Abstract
Background
Neutral‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), and platelet‐to‐lymphocyte ratio (PLR) are associated with coronavirus disease 2019 (COVID‐19) and many diseases, but there are few data about the reference interval (RI) of NLR, LMR, and PLR.
Methods
The neutrophil count, lymphocyte count, monocyte count, and platelet count of 404,272 Chinese healthy adults (>18 years old) were measured by Sysmex XE‐2100 automatic hematology analyzer, and NLR, LMR, and PLR were calculated. According to CLSI C28‐A3, the nonparametric 95% percentile interval is defined as the reference interval.
Results
The results of Mann‐Whitney U test showed that NLR (p < .001) in male was significantly higher than that in female; LMR (p < .001) and PLR (p < .001) in male were significantly lower than that in female. Kruskal‐Wallis H test showed that there were significant differences in NLR, LMR, and PLR among different genders and age groups (p < .001). The linear graph showed that the reference upper limit of NLR and PLR increased with age and the reference upper limit of LMR decreases with age in male population. In female population, the reference upper limit of NLR in 50–59 group, LMR in >80 group, and PLR in 70–79 group appeared a trough; the reference upper limit of NLR in >80 group, LMR in 50–59 group, and PLR in 40–49 group appeared peak.
Conclusion
The establishment of RI for NLR, LMR, and PLR in Chinese healthy adults according to gender and age will promote the standardization of clinical application.
Keywords: lymphocyte‐to‐monocyte ratio, neutrophil‐to‐lymphocyte ratio, platelet‐to‐lymphocyte ratio, reference interval
Values of upper reference limits for three indicators in different age partitions. A: Values of upper reference limits for NLR in different age partitions. B: Values of upper reference limits for LMR in different age partitions. C: Values of upper reference limits for PLR in different age partitions. The line chart based on age showed that the reference upper limit of NLR, LMR, and PLR increased with age in male population. In female population, the reference upper limit of NLR in 50–59 group, LMR in >80 group, and PLR in 70–79 group showed a trough; the reference upper limit of NLR in >80 group, LMR in 50–59 group, and PLR in 40–49 group showed peak.
1. INTRODUCTION
With the deepening of the research on inflammatory markers, there is a growing interest in research aimed at better understanding the disease status or predicting the prognosis of patients with simple blood inflammatory markers. Neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), and platelet‐to‐lymphocyte ratio (PLR) are novel biomarkers of systemic inflammation, which are closely related to immune response.
Studies have shown that NLR, LMR, and PLR are a independent risk factor for coronavirus disease 2019 (COVID‐19)1, 2, 3 and can predictive of response to chemotherapy and survival in patients with malignancy.4, 5, 6, 7, 8 They are also associated with a variety of other diseases. Platelet‐to‐lymphocyte ratio (PLR) has been suggested to be associated with type 2 diabetes mellitus9 and bowel disease.10 PLR can also be used as a prognostic marker of fibrosis in patients with NAFLD and can be disturbed in patients with liver cirrhosis.11 On the other hand, neutrophil‐to‐lymphocyte ratio (NLR) has been suggested to be associated with cardiac arrhytmia,12 inflammatory bowel disease,13 thyroiditis,14 malignant nodules,15 diabetes mellitus,16 and irritable bowel syndrome.17 Similarly, lymphocyte‐to‐monocyte ratio (LMR) or reversely monocyte‐to‐lymphocyte ratio has been related to diabetic foot,18 breast cancer,19 and diabetic kidney injury.20
Therefore, these markers have been widely used in clinical practice. However, due to the influence of genotype, geographical location, lifestyle, and many other factors, these markers may be different among different regions, genders, and ages. Therefore, we urgently need to establish a specific and reliable reference interval (RI) for NLR, LMR, and PLR in Chinese population.
