Dermatology: Practical and Conceptual Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 1 The Use of New Hematological Markers in the Diagnosis of Alopecia Areata Gulhan Aksoy Sarac1, Onur Acar 2, Tufan Nayır3, Pınar Hararcı Yıldırım1, Didem Dinçer Rota1 1 Ufuk University Faculty of Medicine Department of Dermatology, Ankara, Turkey 2 Ağrı Provincial Health Directorate, Republic of Turkey, Ministry of Health, Ağrı, Turkey 3 Turkish Ministry of Health, Ankara, Turkey Key words: alopecia areata, monocyte lymphocyte ratio (MLR), ROC analysis, marker Citation: Aksoy Sarac G, Acar O, Nayir T, Hararcı Yıldırım P, Dinçer Rota D. The Use of New Hematological Markers in the Diagnosis of Alopecia Areata. Dermatol Pract Concept. 2023;13(2):e2023118. DOI: https://doi.org/10.5826/dpc.1302a118 Accepted: November 16, 2022; Published: April 2023 Copyright: ©2023 Aksoy Sarac et al. This is an open-access article distributed under the terms of the Creative Commons Attribution- NonCommercial License (BY-NC-4.0), https://creativecommons.org/licenses/by-nc/4.0/, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original authors and source are credited. Funding: None. Competing interests: None. Authorship: All authors have contributed significantly to this publication. Corresponding author: Onur Acar, MD, Ağrı Provincial Health Directorate, Republic of Turkey, Ministry of Health, Ağrı, Turkey. Tel: +90 5062341595 ORCID ID: https://orcid.org/0000-0003-3561-3192 E-mail: dronuracar@yandex.com Introduction: Alopecia areata (AA) is a non-cicatricial inflammatory and autoimmune hair loss disease. In recent studies, it has been reported that hematological parameters can be used as oxidative stress markers in the diagnosis of many inflammatory diseases due to their low cost and widespread use. Objectives: In this study, it was aimed to reveal the significant cut-off points of hematological inflam- matory markers in AA that can guide clinicians in clinical practice and determine how many times they increase the risk of disease. Methods: The present study is retrospective case-control type. Seventy patients with AA and seventy healthy controls were included in the study. The hematological parameters in both groups were eval- uated retrospectively. Results: Hemoglobulin, monocyte, platelet, monocyte high-density lipoprotein cholesterol (HDL-C) ratio (MHR), monocyte lymphocyte ratio (MLR), platelet lymphocyte ratio (PLR) were high in pa- tients with AA, while the number of lymphocytes was low. In ROC analysis, the optimal cut-off values for the diagnosis of AA were as follows: MLR 0.216, MHR 0.010, and PLR 111.715. In regression analysis, being above the following values of MLR 0.216, MHR 0.010, and PLR 111.715 increased the risk of developing AA by 6.3, 3.8, and 2.7 times, respectively. Conclusions: It was seen that MHR and PLR, especially MLR, can significantly increase the risk of developing the disease in AA and can also be used as diagnostic markers. ABSTRACT 2 Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 Introduction Alopecia areata (AA) is an inflammatory and autoimmune dis- ease clinically ranging from small, round, well-defined hair loss patch to its complete disappearance on the body and scalp [1]. The incidence of AA, which is a non-scarring disease in which the hair follicle is preserved, is 2% [2]. The mean age at di- agnosis of AA, which can be seen in all age groups without any difference between genders, is 30-39 years [3]. The etio- pathogenesis of AA has not yet been fully elucidated. Although genetics and immunity are seen as the factors that cause the most disease, many factors such as melanocyte anomalies, ke- ratinocyte degeneration, neurological