Platelet Activation and Inflammation in Patients with Papillary Thyroid Cancer

Background: The primary endpoint was to analyze the preoperatory inflammatory markers and platelet indices in papillary thyroid cancer (PTC) patients compared with patients with benign thyroid pathology. The secondary endpoints were to analyze the relationship between these markers and the pathological features of PTC and to compare their pre- and postoperative levels in PTC patients. Methods: In this retrospective case-control study, we analyzed the files of 1183 patients submitted to thyroidectomy between January 2012 and December 2018. A total of 234 patients with PTC (mean age 51.54 ± 13.10 years, 84.6% females) were compared with an age-, gender- and BMI-matched control group of 108 patients with histologic benign thyroid disorders. Results: PTC patients had higher platelet count (PLT) (p = 0.011), plateletcrit (PCT) (p = 0.006), neutrophil (p = 0.022) and fibrinogen (p = 0.005) levels. Subgroup analysis showed that PTC females had higher PLT (p = 0.006), PCT (p < 0.001) and erythrocyte sedimentation rate (ESR) (p = 0.005), while males had higher neutrophil (p = 0.040) levels. Papillary thyroid cancer patients under 55 years had higher PLT (p < 0.001) and PCT (p = 0.010), while patients over 55 years had higher mean platelet volume (p = 0.032), neutrophil-to-lymphocyte ratio (p = 0.013), ESR (p = 0.005) and fibrinogen (p = 0.019) levels. Preoperative values for platelet indices and inflammatory markers were similar to the postoperative determinations in PTC patients. Fibrinogen (AUROC = 0.602, p = 0.02; cut-off = 327.5 mg/dL, Se = 53.8%, Sp = 62.9%) and PLT (AUROC = 0.584, p = 0.012; cut-off = 223.5 × 103/mm3, Se = 73.1%, Sp = 42.6%) were independent predictors of the presence of PTC. Conclusions: Our data show that fibrinogen and platelet count could be promising, inexpensive, independent predictors for the presence of PTC when compared with benign thyroid disorders.


Introduction
Thyroid carcinomas, the most common type of endocrine malignancies, are 2-4 times more common in women than men, and their incidence has rapidly increased during the past decades, mostly due to increased incidence of papillary thyroid carcinomas (PTCs) [1]. The prevalence of thyroid nodules ranges from 5% by palpation to 19-68% by high resolution ultrasonography [2]. Ultrasonography and fine-needle aspiration biopsy play important roles in the diagnosis and follow-up of thyroid nodules. In addition, a variety of PTC and to compare pre-and postoperative inflammatory markers and platelet indices in PTC patients.

Patients and Study Protocol
We conducted a hospital-based retrospective case-control study using the data from 1183 files of patients who underwent total thyroidectomy or lobectomy in our surgery department between January 2012 and December 2018. A total of 265 (22.40%) of these patients were diagnosed with thyroid cancer. The study population included 249 (93.96%) patients with histologic differentiated thyroid cancer (DTC), 234 (88.3%) papillary thyroid carcinomas and 15 (5.66%) follicular thyroid carcinomas (FTC). Exclusion criteria were poorly differentiated thyroid cancers (4, 1.51%), anaplastic cancers (4, 1.51%), medullary thyroid carcinomas (MTC) (8,3.02%) and patients with histologic benign thyroid pathology (918). The controls were selected from the same cohort of 1183 patients and included the first 108 age-, gender-and BMI-matched subjects with histologic benign thyroid pathology: multinodular goiter (84), follicular adenoma (12) and Graves' disease (12) (Figure 1). Due to the retrospective nature of the study and the recent change in nomenclature that saw EFVPTC (encapsulated follicular variant of papillary thyroid carcinoma) redefined as NIFTP (noninvasive follicular thyroid neoplasm with papillary-like nuclear features) [23], we did not include patients diagnosed with NIFTP after 2016 and did not analyze patients based on the PTC histological subtype.