Prior to that, some scholars have carried out relevant research on the reference intervals of NLR, LMR, and PLR.21, 22, 23 However, the results are not very representative due to the small amount of data and incomplete coverage area. In this study, 404,272 healthy adults were tested and the reference intervals of NLR, LMR, and PLR were established according to Clinical and Laboratory Standards Institute (CLSI) CA28‐A3.24
2. MATERIAL AND METHODS
2.1. Study subjects
According to the inclusion and exclusion criteria, 404,272 healthy adults (205,592 men, 18–112 years old; 198,680 women, 18–112 years old) who completed physical examination in the physical examination center of the First Affiliated Hospital of Wenzhou Medical University from January 2009 to December 2019 were selected as the research objects. According to CLSI C28‐A3, the subjects were divided into 12 groups according to gender (male and female) and age (18–39 years old; 40–49 years old; 50–59 years old; 60–69 years old; 70–79 years old; and >80 years old) to determine whether the distribution of NLR, LMR, and PLR varied with age and / or gender. The detailed screening procedures of the study participants are shown in Figure 1.
FIGURE 1.
Establishing reference interval of neutrophil‐to‐lymphocyte ratio, lymphocyte‐to‐monocyte ratio, and platelet‐to‐lymphocyte ratio on the bias of Clinical and Laboratory Standards Institute CA28‐A3
Inclusion criteria were as follows: (a) adults over 18 years old; (b) no history of surgery in the past 6 months; (c) no leukemia or any other blood system diseases; (d) no receiving transfusion of blood or any other blood products; (e) infectious diseases such as hepatitis B virus, hepatitis C virus, syphilis, and acquired immune deficiency syndrome were negative. Exclusion criteria were as follows: (a) acute inflammation or infection; (b) acute or chronic liver, kidney, lung, brain, heart, or other systemic diseases; (c) drug treatment history in the past month; (d) recent irregular diet, irregular working hours, insufficient sleep, or excessive drinking. This study was approved by the ethics committee of the First Affiliated Hospital of Wenzhou Medical University.
2.2. Laboratory methods
The venous blood collected from each subject was anticoagulated with EDTA‐K2 and tested within 2 h. According to the principle of five blood cell classification, Sysmex XE‐2100 automatic blood cell analyzer and related reagents (Sysmex) were used to determine the test items: neutrophil count, lymphocyte count, monocyte count, and platelet count in strict accordance with the instructions. NLR, LMR, and PLR are calculated as follows: NLR = neutral count/lymphocyte count,25 LMR = lymphocyte count/monocyte count,26 and PLR = platelet count/lymphocyte count.27 Use special reagents and standard methods. Two levels of control materials (e‐CHECK (XE)) were used daily quality control. During the whole study period, internal quality control (IQC) was conducted by Westgard multi rule quality control method. The total coefficient of variation (CV) of the two control materials was less than 5%.
2.3. Statistical analysis
Kolmogorov‐Smirnov test was used to test the normality of the data; the normal distribution measurement data were expressed as X±s, and the comparison between the two groups was conducted by t test; the non‐normal distribution measurement data was expressed as the median (p25‐p75), and the comparison between the two groups was conducted by Mann‐Whitney U test, and the comparison among the multiple groups was conducted by Kruskal‐Wallis H test; reference interval was established from nonparametric 95% percentile according to CLSI C28‐A3.13 Statistical analysis was conducted by using IBM SPSS statistics version 20.0 software and MedCalc 19.1 software. p < .05 was statistically significant.
3. RESULTS
SPSS statistical results showed that among the 404,272 subjects included in the study, 205,592 were male, accounting for 50.85%; 198,680 were female, accounting for 49.15%; and the ratio of male and female was 1.03. Kolmogorov‐Smirnov test showed that NLR, LMR, and PLR data showed skewed distribution (p < .05) (Figure 2). In order to explore the influence of gender on NLR, LMR, and PLR, we used Mann‐Whitney U test to compare NLR, LMR, and PLR between different genders. The results showed that NLR in male (p < .001) was significantly higher than that in female; LMR in male (p < .001) and PLR in male (p < .001) were significantly lower than in women (Table 1).