factors, and emotional stress have also been blamed [4-6]. The disease develops as a result of T cell-mediated cytotoxic damage to the hair follicle. Since IL-17A, IL17F, IL21, IL22, IL6, and TNF alpha levels are elevated in AA patients, these cytokines are thought to play a role in the pathogenesis [7]. In recent studies, it has been discussed that the whole blood parameters can be used as an oxidative stress and diagnostic marker in many diseases associated with inflammatory processes. In clinical practice, these markers are important for objective and quantitative evaluation of the disease process and response to treatment, as well as the diagnosis [8]. Red-cell distribution width (RDW), monocyte high-density lipoprotein ratio (MHR), monocyte lymphocyte ratio (MLR), platelet lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR) and mean platelet volume (MPV) are investigated in many dermatological diseases such as psoriasis, rheumatological diseases of dermatology, cutane- ous vasculitis, atopic eczema, pityriasis rosea, Behçet disease, recurrent aphthous stomatitis, and pemphigus vulgaris [9-12]. Although there are many studies on these dermatolog- ical diseases in the literature, studies investigating the rela- tionship between AA and these inflammatory markers are limited. In addition, no studies have been found showing at which cutoff point these significant inflammatory markers start to be significant and how many times they increase the risk of developing the disease. Objectives In this study, it was aimed to compare the levels of RDW, MPV, MHR, MLR, NLR, PLR between patients with AA and healthy controls, and to reveal the significant cut-off points that can guide clinicians in clinical practice and deter- mine how many times they increase the risk. Methods Study Design and Patient Selection This study was conducted as a retrospective case-control study with patients with AA who applied to the dermatology outpatient clinic between June 2020 and June 2021 and healthy controls with no previous history of AA. Ethics com- mittee approval of the study was received from Local Ethics Committee. Demographic characteristics and laboratory val- ues were obtained from the database of the health center for both the case and control groups. Demographic data include age, gender, duration of illness (months). Laboratory data include the levels of white blood cell (WBC: K/µL), hemo- globin (Hb: g/dL), platelets (PLT: K/µL), RDW, MPV (K/µL), neutrophils (NE: K/µL), lymphocytes (LY: K/µL), monocytes (MN: K/µL), high-density lipoprotein cholesterol (HDL-C: mg/dL), NLR, PLR, MHR, and MLR. Disease severity in patients with AA was evaluated ac- cording to the classification made by Kavak et al and clas- sified as mild (3 or fewer patches with a diameter of 3 cm or less, or involvement limited to eyebrows and eyelashes), moderate (more than 3 alopecic patches or involvement of more than 3 cm without alopecia totalis or alopecia univer- salis), severe (alopecia totalis or alopecia universalis) [13]. Patients with AA who had an active infection, malnutri- tion, anemia, immunodeficiency, chronic inflammatory skin disease, rheumatological disease, heart disease, and drug use were excluded from the study. The laboratory values of the patients with AA at the application date were included. Laboratory values of the patients with AA regarding the follow-up and treatment couldn’t be included because they were absent in the hospital record. Healthy controls were comprised of individuals without active infection, systemic or dermatological disease, and drug use. Both of two groups don’t include members who got Covid-19 infection in recent six months. Statistical