Data Presentation and Statistical Analyses
The distribution of the continuous quantitative variables was evaluated by the Shapiro-Wilk normality test. Descriptive data are presented as means ± SD, medians with interquartile range (IQR) or percentage. Between groups comparisons were carried out using parametric (independent sample t-test, t-test for pairwise samples, one-way analysis of variance (ANOVA) for more than two independent groups) or nonparametric (Mann-Whitney U-test, Kruskal-Wallis one-way ANOVA, Kolmogorov-Smirnov) tests, as appropriate. Chi-square test and Fisher's exact test were used to compare proportions in large, respectively small groups. Relations between continuous variables were analyzed using Pearson's correlation parametric coefficient or Spearman's rho nonparametric correlation coefficient. Linear regression analyses and logistic regression analyses were used to identify the influence of inflammatory markers and platelet indices in PTC patients. Results are presented as odds ratio (OR) for the predictor variable, 95% confidence interval (CI) and p value for each variable assumed as a predictor. The overall validity of the model was measured using area under the receiver operating characteristic curve (AUROC) with 95% CI.  For all the 249 DTC patients, we recorded the following preoperative clinical and paraclinical data: age, gender, body mass index (BMI), fibrinogen, erythrocyte sedimentation rate (ESR), platelet count, MPV, PDW, PCT, TSH, FT4, anti-thyroid peroxidase antibodies (TPOAb), anti-thyroglobulin antibodies (ATA), anti-TSH receptor antibodies (TRAb) and pathological report data describing tumor features that included pathological variant of DTC-follicular and papillary carcinoma subtypes, cancer size, pTNM stage [21], multifocality, vascular invasion, capsular invasion, extracapsular extension, locoregional lymph node involvement and presence of thyroiditis. In addition, we calculated the neutrophil-tolymphocyte (NLR) and platelet-to-lymphocyte (PLR) ratios as follows: NLR was calculated as the absolute neutrophil count divided by the absolute lymphocyte count, and PLR was calculated as the absolute platelet count divided by the absolute lymphocyte count, based on the preoperative blood count. For 63 PTC patients, the following postoperative data were also available to be recorded at a mean time of 3 months after surgery at the first follow-up visit: ESR, platelet count, MPV, PDW, PCT. For the 108 patients with benign thyroid pathology who were included in the control group, preoperative data were col-lected: age, gender, BMI, fibrinogen, ESR, platelet count, MPV, PDW, PCT, NLR, PLR and pathological report diagnosis.

Data Presentation and Statistical Analyses
The distribution of the continuous quantitative variables was evaluated by the Shapiro-Wilk normality test. Descriptive data are presented as means ± SD, medians with interquartile range (IQR) or percentage. Between groups comparisons were carried out using parametric (independent sample t-test, t-test for pairwise samples, one-way analysis of variance (ANOVA) for more than two independent groups) or nonparametric (Mann-Whitney U-test, Kruskal-Wallis one-way ANOVA, Kolmogorov-Smirnov) tests, as appropriate. Chisquare test and Fisher's exact test were used to compare proportions in large, respectively small groups. Relations between continuous variables were analyzed using Pearson's correlation parametric coefficient or Spearman's rho nonparametric correlation coefficient. Linear regression analyses and logistic regression analyses were used to identify the influence of inflammatory markers and platelet indices in PTC patients. Results are presented as odds ratio (OR) for the predictor variable, 95% confidence interval (CI) and p value for each variable assumed as a predictor. The overall validity of the model was measured using area under the receiver operating characteristic curve (AUROC) with 95% CI. The
Univariate comparative analysis of the inflammatory markers and platelet indices according to weight categories in PTC patients did not disclose any significant differences (data not shown).
Multivariate binary logistic regression analysis was performed to ascertain the effects of preoperative platelet indices and inflammatory markers on the likelihood that the patients have PTC. The logistic regression model was statistically significant, χ 2 (6) = 13.559, p = 0.035. The model explained 10      Abbreviations: BMI, body mass index; ESR, erythrocyte sedimentation rate; IQR, interquartile range; MPV, mean platelet volume; NLR, neutrophil-to-lymphocyte ratio; PCT, plateletcrit; PDW, platelet distribution width; PLR, platelet-to-lymphocyte ratio; PLT, platelet count; SD, standard deviation.