FIGURE 2.
Distribution histogram of three indicators. A, Kolmogorov‐Smirnov test showed that NLR data showed skewed distribution. B, Kolmogorov‐Smirnov test showed that LMR data showed skewed distribution. C, Kolmogorov‐Smirnov test showed that PLR data showed skewed distribution
TABLE 1.
Sex‐dependent reference values for three indicators
| Gender | Number | Median (P25‐P75) | RIs | Z‐value | p‐value |
|---|---|---|---|---|---|
| Male (NLR) | 205,592 | 1.550 (1.252–1.933) | 0–2.696 | −22.093 | <.001 |
| Female (NLR) | 198,680 | 1.587 (1.272–2.000) | 0–2.805 | ||
| Male (LMR) | 205,592 | 5.14 (4.22–6.26) | 0–9.00 | −71.132 | <.001 |
| Female (LMR) | 198,680 | 5.50 (4.49–6.88) | 0–10.00 | ||
| Male (PLR) | 205,592 | 102.00 (84.70–123.24) | 0–162.84 | −141.920 | <.001 |
| Female (PLR) | 198,680 | 116.57 (96.28–141.05) | 0–185.52 |
Abbreviations: IQR, interquartile range; RI, reference interval.
In order to explore the influence of age on NLR, LMR, and PLR, we used Kruskal‐Wallis H test to compare the NLR, LMR, and PLR of male and female on the basis of Mann‐Whitney U test results. In the male group, there were significant differences in NLR (p < .001), LMR(p < .001), and PLR(p < .001) in different age groups. In the female group, there were also significant differences in NLR (p < .001), LMR (p < .001), and PLR (p < .001) in different age groups (Tables 2, 3, 4).
TABLE 2.
Age‐dependent and sex‐dependent reference values for NLR
| Age | Number | Median (P25‐P75) | RIs | H‐value | p‐value |
|---|---|---|---|---|---|
| 18–39 (male) | 79,180 | 1.50 (1.21–1.85) | 0–2.55 | 3245.610 | <.001 |
| 40–49 (male) | 60,350 | 1.55 (1.25–1.91) | 0–2.64 | ||
| 50–59 (male) | 38,825 | 1.59 (1.28–2.00) | 0–2.76 | ||
| 60–69 (male) | 18,404 | 1.67 (1.33–2.12) | 0–2.99 | ||
| 70–79 (male) | 6791 | 1.74 (1.38–2.22) | 0–3.17 | ||
| >80 (male) | 2041 | 1.78 (1.39–2.26) | 0–3.28 | ||
| 18–39 (female) | 85,970 | 1.59 (1.28–2.00) | 0–2.80 | 3232.729 | <.001 |
| 40–49 (female) | 53,623 | 1.68 (1.35–2.09) | 0–2.90 | ||
| 50–59 (female) | 36,244 | 1.48 (1.19–1.86) | 0–2.65 | ||
| 60–69 (female) | 16,193 | 1.51 (1.21–1.90) | 0–2.73 | ||
| 70–79 (female) | 5372 | 1.60 (1.25–2.04) | 0–2.88 | ||
| >80 (female) | 1278 | 1.76 (1.38–2.21) | 0–3.39 |
Abbreviations: IQR, interquartile range; RI, reference interval.
TABLE 3.