Analysis The data of the study were analyzed using SPSS 20 (Statis- tical Package for Social Sciences). Descriptive statistics were given as numbers, percentages, mean and standard deviation. The relationship between continuous variables was evalu- ated with the Pearson correlation test. The t-test was used for continuous variables between two independent groups. Significant cut-off points were determined using ROC ( Receiver operating characteristic) analysis for markers with significant differences between the two groups in the t-test. The odds ratios of the cut points that were found to be caus- ing high activity AA were analyzed using the logistic regres- sion model. All findings were evaluated at a 95% confidence interval (CI) and 5% significance level (P). Results Seventy patients with AA and 70 healthy controls were in- cluded in this study. The mean age was 31.57 ± 9.92 years in the patient group and 31.51 ± 7.37 years in the control group. Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 3 There was no significant difference between the groups ac- cording to age (P = 0.969). The mean age of patients with AA was 29.78 ± 8.58 years in men and 33.47 ± 10.98 years in women, and the difference was not statistically significant. The gender distribution was the same in the patient and con- trol groups, with 36 (51.4%) men and 34 (48.6%) women. While the mean duration of disease was 1.22 ± 2.21 months in men and 3.05 ± 5.43 months in women, it was 2.11 ± 4.17 months in the whole AA group, and there was no sig- nificant difference between the genders. Of the patients with AA, 41 (58.6%) had mild, 12 (17.1%) had moderate, and 17 (24.3%) had severe alopecia. The laboratory findings of the patient and control groups are shown in Table 1. The mean of Hb (P = 0.004), MN (P < 0.001), PLT (P = 0.042), MHR (P < 0.001), MLR (P < 0.001) and PLR (P < 0.001) was higher in patients with AA com- pared to the control group, while the number of lymphocytes was lower (P = 0.005). Table 2 shows the effect of laboratory parameters on disease duration in patients with AA. While the increase in HDL-C (r = 0.324, P = 0.013), MPV (r = 0.239, P = 0.046) and PLR (r = 0.297, P = 0.013) in patients with AA increased the duration of the disease (positive correlation); the increase in Hb (r = -0.301, P = 0.011), LY (r = -0.269, P = 0.024) and MHR (r = -0.289, P = 0.015) was a factor reducing disease duration (negative correlation). When classified according to disease severity, for those who have severe AA disease the increase in HDL-C (r = 0.620, p = 0.008) led to increasing the duration of the disease (positive correlation). Also the increase in Hb (r = -0.505, P = 0.039) led to decreasing the duration of the disease (negative correlation). While there was a positive correlation between disease severity and RDW (r = 0.242, P = 0.044) and PLR (r = 0.315, P = 0.008); a negative correlation between WBC (r = -0.236, P = 0.049), Hb (r = -0.285, P = 0.017), MN (r = -0.270, P = 0.024) and MHR (r = -0.356, P = 0.002) was present. There was a pos- itive, weak and very significant correlation between disease duration and disease severity in patients with AA (r = 0.494, P < 0.001). Table 3 and Figure 1 show the optimal value of labo- ratory parameters to diagnose AA using ROC analysis. In ROC analysis, it was found that MLR (P < 0.001), MHR (P < 0.001) and PLR (P = 0.001) values could be used as a diagnostic test in AA. The cut-off values of MLR 0.216 value (AUC = 0.873, good usefulness, 85.7% sensitivity and 70% specificity), MHR 0.010 value (AUC = 0.759, moderate useful, 82.9% sensitivity and 58.6% specificity), PLR 111.715 value (AUC = 0.727, moderate useful, 