Evaluation of blood neutrophil to lymphocyte and platelet to lymphocyte ratios according to plasma glucose status and serum insulin-like growth factor 1 levels in patients with acromegaly

Abstract

Introduction:

Cardiovascular, respiratory, and cerebrovascular diseases and malignancies are responsible for morbidity and mortality in acromegaly. Also these diseases are associated with chronic inflammation. The neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) are currently gaining interest as new markers of inflammation. Moreover, increased morbidity and mortality are positively correlated with the presence of diabetes and levels of insulin-like growth factor 1 (IGF-1) in acromegaly. The objective of the present study was to investigate the relationship between these markers and acromegaly according to plasma glucose status and serum IGF-1 levels.

Materials and Methods:

We retrospectively analyzed data from 61 acromegaly patients who were in a newly diagnosed period (35 male, 26 female; mean age 38.13 ± 13.98). Patients with normal plasma glucose (n = 27), impaired fasting glucose (n = 18), and diabetes mellitus (n = 16) were categorized into three different groups. NLR and PLR were compared between the study groups and were evaluated according to IGF-1 levels.

Results:

There were no statistically significant differences in NLR and PLR measurements among the study groups (p > 0.05). However, there were significant positive correlations between NLR and IGF-1 levels and between PLR and IGF-1 levels when all patients were evaluated (r = 0.334, p = 0.011 and r = 0.277, p = 0.035, respectively).

Conclusions:

This is the first report studying the relationship of NLR and PLR with glucose status and IGF-1 levels in acromegaly patients. Our study results suggest that subclinical inflammation may play a role in increased incidence of mortality and morbidity, which depends on uncontrolled IGF-1 levels in patients with acromegaly.

Keywords

Inflammation acromegaly impaired fasting glucose diabetes

Introduction

Acromegaly is a disorder characterized by hypersecretion of growth hormone (GH), multisystem-associated morbidities, and increased mortality. The presence of type 2 diabetes mellitus (DM) is detected in up to 56% of patients with acromegaly.¹ Acromegaly is associated with a 2- to 2.5-fold increase in mortality risk, mostly due to cardiovascular, cerebrovascular and respiratory complications and malignancies.^2,3

The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are simple markers of inflammation that can be easily obtained from the complete blood count (CBC) test. NLR, PLR, and other hematologic markers of inflammation have been identified as predictors and independent risk factors for several diseases.^4

–7 Additionally, these markers are predictors of prognosis in cardiovascular disease^8,9 and several malignancies.^10,11

Some previous studies have found an increase in subclinical inflammation markers, such as tumor necrosis factor α (TNF-α), interleukin 8 (IL-8), intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1), and mean platelet volume (MPV), in patients with acromegaly.^12
–14 However, there have been no studies evaluating NLR and PLR in acromegaly. NLR and PLR have also been associated with diabetes and diabetic complications.^15,16 The aim of this study was to assess NLR and PLR according to plasma glucose status and serum insulin-like growth factor 1 (IGF-1) levels in patients with newly diagnosed acromegaly.

Materials and methods

Patients

We retrospectively analyzed data of 61 acromegaly patients from a newly diagnosed period (35 male, 26 female; mean age 38.13 ± 13.98, between 18 and 78 years old). The diagnosis of acromegaly was based on the presence of classical clinical features, increased age-adjusted serum IGF-1 concentration, inability to suppress GH levels below 1 ng/mL after ingestion of 75 g glucose, and the presence of pituitary adenoma on magnetic resonance imaging.¹ The patients were separated into three groups according to their plasma glucose status. The patients with normal plasma glucose (group NPG, n = 27), impaired fasting glucose (group IFG, n = 18), and DM (group DM, n = 16) were categorized. The study protocol was approved by the local ethics committee. The requirement for patient informed consent was waived.

Demographic and laboratory data and medical history of all subjects were recorded from the electronic patient database in our hospital. Data for the active disease period contained information for newly diagnosed acromegaly patients who had not begun any treatment for acromegaly. For each patient, we evaluated simultaneous measurements of CBC test, serum IGF-1, and fasting plasma glucose (FPG) levels in the active disease period. We also recorded the data regarding the patient age, presence of hypertension, and tumor size from the medical history at the time of initial diagnosis.

Patients with known hematologic or chronic inflammatory diseases who had any pituitary hormone deficiency, patients receiving any medical treatment (except for antihypertensive and antidiabetic drugs), and patients who did not have a CBC test during active disease were excluded from the study. Also CBC investigations made during any active infection were not included in the study.