Age‐dependent and sex‐dependent reference values for LMR
| Age | Number | Median (P25‐P75) | RIs | H‐value | p‐value |
|---|---|---|---|---|---|
| 18–39 (male) | 79,180 | 5.29 (4.40–6.47) | 0–9.48 | 3839.148 | <.001 |
| 40–49 (male) | 60,350 | 5.20 (4.29–6.33) | 0–9.00 | ||
| 50–59 (male) | 38,825 | 5.00 (4.13–6.11) | 0–8.67 | ||
| 60–69 (male) | 18,404 | 4.77 (3.90–5.82) | 0–8.21 | ||
| 70–79 (male) | 6791 | 4.56 (3.69–5.67) | 0–8.33 | ||
| >80 (male) | 2041 | 4.37 (3.55–5.46) | 0–7.67 | ||
| 18–39 (female) | 85,970 | 5.50 (4.50–6.87) | 0–10.04 | 3054.759 | <.001 |
| 40–49 (female) | 53,623 | 5.25 (4.25–6.50) | 0–9.50 | ||
| 50–59 (female) | 36,244 | 5.89 (4.75–7.31) | 0–10.37 | ||
| 60–69 (female) | 16,193 | 5.76 (4.72–7.17) | 0–10.17 | ||
| 70–79 (female) | 5372 | 5.40 (4.35–6.73) | 0–9.67 | ||
| >80 (female) | 1278 | 5.05 (4.00–6.45) | 0–8.78 |
Abbreviations: IQR, interquartile range; RI, reference interval.
TABLE 4.
Age‐dependent and sex‐dependent reference values for PLR
| Age | Number | Median (P25‐P75) | RIs | H ‐value | p‐value |
|---|---|---|---|---|---|
| 18–39 (male) | 79,180 | 101.30 (84.44–121.61) | 0–159.55 | 130.254 | <.001 |
| 40–49 (male) | 60,350 | 102.33 (85.11–123.18) | 0–162.43 | ||
| 50–59 (male) | 38,825 | 102.91 (85.29–124.83) | 0–164.49 | ||
| 60–69 (male) | 18,404 | 103.01 (84.44–125.98) | 0–170.65 | ||
| 70–79 (male) | 6791 | 100.63 (81.69–125.36) | 0–169.91 | ||
| >80 (male) | 2041 | 102.50 (81.08–127.83) | 0–177.16 | ||
| 18–39 (female) | 85,970 | 115.43 (95.98–138.85) | 0–181.43 | 3791.161 | <.001 |
| 40–49 (female) | 53,623 | 123.68 (102.22–149.32) | 0–196.15 | ||
| 50–59 (female) | 36,244 | 114.09 (94.38–138.25) | 0–183.47 | ||
| 60–69 (female) | 16,193 | 109.05 (90.00–132.66) | 0–175.00 | ||
| 70–79 (female) | 5372 | 106.07 (86.00–130.00) | 0–173.25 | ||
| >80 (female) | 1278 | 109.96 (88.50–138.75) | 0–190.46 |
Abbreviations: IQR, interquartile range; RI, reference interval.
Further between‐group comparisons by Mann‐Whitney U test showed statistically significant differences between most age partitions. In the male group for NLR, the average NLR of 18–39 group was significantly lower than 40–49 group (Z = −19.639, p < .001), 50–59 group (Z = −31.012, p < .001), 60–69 group (Z = −41.339, p < .001), 70–79 group (Z = −34.845, p < .001), and >80 group (Z = −21.320, p < .001). In the female group for NLR, the average NLR of 50–59 group was significantly lower than 18–39 group (Z = −31.287, p < .001), 40–49 group (Z = −52.664, p < .001), 60–69 group (Z = −5.378, p < .001), 70–79 group (Z = −13.665, p < .001), and >80 group (Z = −15.770, p < .001). In the male group for LMR, the average LMR of >80 group was significantly lower than 18–39 group (Z = −26.335, p < .001), 40–49 group (Z = −23.237, p < .001), 50–59 group (Z = −18.182, p < .001), 60–69 group (Z = −10.766, p < .001), and 70–79 group (Z = −4.619, p < .001). In the female group for LMR, the average LMR of >80 group was significantly lower than 18–39 group (Z = −9.638, p < .001), 40–49 group (Z = −3.927, p < .001), 50–59 group (Z = −15.428, p < .001), 60–69 group (Z = −13.880, p < .001), and 70–79 group (Z = −6.517, p < .001). In the male group for PLR, the average PLR of 70–79 group was lower than 18–39 group (Z = −0.852, p = .394), 40–49 group (Z = −3.619, p < .001), 50–59 group (Z = −4.872, p < .001), 60–69 group (Z = −4.599, p < .001), and >80 group (Z = −0.817, p = .414). In the female group for PLR, the average PLR of 70–79 group was significantly lower than 18–39 group (Z = −20.679, p < .001), 40–49 group (Z = −35.151, p < .001), 50–59 group (Z = −17.301, p < .001), 60–69 group (Z = −6.816, p < .001), and >80 group (Z = −4.394, p < .001).
