 166, 2017.
[40] R. N. Maham Liaqat and M. Zafar, “Neutrophil lymphocyte
ratio as an evaluation tool for the glycemic control in patients
suffering from diabetes,”Indo American Journal of Pharma-
ceutical Sciences, vol. 7, no. 1, pp. 844–848, 2020.
[41] F. Sefil, K. T. Ulutas, R. Dokuyucu et al., “Investigation of neu-
trophil lymphocyte ratio and blood glucose regulation in
patients with type 2 diabetes mellitus,”Journal of International
Medical Research, vol. 42, no. 2, pp. 581–588, 2014.
[42] V. S. Kumar, S. N. Aishwarya Ganga, and A. S. Anand, “Cor-
relation of neutrophillymphocyte ratio with glycosylated hb
in patients with type 2 diabetes mellitus,”Indian Journal of
Applied Research, vol. 10, no. 9, pp. 1–4, 2020.
[43] T. Assulyn, R. Khamisy‐Farah, W. Nseir, A. Bashkin, and
R. Farah, “Neutrophil-to-lymphocyte ratio and red blood cell
distribution width as predictors of microalbuminuria in type
2 diabetes,”Journal of Clinical Laboratory Analysis, vol. 34,
no. 7, article e23259, 2020.
[44] R. S. Ahmad Abed Alnabi and F. Hussain, “The relationship
between neutrophil to lymphocyte ratio and glycemic control
degree in patients with type 2 diabetes mellitus,”2020.
[45] E. Palella, R. Cimino, S. A. Pullano et al., “Laboratory param-
eters of hemostasis, adhesion molecules, and inflammation in
type 2 diabetes mellitus: correlation with glycemic control,”
International Journal of Environmental Research and Public
Health, vol. 17, no. 1, p. 300, 2020.
[46] N. N. Arsa, “Relationship between neutrophil lymphocyte
ratio and different levels of glycemic control in type 2 diabetic
patients,”World Journal of Pharmaceutical and Medical
Research, vol. 5, no. 3, pp. 344–347, 2019.
[47] T. T. Duman, G. Aktas, B. M. Atak, M. Z. Kocak, E. Erkus, and
H. Savli, “Neutrophil to lymphocyte ratio as an indicative of
diabetic control level in type 2 diabetes mellitus,”African
Health Sciences, vol. 19, no. 1, pp. 1602–1606, 2019.
[48] A. Fawwad, A. M. Butt, I. A. Siddiqui, M. Khalid, R. Sabir, and
A. Basit, “Neutrophil-to-lymphocyte ratio and microvascular
complications in subjects with type 2 diabetes: Pakistan’s per-
spective,”Turkish Journal of Medical Sciences, vol. 48, no. 1,
pp. 157–161, 2018.
[49] A. Shiny, Y. S. Bibin, C. S. Shanthirani et al., “Association of
neutrophil-lymphocyte ratio with glucose intolerance: an indi-
cator of systemic inflammation in patients with type 2 diabe-
tes,”Diabetes Technology & Therapeutics, vol. 16, no. 8,
pp. 524–530, 2014.
[50] P. Marques-Vidal, R. Schmid, M. Bochud et al., “Adipocyto-
kines, hepatic and inflammatory biomarkers and incidence of
type 2 diabetes. the CoLaus study,”PloS One, vol. 7, no. 12,
article e51768, 2012.
[51] X. Guo, S. Zhang, Q. Zhang et al., “Neutrophil:lymphocyte
ratio is positively related to type 2 diabetes in a large-scale
adult population: a Tianjin chronic low-grade systemic
10 Journal of Diabetes Research

inflammation and health cohort study,”European Journal of
Endocrinology, vol. 173, no. 2, pp. 217–225, 2015.
[52] A. J. Van Oostrom, J. P. Van Wijk, T. P. Sijmonsma, T. J. Rabe-
link, and M. Castro Cabezas, “Increased expression of activa-
tion markers on monocytes and neutrophils in type 2
diabetes,”The Netherlands Journal of Medicine, vol. 62, no. 9,
pp. 320–325, 2004.
[53] S. Berliner, O. Rogowski, R. Rotstein et al., “Activated poly-
morphonuclear leukocytes and monocytes in the peripheral
blood of patients with ischemic heart and brain conditions
correspond to the presence of multiple risk factors for athero-
thrombosis,”Cardiology, vol. 94, no. 1, pp. 19–25, 2000.
[54] M. Pertyńska-Marczewska, S. Kiriakidis, R. Wait, J. Beech,
M. Feldmann, and E. M. Paleolog, “Advanced glycation end
products upregulate angiogenic and pro-inflammatory cyto-
kine production in human monocyte/macrophages,”Cytokine,
vol. 28, no. 1, pp. 35–47, 2004.
[55] R. Shurtz-Swirski, S. Sela, A. T. Herskovits et al., “Involvement
of peripheral polymorphonuclear leukocytes in oxidative
stress and inflammation in type 2 diabetic patients,”Diabetes
Care, vol. 24, no. 1, pp. 104–110, 2001.
[56] G. Fontana, A. Lapolla, M. Sanzari et al., “An immunological
evaluation of type II diabetic patients with periodontal dis-
ease,”Journal of Diabetes and its Complications, vol. 13,
no. 1, pp. 23–30, 1999.