Laboratory analysis

Neutrophil (normal range, 2–8 × 10³ μL⁻¹) and lymphocyte (normal range, 1–5 × 10³ μL⁻¹) counts were routinely measured as part of the automated CBC using a hematology analyzer (Coulter Hmx; Beckman Coulter Ltd, High Wycombe, Bucks, UK). NLR and PLR were calculated as the ratio of neutrophils and platelets to lymphocytes, respectively. Serum glucose levels were measured using a hexokinase enzymatic method (Architect c8000 Chemistry Analyzer, Abbott Diagnostics, North Chicago, Illinois, USA) according to the manufacturer’s instructions. NPG was defined as FPG < 100 mg dL⁻¹; IFG was defined as FPG levels of 100–125 mg dL⁻¹; DM was established based on FPG ≥ 126 mg dL⁻¹, 2-h PG ≥ 200 mg/dL during an oral glucose tolerance test or the use of antidiabetic drugs.¹⁷ Serum GH was assessed by electrochemiluminescence immunoassay (human GH kit, Architect c8000 Chemistry Analyzer, Abbott Diagnostics). The basal GH samples were taken at 8 a.m. following an overnight fast. In terms of confirming the diagnosis for acromegaly, blood GH measurements were initially performed following an overnight fast, and then repeated every 30 min for a total of 120 min after administration of 75 g glucose.¹ Serum total IGF-1 was assessed by immunometric chemiluminescence assay (IMMULITE 2000, Siemens, Washington, DC, USA).

Statistical analysis

Descriptive statistics of studied variables (characteristics) are presented as mean and standard deviation for continuous variables and as count and percent for categorical variables. Student’s t-test was used to compare the study group means. In addition, paired t-test was used to compare before and after treatment values. Pearson correlation analysis was performed to determine linear relationships between variables. Comparisons of proportions were done by Z-test. Statistical significance levels were considered as 5%, and SPSS (version 13) statistical program was used for all statistical computations.

Results

Following retrospective screening of 77 patients with acromegaly, 16 patients were excluded, therefore 61 patients were included in the present study (35 male and 26 female patients). A detailed description of how the patients were excluded is presented in Table 1.

Table 1.

Reasons for exclusion.

1. Patients with myelodysplastic syndrome (n = 1)

2. Patients with multiple myeloma (n = 1)

3. Patients with acute renal failure (n = 1)

4. Patients with pituitary hormone deficiency (n = 6)

5. Patients for whom a CBC for the newly diagnosed period could not be obtained (n = 7)

CBC: complete blood count.

Table 2 shows the demographic and laboratory data of the study groups. There were no statistically significant differences in age, gender, presence of hypertension, tumor size, serum IGF-1 levels, NLR, and PLR between the study groups (p > 0.05).

Table 2.

Demographic and laboratory findings in the study groups.

	Active acromegaly patients (n = 61)
	Group NPG (n = 27)	Group IFG (n = 18)	Group DM (n = 16)	p Value
Age (year)^a	35.07 ± 13.33	36.67 ± 11.94	44.94 ± 15.61	0.069
Sex, male/female	12/15	13/5	10/6	0.162
Presence of HT	4/27	2/18	5/16	0.264
Tumor size (mm)^a	21.14 ± 14.61	21.93 ± 11.91	18.91 ± 10.48	0.834
IGF-1 (ng mL⁻¹)^a	776.84 ± 352.15	921.89 ± 313.68	784.00 ± 303.25	0.319
WBC (×10³ μL⁻¹)^a	6.40 ± 1.37	6.87 ± 1.99	6.99 ± 2.23	0.530
Hemoglobin (g dL⁻¹)^a	13.79 ± 1.71	14.51 ± 1.17	14.37 ± 1.50	0.245
Platelet count (×10³ μL⁻¹)^a	243.15 ± 47.25	238.17 ± 52.68	243.38 ± 54.74	0.939
Neutrophil count (×10³ μL⁻¹)^a	3.71 ± 1.05	4.00 ± 1.59	4.20 ± 1.35	0.474
Lymphocite count (×10³ μL⁻¹)^a	2.06 ± 0.52	2.09 ± 0.60	2.52 ± 1.02	0.097
NLR^a	1.91 ± 0.74	2.00 ± 0.82	1.82 ± 0.65	0.775
PLR^a	125.99 ± 42.08	119.34 ± 32.65	105.57 ± 32.97	0.229

NPG: normal plasma glucose; IFG: impaired fasting glucose; DM: diabetes mellitus; HT: hypertension; IGF-1: insulin-like growth factor 1; WBC: white blood cell counts; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; SD: standard deviation.