According to the nonparametric method recommended by CLSI CLSI C28‐A3, we established NLR, LMR, and PLR reference intervals for different genders and ages. The line chart based on age showed that the reference upper limit of NLR and PLR increased with age and the reference upper limit of LMR decreases with age in male population. In female population, the reference upper limit of NLR in 50–59 group, LMR in >80 group, and PLR in 70–79 group showed a trough; the reference upper limit of NLR in >80 group, LMR in 50–59 group, and PLR in 40–49 group showed peak(Figure 3).
FIGURE 3.
Values of upper reference limits for three indicators in different age partitions. A, The reference upper limit of NLR increased with age in male population. In female population, the reference upper limit of NLR in 50–59 group showed a trough and the reference upper limit of NLR in >80 group showed peak. B, The reference upper limit of LMR decreases with age in male population. In female population, the reference upper limit of LMR in >80 group showed a trough and the reference upper limit of LMR in 50–59 group showed peak. C, The reference upper limit of PLR increased with age in male population. In female population, the reference upper limit of PLR in 70–79 group showed a trough and the reference upper limit of PLR in 40–49 group showed peak
4. DISCUSSION
In today's global pandemic of COVID‐19, NLR, LMR, and PLR, as simple and easy to measure systemic inflammatory markers, have attracted more and more attention and have been widely used in the world.28, 29
However, the results of NLR, LMR, and PLR without appropriate RI in clinical application are not valuable. Meng x30 only analyzed the clinical data of different disease groups in the study of PLR, but did not consider the reference range of PLR, which led to the inability to know whether the clinical data exceeded the normal reference range. Many retrospective studies have proposed "high‐risk" cutoff levels of NLR from Kaplan‐Meier curves and multivariate Cox regression analysis, but gender and age factors have not been considered. Therefore, we have established the appropriate reference interval according to gender and age, which can provide important basis for the diagnosis, progress, and prognosis of clinical diseases.
NLR, LMR, and PLR are important inflammatory markers. Different studies have shown that the NLR cutoff values for populations in western countries range from 2.5 to 5, higher than those in Asia or Africa.31, 32 Another study shows that the average NLR of Americans except non‐Hispanic black patients is higher than 2.33 This study shows that the average NLR of Chinese men and women is 1.550 and 1.587, respectively, which is lower than that of the United States or other western countries. It is consistent with previous studies. The reason may be related to the different natural environment, cultural environment, and eating habits in different regions. The reference upper limit of male NLR and PLR increased with age, and the reference upper limit of male LMR decreased with age, which may be due to the aging of human. The reason for this result may be the decline of immunity,34 the thymus involvement,35 and changes in T‐cell subsets,36 and the absolute value of lymphocytes decreased slowly. The reference upper limit of NLR, LMR, and PLR in women varies with age, which is not only the reason for the decrease of absolute value of lymphocyte representing immunity, but also related to the exuberance of sex hormone represented by estrogen and progesterone in reproductive period and the significant decrease of sex hormone in menopause. These sex hormones can increase the aggregation of neutrophils and monocytes, promote the formation of megakaryocyte polyploidy, and the formation and release of PLT precursors.37, 38
Although this study has established the reference range of NLR, LMR, and PLR based on the big data of 404,272 Chinese adults, the limitations of this study are worth emphasizing. First of all, this study is limited to the population in East China, which may make the results unrepresentative and impossible to be directly applied to subjects in other regions or clinical laboratories. In the future, it is necessary to conduct research in multiple regions and centers. Second, because this study only analyzes the data of healthy adults (>18 years old), there is no data research on adolescents, preschool children, and other special groups such as pregnant women. Third, this study also lacks more abundant data to eliminate the influence factors of these indicators, such as body mass index (BMI). In the future, we will conduct further research and collect more data.