75.7% sensitivity and 58.6% specificity) were found to be useful as diagnostic tests. Table 4 shows how many times the parameters found to be significant in diagnosing AA in the ROC analysis increase Table 1. Comparison of laboratory values of patients and controls using t-test. Group N Mean SD P value WBC Patient 70 7.26 1.80 0.115 Control 70 7.67 1.16 Hb (g/dL) Patient 70 14.91 1.65 0.004 Control 70 14.15 1.37 RDW (%) Patient 70 11.95 1.67 0.026 Control 70 12.44 0.76 MN(K/µL) Patient 70 0.57 0.17 <0.001 Control 70 0.38 0.66 HDL-C (mg/dL) Patient 70 52.49 10.83 0.252 Control 70 50.31 11.62 NE (K/µL) Patient 70 4.27 1.26 0.062 Control 70 4.63 0.95 PLT (K/µL) Patient 70 248.81 57.91 0.042 Control 70 229.87 50.94 LY (K/µL) Patient 70 2.21 0.80 0.005 Control 70 2.56 0.62 MPV (K/µL) Patient 70 8.06 1.22 0.252 Control 70 8.26 0.76 MHR Patient 70 0.011 0.004 <0.001 Control 70 0.007 0.001 MLR Patient 70 0.281 0.111 <0.001 Control 70 0.158 0.050 NLR Patient 70 2.140 0.986 0.127 Control 70 1.921 0.674 PLR Patient 70 121.461 34.492 <0.001 Control 70 94.805 29.309 Hb = Hemoglobin; HDL-C = high-density lipoprotein cholesterol; LY = lymphocytes; MN = monocytes; MHR = monocyte high-density lipoprotein cholesterol ratio; MLR = monocyte lymphocyte ratio; MPV = mean platelet volume; NE = neutrophils;NLR = neutrophil lymphocyte ratio; PLR = platelet lymphocyte ratio; PLT = platelets; RDW = red-cell distribution width; WBC = white blood cell. 4 Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 Table 2. Correlation analysis between disease duration and Alopecia Areata group parameters. Variables Disease Duration (months) Disease Severity Mild&Moderate Patients (N = 53) Severe Patients (N = 17) All Patients (N = 70) r P r P r P r P WBC 0.054 0.703 -0.223 0.390 -0.205 0.089 -0.236 0.049 Hb -0.010 0.946 -0.505 0.039 -0.301 0.011 -0.285 0.017 RDW (%) -0.128 0.361 0.201 0.440 0.113 0.351 0.242 0.044 MN (K/µL) 0.012 0.931 -0.179 0.492 -0.230 0.055 -0.270 0.024 HDL-C (mg/dL) 0.117 0.405 0.620 0.008 0.324 0.013 0.227 0.059 NE (K/µL) 0.024 0.865 0.375 0.138 0.193 0.110 0.083 0.496 PLT (K/µL) 0.304 0.027 -0.264 0.306 -0.065 0.593 0.044 0.715 LY (K/µL) -0.013 0.926 -0.482 0.050 -0.269 0.024 -0.182 0.132 MPV (K/µL) -0.150 0.284 0.312 0.222 0.239 0.046 0.195 0.106 MHR -0.079 0.574 -0.355 0.161 -0.289 0.015 -0.356 0.002 MLR -0.002 0.989 0.219 0.399 0.048 0.691 -0.064 0.601 NLR 0.024 0.865 0.375 0.138 0.193 0.110 0.083 0.496 PLR 0.167 0.231 0.366 0.149 0.297 0.013 0.315 0.008 Hb = Hemoglobin; HDL-C = high-density lipoprotein cholesterol; LY = lymphocytes; MN = monocytes; MHR = monocyte high-density lipo- protein cholesterol ratio; MLR = monocyte lymphocyte ratio; MPV = mean platelet volume; NE = neutrophils; NLR = neutrophil lymphocyte ratio; PLR = platelet lymphocyte ratio; PLT = platelets; RDW = red-cell distribution width; WBC = white blood cell. Table 3. Findings of the ROC analysis. Variables AUC (p value) 95% CI CO Sen (%) Spe (%) PLR NLR MLR 0.873 (<0.001) 0.815- 0.931 0.216 85.7 70.0 2.85 0.20 MHR 0.759 (<0.001) 0.679- 0.840 0.010 82.9 58.6 2 0.29 PLR 0.727 (<0.001) 0.643- 0.810 111.715 75.7 58.6 1.82 0.41 AUC = Area under curve; CI = confidence interval; CO = cutoff value; MHR = monocyte high-density lipoprotein cholesterol ratio; MLR = monocyte lymphocyte ratio; NLR = negative likelihood ratio; PLR = platelet lymphocyte ratio; PLR = positive likelihood ratio; ROC = receiver operating characteristic; Sen = sensitivity; Spe = specifity. the probability of catching AA at the determined cut-off val- ues in the established logistic regression model. According to the logistic regression analysis result, an MLR value of 0.216 and above increases the risk of developing AA by 6.30 