[57] E. Y. Moursy, M. H. Megallaa, R. F. Mouftah, and S. M.
Ahmed, “Relationship between neutrophil-lymphocyte ratio
and microvascular complications in Egyptian patients with
type 2 diabetes,”American Journal of Medicine, vol. 3, no. 6,
pp. 250–255, 2015.
[58] E. J. Gallagher, D. Le Roith, and Z. Bloomgarden, “Review of
hemoglobin A
1c
in the management of diabetes,”Journal of
Diabetes, vol. 1, no. 1, pp. 9–17, 2009.
[59] Assessment G, “6. Glycemic targets: standards of medical care
in diabetes 2021,”Diabetes Care, vol. 44, article s73, Supple-
ment_1, pp. S73–S84, 2021.
[60] M. Yuksel, A. Yildiz, M. Oylumlu et al., “Novel markers of
endothelial dysfunction and inflammation in Behçet's disease
patients with ocular involvement: epicardial fat thickness,
carotid intima media thickness, serum ADMA level, and
neutrophil-to-lymphocyte ratio,”Clinical Rheumatology,
vol. 35, no. 3, pp. 701–708, 2016.
[61] T. Angkananard, T. Anothaisintawee, M. McEvoy, J. Attia, and
A. Thakkinstian, “Neutrophil lymphocyte ratio and cardiovas-
cular disease risk: a systematic review and meta-analysis,”
BioMed Research International, vol. 2018, Article ID
2703518, 11 pages, 2018.
[62] N. P. Pace and J. Vassallo, “Association bbetween neutrophil-
lymphocyte ratio and gestational diabetes—a systematic
review and meta-analysis,”Journal of the Endocrine Society,
vol. 5, no. 7, 2021.
[63] P. Paliogiannis, A. G. Fois, S. Sotgia et al., “Neutrophil to lym-
phocyte ratio and clinical outcomes in COPD: recent evidence
and future perspectives,”European Respiratory Review, vol. 27,
no. 147, article 170113, 2018.
[64] E. Belen, A. Sungur, M. A. Sungur, and G. Erdoğan, “Increased
neutrophil to lymphocyte ratio in patients with resistant
hypertension,”The Journal of Clinical Hypertension, vol. 17,
no. 7, pp. 532–537, 2015.
[65] S. R. Walsh, E. J. Cook, F. Goulder, T. A. Justin, and N. J. Keel-
ing, “Neutrophil-lymphocyte ratio as a prognostic factor in
colorectal cancer,”Journal of Surgical Oncology, vol. 91,
no. 3, pp. 181–184, 2005.
[66] P. Forget, C. Khalifa, J. P. Defour, D. Latinne, M. C. Van Pel,
and M. De Kock, “What is the normal value of the
neutrophil-to-lymphocyte ratio?,”BMC Research Notes,
vol. 10, no. 1, pp. 1–4, 2017.
[67] U. Ikeda, M. Ikeda, T. Oohara, S. Kano, and T. Yaginuma,
“Mitogenic action of interleukin-1αon vascular smooth mus-
cle cells mediated by PDGF,”Atherosclerosis, vol. 84, no. 2-3,
pp. 183–188, 1990.
[68] E. Simpson and H. Cantor, “Regulation of the immune
response by subclasses of T lymphocytes. II. The effect of adult
thymectomy upon humoral and cellular responses in mice,”
European Journal of Immunology, vol. 5, no. 5, pp. 337–343,
1975.
[69] B. Srinivasagopalane, S. Andrew Rajarathinam, and
T. Balasubramaiyan, “Clinical pertinence of neutrophil-to-
lymphocyte ratio among hypertensives with different grades
and duration of hypertension –an insight,”Clinical and Exper-
imental Hypertension, vol. 41, no. 4, pp. 394–399, 2019.
[70] Y. H. Jhuang, T. W. Kao, T. C. Peng et al., “Neutrophil to lym-
phocyte ratio as predictor for incident hypertension: a 9-year
cohort study in Taiwan,”Hypertension Research, vol. 42,
no. 8, pp. 1209–1214, 2019.
[71] A. J. Templeton, M. G. McNamara, B. Šeruga et al., “Prognos-
tic role of neutrophil-to-lymphocyte ratio in solid tumors: a
systematic review and meta-analysis,”JNCI: Journal of the
National Cancer Institute, vol. 106, no. 6, 2014.
[72] H. K. Jensen, F. Donskov, N. Marcussen, M. Nordsmark,
F. Lundbeck, and H. von der Maase, “Presence of intratumoral
neutrophils is an independent prognostic factor in localized
renal cell carcinoma,”Journal of Clinical Oncology, vol. 27,
no. 28, pp. 4709–4717, 2009.
[73] S. Chittawar, D. Dutta, Z. Qureshi, V. Surana, S. Khandare,
and T. N. Dubey, “Neutrophil-lymphocyte ratio is a novel reli-
able predictor of nephropathy, retinopathy, and coronary
artery disease in Indians with type-2 diabetes,”Indian Journal
of Endocrinology and Metabolism, vol. 21, no. 6, pp. 864–870,
2017.
11Journal of Diabetes Research