In summary, we have established the reference range of NLR, LMR, and PLR for Chinese healthy adults of different genders and ages through big data. This will help to increase the rationality of relevant experimental research design and also help to better regulate the application of NLR, LMR, and PLR in clinical practice.
Wang J, Zhang F, Jiang F, Hu L, Chen J, Wang Y. Distribution and reference interval establishment of neutral‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), and platelet‐to‐lymphocyte ratio (PLR) in Chinese healthy adults. J Clin Lab Anal. 2021;35:e23935. 10.1002/jcla.23935
Wang, Zhang and Jiang contributed equally to this study.
Funding information
National Natural Science Foundation of China, Grant/Award Number: 81672088; Natural Science Foundation of Zhejiang Provincial, Grant/Award Number: LY19H200002, Wenzhou Municipal Science and Technology Bureau, China, Grant/Award Number: Y20180548; Research incubation project at Institute level, Grant/Award Number: FHY2019059; Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Grant/Award Number: JBZX‐202003
DATA AVAILABILITY STATEMENT
All data included in this study are available upon request by contact with the corresponding author.
REFERENCES
- 1.Shi N, Ma Y, Fan Y, et al. Predictive value of the neutrophil‐to‐lymphocyte ratio (NLR) for diagnosis and worse clinical course of the COVID‐19: findings from ten provinces in China. SSRN Electronic J. 2020;1(1):1‐43. [Google Scholar]
- 2.Liu J, Liu Y, Xiang P, et al. Neutrophil‐to‐lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage. J Transl Med. 2020;18(1):1‐12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Zhu S, Dong L, Cai W. Predictive value of neutrophil to lymphocyte and platelet to lymphocyte ratio in COVID‐19. Crit Care. 2020;24(1):532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Dalpiaz O, Krieger D, Ehrlich GC, et al. Validation of the preoperative platelet‐to‐lymphocyte ratio as a prognostic factor in a European cohort of patients with upper tract urothelial carcinoma. Urol Int. 2017;98:320‐327. [DOI] [PubMed] [Google Scholar]
- 5.Mei Z, Shi L, Wang B, et al. Prognostic role of pretreatment blood neutrophil‐to‐lymphocyte ratio in advanced cancer survivors: a systematic review and meta‐analysis of 66 cohort studies. Cancer Treat Rev. 2017;58:1‐13. [DOI] [PubMed] [Google Scholar]
- 6.Jiang T, Qiao M, Zhao C, et al. Pretreatment neutrophil‐to‐lymphocyte ratio is associated with outcome of advanced‐stage cancer patients treated with immunotherapy: a meta‐analysis. Cancer Immunol Immunother. 2018;67(5):713‐727. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Hsueh C, Tao L, Zhang M, et al. The prognostic value of preoperative neutrophils, platelets, lymphocytes, monocytes and calculated ratios in patients with laryngeal squamous cell cancer. Oncotarget. 2017;8(36):60514‐60527. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Wang H, Gu L, Wu Y, et al. The values of neutrophil‐lymphocyte ratio and/or prostate‐specific antigen in discriminating real Gleason score ≥7 prostate cancer from group of biopsy‐based Gleason score ≤6. BMC Cancer. 2017;17(1):629. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Atak B, Aktas G, Duman TT, et al. Diabetes control could through platelet‐to‐lymphocyte ratio in hemograms. Rev Da Assoc Méd Bras. 2019;65(1):38‐42. [DOI] [PubMed] [Google Scholar]