times (95% CI: 2.41-16.45 P < 0.001), an MHR value of 0.010 and above by 3.87 times (95% CI: 1.54-9.73 P = 0.004) and a PLR value of 111.715 and above by 2.76 times (95% CI:1.06-7.17 P = 0.037). Conclusions In this study, the relationship between complete blood count and biochemical parameters, which can be easily used by cli- nicians in routine, and AA disease is shown in detail. There is a limited number of studies on the subject in the literature, and it has not been investigated yet at what values hema- tological and inflammatory markers are diagnostic for the disease and how much they increase the risk of disease in these diagnostic values. This study is a pioneering study in terms of answering these questions that are not yet available in the literature. AA is a non-cicatricial, autoimmune, inflammatory hair loss disease that has many factors in its etiology and has various clinical manifestations [1]. There is no significant difference between genders in terms of incidence. However, it was emphasized that the most common age of onset of the disease was between 50-59 years of age in women and 30-39 years in men and that the average age of diagnosis was older in women than in men (36.2 versus31.5 years) [14]. In this study, the mean age of patients with AA was 29.78 ± 8.58 years in men and 33.47 ± 10.98 years in women, which is consistent with the literature. Whole blood parameters are a low-cost test and are widely used by clinicians. It provides important informa- tion about systemic inflammation. In this study, Hb, MN, PLT, MHR, MLR, and PLR values were higher in patients Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 5 and HDL-C, MPV, and PLR, and a negative correlation between Hb, LY, and MHR. But, when correlation analy- sis included only severe AA patients, there was a positive with AA compared to the control group, while the num- ber of lymphocytes was found to be lower. In addition, there was a positive correlation between AA durations Table 4. Logistic regression results. Variables OR 95% CI P value MLR 0.216 and above 6.309 2.419- 16.456 <0.001 Below 0.216 1 (reference) MHR 0.010 and above 3.879 1.546- 9.732 0.004 Below 0.010 1 (reference) PLR 111.715 and above 2.761 1.062- 7.174 0.037 Below 111.715 1 (reference) CI = confidence interval; MHR = monocyte high-density lipoprotein cholesterol ratio; MLR = monocyte lymphocyte ratio; PLR = platelet lymphocyte ratio; OR = odds ratio. ROC CURVE SE N SI TI V IT Y 1 - SPECIFICITY DIAGONAL SEGMENTS ARE PRODUCED BY TIES. 0,0 0,0 0,2 0,4 0,6 0,8 1,0 0,2 0,4 0,6 0,8 1,0 SOURCE OF THE CURVE MLR MHR PLR REFERENCE LINE Figure 1. ROC Curve. MHR: Monocyte high-density lipoprotein cholesterol ratio MLR Monocyte lymphocyte ratio PLR: Platelet lymphocyte ratio 6 Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 2. Pratt CH, King LE, Messenger AG, Christiano AM, Sund- berg JP. Alopecia areata. Nat Rev Dis Primer. 2017;3:17011. DOI:10.1038/nrdp.2017.11. PMID: 28300084. PMCID: PMC5573125. 3. Safavi KH, Muller SA, Suman VJ, Moshell AN, Melton LJ. In- cidence of alopecia areata in Olmsted County, Minnesota, 1975 through 1989. Mayo Clin Proc. 1995;70(7):628-633. DOI:10.4065/70.7.628. PMID: 7791384. 4. Darwin E, Hirt PA, Fertig R, Doliner B, Delcanto G, Jimenez JJ. Alopecia Areata: Review of Epidemiology, Clinical Fea- tures, Pathogenesis, and New Treatment Options. Int J Trichol- ogy. 2018;10(2):51-60. DOI:10.4103/ijt.ijt_99_17. PMID: 29769777. PMCID: PMC5939003. 5. Gilhar A, Etzioni A, Paus R. Alopecia areata. N Engl J Med. 2012;366(16):1515-1525. DOI:10.1056/NEJMra1103442. PMID: 22512484. 6. Simakou T, Butcher JP, Reid S, Henriquez FL. Alopecia areata: A multifactorial autoimmune condition. J Autoimmun. 