^aData are expressed as mean ± SD for normally distributed data.

In correlation analysis, there were significant positive correlations between serum NLR and IGF-1 levels (r = 0.334, p = 0.011; Figure 1) and PLR and serum IGF-1 levels (r = 0.277, p = 0.035; Figure 2) when all patients were evaluated.

Figure 1.

The correlation between NLR and IGF-1 levels. NLR: neutrophil-to-lymphocyte ratio; IGF-1: insulin-like growth factor 1.

Figure 2.

The correlation between PLR and IGF-1 levels. PLR: platelet-to-lymphocyte ratio; IGF-1: insulin-like growth factor 1.

Discussion

Cardiovascular, respiratory, and cerebrovascular diseases and malignancies are responsible for morbidity and mortality in acromegaly.^1
–3 On the other hand, it is now widely accepted that these diseases are associated with chronic inflammation.^10,11,18,19 Also, increased morbidity and mortality are positively correlated with the presence of diabetes and the levels of IGF-1 in acromegaly. Nevertheless, it is unclear whether this is related to increased conventional risk factors or whether it is a result of the direct effect of hypersecretion of IGF-1.^2,3 The increase in subclinical inflammation in acromegaly may contribute to the increase in the incidence of cardiovascular, respiratory, and cerebrovascular diseases and malignancies.

DM was reported in 16% of cases in patients with acromegaly, and the presence of diabetes was also identified as a predictor of mortality in a study that evaluated predictors of morbidity and mortality in acromegaly.³ We found a 26% rate of diabetes, consistent with the literature,¹ in the patients with newly diagnosed acromegaly. There are conflicting results on the relationship between DM and NLR. Otherwise, data on the relationship between DM and PLR are very limited. Shiny et al.¹⁵ found that NLR was significantly higher in diabetic patients than in the controls and demonstrated a significant positive correlation of NLR with FPG levels. In another study, Akbas et al.¹⁶ reported that the degree of albuminuria in diabetic nephropathy was associated with NLR and PLR. In contrast, Lorenzo et al.²⁰ found no relationship between the presence of DM and NLR. In our study, NLR and PLR were not statistically different between the NPG, IFG, and DM groups in patients with acromegaly. The results of this study support the conclusion that NLR and PLR measurements are not useful markers for illustrating subclinical inflammation due to the presence of DM and IFG in acromegaly.

There are limited data on the relationship between acromegaly and chronic inflammation in the literature. Unübol et al.¹² found that MPV was significantly higher in patients with acromegaly than in the controls and demonstrated a significant positive correlation of MPV with IGF-1 levels. Topaloglu et al.¹³ demonstrated that ICAM-1 and VCAM-1 were significantly higher in patients with acromegaly than in controls. In addition, atherosclerotic risk markers such as aortic pulse wave velocity and epicardial fat thickness were found to be significantly higher in patients with acromegaly in these studies.^12,13 In another study, Arikan et al.¹⁴ reported that TNF-α and IL-8 were significantly higher in patients with acromegaly compared with the controls. To the best of our knowledge, there are no data on the interaction between NLR or PLR and IGF-1 levels in patients with acromegaly. Therefore, our present study is the first study evaluating the correlation of NLR and PLR with IGF-1 levels in patients with acromegaly. A significant positive correlation was found between NLR and IGF-1 levels and PLR and IGF-1 levels in our study. Our results suggest that long-term exposure to high levels of IGF-1 may lead to increased cardiovascular risk based on an increase in atherosclerotic risk markers such as NLR and PLR.^8,9 In addition, the present study results support the hypothesis that increases in subclinical inflammation due to uncontrolled disease may contribute to increased morbidity and mortality in patients with acromegaly.

There are some limitations to our study: body mass index, blood pressure, and blood lipid measurements were not assessed to compare the study groups due to the retrospective nature of our study. It is possible that changes of these parameters may affect NLR and PLR measurements.

In conclusion, evaluation of inflammation markers such as NLR and PLR according to serum IGF-1 levels in patients with newly diagnosed acromegaly showed a significant positive correlation between NLR and IGF-1 levels and PLR and IGF-1 levels in our study. Based on these data, we think that subclinical inflammation should be considered in management of acromegaly since subclinical inflammation may play a role in increased incidence of mortality and morbidity, which depends on the uncontrolled IGF-1 levels in acromegaly.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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