- 10.Turri G, Barresi V, Valdegamberi A, et al. Significance of preoperative inflammatory markers in prediction of prognosis in node‐negative colon cancer: correlation between neutrophil‐to‐lymphocyte ratio and poorly differentiated clusters. Biomedicines. 2021;9(1):94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Tamara MA, Milica SL, Igor D, et al. Diagnostic accuracy of platelet count and platelet indices in noninvasive assessment of fibrosis in nonalcoholic fatty liver disease patients. Can J Gastroenterol Hepatol. 2017;1:1‐5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hideki W, Tomotaka D, Katsumi M, et al. Neutrophil to lymphocyte ratio and long‐term cardiovascular outcomes in coronary artery disease patients with low high‐sensitivity C‐reactive protein level. Int Heart J. 2020;61(3):447‐453. [DOI] [PubMed] [Google Scholar]
- 13.Posul E, Yilmaz B, Aktas G, et al. Does neutrophil‐to‐lymphocyte ratio predict active ulcerative colitis? Wien Klin Wochenschr. 2015;127(7‐8):262‐265. [DOI] [PubMed] [Google Scholar]
- 14.Gulali A, Mustafa S, Oguz D, et al. Elevated neutrophil‐to‐lymphocyte ratio in the diagnosis of Hashimoto's thyroiditis. Rev Assoc Med Bras. 2017;63(12):1065‐1068. [DOI] [PubMed] [Google Scholar]
- 15.Sit M, Aktas G, Erkol H, Yaman S, Keyif F, Savli H. Neutrophil to lymphocyte ratio is useful in differentiation of malign and benign thyroid nodules. P R Health Sci J. 2019;38(1):60‐63. [PubMed] [Google Scholar]
- 16.Duman TT, Aktas G, Atak BM, et al. Neutrophil to lymphocyte ratio as an indicative of diabetic control level in type 2 diabetes mellitus. Afr Health Sci. 2019;19(1):1602‐1606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Güçlü M, Ağan AF. Relationship of peripheral blood neutrophil to lymphocyte ratio and irritable bowel syndrome. Turk J Med Sci. 2017;47:1067‐1071. [DOI] [PubMed] [Google Scholar]
- 18.Demirdal T, Sen P. The significance of neutrophil‐lymphocyte ratio, platelet‐lymphocyte ratio and lymphocyte‐monocyte ratio in predicting peripheral arterial disease, peripheral neuropathy, osteomyelitis and amputation in diabetic foot infection. Diabetes Res Clin Pract. 2018;144:118‐125. [DOI] [PubMed] [Google Scholar]
- 19.Tiainen S, Rilla K, Hämäläinen K, et al. The prognostic and predictive role of the neutrophil‐to‐lymphocyte ratio and the monocyte‐to‐lymphocyte ratio in early breast cancer, especially in the HER2+ subtype. Breast Cancer Res Treat. 2021;185(4):63‐72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kocak MZ, Aktas G, Duman TT, et al. Monocyte lymphocyte ratio As a predictor of diabetic kidney injury in type 2 diabetes mellitus; the MADKID study. J Diabetes Metab Disord. 2020;19(2):997‐1002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Huguet E, Maccallini G, Pardini P, et al. Reference values for neutrophil to lymphocyte ratio (NLR), a biomarker of cardiovascular risk, according to age and sex in a Latin American population. Curr Probl Cardiol. 2019;46(3):1‐12. [DOI] [PubMed] [Google Scholar]
- 22.Lee JS, Kim NY, Na SH, et al. Reference values of neutrophil‐lymphocyte ratio, lymphocyte‐monocyte ratio, platelet‐lymphocyte ratio, and mean platelet volume in healthy adults in South Korea. Medicine. 2018;97(26):e11138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Meng X, Chang Q, Liu Y, et al. Determinant roles of gender and age on SII, PLR, NLR, LMR and MLR and their reference intervals defining in Henan, China: a posteriori and big‐data‐based. J Clin Lab Anal. 2017;32(2):e22228. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Clinical and Laboratory Standards Institute . Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory; Approved Guideline, 3rd edn. CLSI document EP28‐A3c. Clinical and Laboratory Standards Institute. 2008. [Google Scholar]