2019;98:74-85. DOI: 10.1016/j.jaut.2018.12.001. PMID: 30558963. 7. Islam N, Leung PSC, Huntley AC, Gershwin ME. The autoimmune basis of alopecia areata: a comprehensive review. Autoimmun Rev. 2015;14(2):81-89. DOI: 10.1016/j.autrev.2014.10.014. PMID: 25315746. 8. Rashmi R, Rao KSJ, Basavaraj KH. A comprehensive review of biomarkers in psoriasis. Clin Exp Dermatol. 2009;34(6):658-663. DOI:10.1111/j.1365-2230.2009.03410.x. PMID: 19558584. 9. Asahina A, Kubo N, Umezawa Y, Honda H, Yanaba K, Nakagawa H. Neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and mean platelet volume in Japanese patients with psoriasis and psoriatic arthritis: Response to therapy with biologics. J Derma- tol. 2017;44(10):1112-1121. DOI:10.1111/1346-8138.13875. PMID: 28493493. 10. Kridin K, Shihade W, Zelber-Sagi S. Mean Platelet Volume in Pemphigus Vulgaris. Angiology. 2018;69(4):303-307. DOI:10.1177/0003319717718329. KPMID: 28681645. 11. Pancar GS, Eyupoglu O. Red Cell Distribution Width and Mean Platelet Volume in Patients With Pityriasis Rosea. J Clin Med Res. 2016;8(6):445-448. DOI:10.14740/jocmr2535w. PMID: 27222672. PMCID: PMC4852777. 12. Turkmen D, Altunisik N, Sener S. Investigation of monocyte HDL ratio as an indicator of inflammation and complete blood count parameters in patients with acne vulgaris. Int J Clin Pract. 2020;74(12):e13639. DOI:10.1111/ijcp.13639. PMID: 32741037. 13. Kavak A, Baykal C, Ozarmağan G, Akar U. HLA in alopecia areata. Int J Dermatol. 2000;39(8):589-592. DOI:10.1046/ j.1365-4362.2000.00921.x. PMID: 10971726. 14. Mirzoyev SA, Schrum AG, Davis MDP, Torgerson RR. Lifetime incidence risk of alopecia areata estimated at 2.1% by Roch- ester Epidemiology Project, 1990-2009. J Invest Dermatol. 2014;134(4):1141-1142. DOI:10.1038/jid.2013.464. PMID: 2420223. PMCID: PMC3961558. 15. Ozlu E, Karadag AS, Toprak AE, et al. Evaluation of Cardiovas- cular Risk Factors, Haematological and Biochemical Parameters, and Serum Endocan Levels in Patients with Lichen Planus. Derma- tol Basel Switz. 2016;232(4):438-443. doi:10.1159/000447587 OPMID: 27508489. 16. Sirin MC, Korkmaz S, Erturan I, et al. Evaluation of monocyte to HDL cholesterol ratio and other inflammatory markers in patients with psoriasis. An Bras Dermatol. 2020;95(5):575-582. correlation between AA durations and HDL-C, and a neg- ative correlation between AA durations and Hb. In many studies in the literature, the relationship between derma- tological diseases and these hematological markers has been investigated. In a study conducted by Ozlu et al WBC and MHR were found to be high and MPV was found to be low in patients with lichen planus [15]. It was shown that patients with psoriasis have higher levels of MHR and NLR compared to healthy controls [16]. Similarly, while there was a positive relationship between MHR, NLR, PLR, and MLR and disease duration in psoriasis, it has been reported that there was a negative relation- ship between NLR, PLR, and disease duration in vitiligo [17,18]. However, there are also studies stating that there is no significant relationship between AA and these hema- tological markers [19]. Monocytes are one of the cornerstones of the immune system that take on important tasks. They play a role in inflammatory processes in many diseases involving many systems such as rheumatologic, endocrine, dermatological, oncologic, and cardiovascular [20-23]. In this study, MLR, MHR, and PLR values were found to be good and moder- ately useful diagnostic tests for AA. The values that are above 0.216 for MLR, 0.010 for MHR, and 111.715 for PLR as cut-off increase the risk of alopecia areata by 6.3, 3.8, and 2.7 times, respectively. In a study by Yayla et al.; It