- 25.Walsh SR, Cook EJ, Goulder F, et al. Neutrophil‐lymphocyte ratio as a prognostic factor in colorectal cancer. J Surg Oncol. 2010;91(3):181‐184. [DOI] [PubMed] [Google Scholar]
- 26.Merekoulias G, Alexopoulos EC, Belezos T, et al. Lymphocyte to monocyte ratio as a screening tool for influenza. Plos Curr. 2010;2(2):RRN1154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Smith RA, Bosonnet L, Ghaneh P, et al. The platelet‐lymphocyte ratio improves the predictive value of serum CA19‐9 levels in determining patient selection for staging laparoscopy in suspected periampullary cancer. Surgery. 2008;143(5):658‐666. [DOI] [PubMed] [Google Scholar]
- 28.Chen J, Hong D, Zhai Y, et al. Meta‐analysis of associations between neutrophil‐to‐lymphocyte ratio and prognosis of gastric cancer. World J Surg Oncol. 2015;13:122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Wang D, Yang JX, Cao DY, et al. Preoperative neutrophil‐lymphocyte and platelet‐lymphocyte ratios as independent predictors of cervical stromal involvement in surgically treated endometrioid adenocarcinoma. Onco Targets Ther. 2013;6:211‐216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Meng X, Wang W, Wei G, et al. A high or a reasonably‐reactively elevated platelet‐to‐lymphocyte ratio, which plays the role? Platelets. 2016;27:491. [DOI] [PubMed] [Google Scholar]
- 31.Dirican A, Kucukzeybek BB, Alacacioglu A, et al. Do the derived neutrophil to lymphocyte ratio and the neutrophil to lymphocyte ratio predict prognosis in breast cancer? Int J Clin Oncol. 2015;20(1):70‐81. [DOI] [PubMed] [Google Scholar]
- 32.Templeton AJ, Mcnamara MG, Seruga B, et al. Prognostic role of neutrophil‐to‐lymphocyte ratio in solid tumors: a systematic review and meta‐analysis. J Natl Cancer Inst. 2014;106(6):dju124. [DOI] [PubMed] [Google Scholar]
- 33.Azab B, Camacho‐Rivera M, Taioli E. Average values and racial differences of neutrophil lymphocyte ratio among a nationally representative sample of United States subjects. PLoS One. 2014;9:e112361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.van Werkhoven CH, Huijts SM, Bolkenbaas M, et al. The impact of age on the efficacy of 13‐valent pneumococcal conjugate vaccine in elderly. Clin Infect Dis. 2015;61:1835‐1838. [DOI] [PubMed] [Google Scholar]
- 35.Naylor K, Li G, Vallejo AN, et al. The influence of age on T cell generation and TCR diversity. J Immunol. 2005;174:7446. [DOI] [PubMed] [Google Scholar]
- 36.Li G, Yu M, Lee WW, et al. Decline in miR‐181a expression with age impairs T cell receptor sensitivity by increasing DUSP6 activity. Nat Med. 2012;18:1518‐1524. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Chen Y, Zhang Y, Zhao G, et al. Difference in leukocyte composition between women before and after menopausal age, and distinct sexual dimorphism. PLoS One. 2016;11:e0162953. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Dar HY, Singh A, Shukla P, et al. High dietary salt intake correlates with modulated Th17‐Treg cell balance resulting in enhanced bone loss and impaired bone‐microarchitecture in male mice. Sci Rep. 2018;8(1):2503. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data included in this study are available upon request by contact with the corresponding author.