has been reported that high NLR increases the risk of systemic sclero- sis by 3.49 times [24]. In the study by Cosansu et al, it was stated that the MLR value of 0.192 was a moderately useful test in the diagnosis of patients with psoriasis, and similarly, MHR and MLR values were significant markers in the diag- nosis of vitiligo [25,18]. There are some limitations to this study. Firstly, since it was in a retrospective style, the laboratory values of the patients at the time of application were included and no evaluation could be made regarding the follow-up data. Sec- ondly, the fact that it is a single-center study, and third, the relatively small number of patients and controls may cause differences in findings. Fourth, it may assess as another lim- itation that The Severity of Alopecia Tool score wasn’t used when classifying the severity. In conclusion, in this study, MHR and PLR values, espe- cially MLR, were shown to be low-cost and fast-accessible oxidative stress markers in the diagnosis of AA. It is believed that our results may provide important information for fur- ther studies on the use of hematological markers in AA. References 1. Strazzulla LC, Wang EHC, Avila L, et al. Alopecia areata: Disease characteristics, clinical evaluation, and new perspec- tives on pathogenesis. J Am Acad Dermatol. 2018;78(1):1-12. DOI:10.1016/j.jaad.2017.04.1141. PMID: 29241771. Original Article | Dermatol Pract Concept. 2023;13(2):e2023118 7 DOI:10.1016/j.abd.2020.02.008. PMID: 32711928. PMCID: PMC7562997. 17. Aktaş Karabay E, Demir D, Aksu Çerman A. Evaluation of mono- cyte to high-density lipoprotein ratio, lymphocytes, monocytes, and platelets in psoriasis. An Bras Dermatol. 2020;95(1):40-45. DOI:10.1016/j.abd.2019.05.002. PMID: 31889591. PMCID: PMC7058861. 18. Demirbaş A, Elmas ÖF, Atasoy M, Türsen Ü, Lotti T. Can monocyte to HDL cholesterol ratio and monocyte to lympho- cyte ratio be markers for inflammation and oxidative stress in patients with vitiligo? A preliminary study. Arch Dermatol Res. 2021;313(6):491-498. DOI:10.1007/s00403-020-02129-3. PMID: 32816078. 19. İslamoğlu ZGK, Demirbaş A. Evaluation of complete blood cell and inflammatory parameters in patients with alopecia areata: Their association with disease severity. J Cosmet Derma- tol. 2020;19(5):1239-1245. DOI:10.1111/jocd.13131. PMID: 31502748. 20. Ji H, Li Y, Fan Z, et al. Monocyte/lymphocyte ratio predicts the severity of coronary artery disease: a syntax score assessment. BMC Cardiovasc Disord. 2017;17(1):90. DOI:10.1186/s12872- 017-0507-4. JPMID: 28359298. PMCID: PMC5374608. 21. Kang Y, Zhu X, Lin Z, et al. Compare the Diagnostic and Prognostic Value of MLR, NLR and PLR in CRC Patients. Clin Lab. 2021;67(9). DOI:10.7754/Clin.Lab.2021.201130. PMID: 34542964. 22. Yue S, Zhang J, Wu J, Teng W, Liu L, Chen L. Use of the Mono- cyte-to-Lymphocyte Ratio to Predict Diabetic Retinopathy. Int J Environ Res Public Health. 2015;12(8):10009-10019. DOI:10.3390/ijerph120810009. PMID: 26308022. PMCID: PMC4555325. 23. Zawada AM, Rogacev KS, Rotter B, et al. SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset. Blood. 2011;118(12):e50-61. DOI:10.1182/blood-2011-01-326827. PMID: 21803849. 24. Yayla ME, İlgen U, Okatan İE, et al. Association of simple he- matological parameters with disease manifestations, activity, and severity in patients with systemic sclerosis. Clin Rheumatol. 2020;39(1):77-83. DOI:10.1007/s10067-019-04685-0. PMID: 31317426. 25. Cosansu NC, Dikicier BS, Yaldiz M, Solak B. Is There Any Asso- ciation Between the Monocyte/Lymphocyte Ratio and the Pres- ence and Severity of the Disease in Patients with Psoriasis? Sak Tıp Derg. 2020;10(3):430-436. DOI: 10.31832/smj.719980.