Discussion
In this retrospective study we analyzed the preoperatory inflammatory markers and platelet indices in 234 PTC patients compared with an age, gender and BMI control group of 108 patients with benign thyroid pathology. Furthermore, we investigated the relationship between inflammatory markers and platelet indices and pathological features of PTC and we compared pre-and postoperative inflammatory markers and platelet indices in PTC patients.
Xenograft experiments and transgenic mouse models demonstrated that platelet activation and platelet-cancer cell interaction are crucial for cancer development and metastasis. Growth factors, metabolites and microRNA released by activated platelets induce epithelial-to-mesenchymal transition and enhance cancer cell stemness, which is crucial for cancer cell colonization at the distant organs. Direct or indirect interaction of platelets induces cancer cell plasticity and enhances survival and extravasation of circulating cancer cells during dissemination. On the other hand, in vivo and in vitro experiments demonstrate that cancer cells induce platelet activation and aggregation, subsequently elevating the risk of thrombosis, suggesting that platelet-cancer interaction is bidirectional [9]. Furthermore, platelets interactions with cancer cells and the tumor microenvironment are very complex and seem to have dual behaviors: pro and anticancerous, with the procancerogenic effect out-numbering the anti-cancerous effects [25]. Targeting platelet-cancer cell interaction may be a potential strategy for reducing both cancer metastasis and cancer-associated thrombosis [9].
Given their broad accessibility, low cost and high reproducibility rates, platelet count and their indices-MPV, PDW and PCT-have been used as inflammatory markers in cancer patients and the subject of numerous studies in different types of cancer, but there are scarce and conflicting data surrounding their role as biomarkers in thyroid cancer, possibly due to the small size population in the previous studies and the excellent prognosis and high survival rates.
Our PTC patients had higher PLT and PCT when compared with controls, a finding that can be explained by the previously described overproduction of interleukin-6 in malignancies, which stimulates the production of thrombopoietin and leads to megakaryocyte proliferation [26]. To the best of our knowledge, we are the first to show that PLT and fibrinogen are independent predictors for the presence of PTC. Using ROC analysis, we found a cutoff value of 327.5 mg/dL for fibrinogen to predict the presence of PTC with a sensitivity of 53.8% and a specificity of 62.9% and a cutoff value of 223.5 × 10 3 /mm 3 for platelet number to predict the presence of PTC with a sensitivity of 73.1% and a specificity of 42.6%. Recently, Mizrak and Kucuk [27] also reported higher platelet count in PTC patients. Additionally, Dincel and Bayratkar noted similar results regarding PCT, but they found no significant difference in PLT between PTC and benign multinodular goiter patients [17]. Supporting our data, Jianyong et al. found that hyperfibrinogenemia is associated with advanced tumor stage and a high rate of recurrence, which enabled them to elaborate a nomogram that can be used to predict recurrence of papillary thyroid carcinoma [28].
Baldane et al. [16] reported that PTC patients have higher MPV values, which decrease after thyroidectomy, and their results were replicated by Ozmen et al. [29]. On the other hand, Yu et al. found lower MPV values in patients with thyroid cancer when compared with controls, but their study group included both DTC and MTC [30]. Our data showed no significant difference in MPV between PTC patients and controls. Additionally, we found no significant difference between preoperative and postoperative values for platelet indices and inflammatory markers, a finding that could be explained by the short time between surgery and the first follow-up visit, or by the connate inflammatory profile in cancer patients.
PDW also assesses the platelet volume, indicating their variation in size. Although often overlooked in everyday clinical practice, Xia et al. showed in their meta-analysis that a high PDW level is a prognostic factor for cancer and is associated with lymph node metastasis [10], while Dincel and Bayraktar obtained significantly lower PDW values in PTC patients when compared with controls [17]. Nevertheless, we could not find any significant difference in PDW levels among our study groups.
NLR and PLR have been widely studied as biomarkers in inflammatory conditions and cancer, but with inconsistent results in thyroid malignancies. A high number of neutrophils suppresses the immune system by inhibiting lymphocytes, activated T cells and natural killer cells in their cytolytic activity. On the other hand, lymphocytes and increased tumoral lymphocytic infiltration have been associated with better outcomes in cancer patients [31]. Seretis et al. were the first to show that NLR may predict the presence of PTC [11]. Subsequent studies showed higher NLR in PTC patients [22,32] and association with tumor size [14,33], extrathyroidal extension [33], lymph node metastases [34] or cancer recurrence [13]. Furthermore, a recent meta-analysis published by Feng et al. underlines the role of NLR as a biomarker for the prediction of tumor growth, metastasis and prognosis in patients with thyroid cancer [35]. Even though we did find a higher neutrophil count in the PTC group, we were not able to replicate the results of the previously mentioned studies. Our data did not reveal PLR as a useful marker in differentiating between PTC and benign thyroid disorders. However, consistent with the findings of Kim et al., who reported higher PLR in patients with tumors larger than 1 cm, in our PTC patients, higher PLR was associated with larger tumor size [36]. Looking further at the pathological reports and trying to find whether platelet indices or inflammatory markers can predict an aggressive tumor behavior, we surprisingly found lower fibrinogen levels in PTC patients with lymph node metastases-data that contradicts recent research on esophageal and gastric cancers [37,38]. However, we were able to replicate the results obtained by Wen et al. [19] regarding PDW and MPV, which were higher in patients with pathological autoimmune thyroiditis. Even though the presence of autoimmune thyroiditis was significantly higher in the control group, it was still highly prevalent in the PTC group as well, with almost half of the patients diagnosed with autoimmune thyroiditis based on thyroid antibody positivity and/or the pathological diagnosis. Published data show that up to one-third of PTC cases are associated with autoimmune thyroiditis [39]. For this reason, we chose to include all patients in the study, regardless of the presence of thyroid autoimmunity, in order to replicate the PTC cases that we evaluate in the clinical practice. While Machairas et al. [21] showed higher MPV in multifocal PTC and higher PLT, PCT and PLR in cases of extrathyroidal extension, platelet indices and inflammation did not differ depending on the presence of vascular invasion, capsular invasion, extracapsular extension, multifocality or pT classification in our study.
The strengths of this study are the important sample size of our thyroid cancer patients, the well-matched controls and the availability of pre-and postoperative data, as well as the detailed pathological reports. The main limitations are the retrospective nature of the study, which made it difficult to exclude other major factors that could have influenced fibrinogen levels and platelet indices, such as diabetes, smoking, infections, inflammatory diseases, iron deficiency and the use of antiplatelet drugs [40][41][42] and the lack of other inflammatory markers such as CRP (C-reactive protein), TNF-α (tumor necrosis factor-α), interleukin-6. The relationship between platelet indices, inflammatory markers and prognosis in PTC was not the subject of this paper, but it will be analyzed in a subsequent study as we gather more follow-up data.

Conclusions
Thyroid carcinomas are the most common type of endocrine malignancies, and their incidence has increased in the last decades due to widespread use of high-resolution ultrasonography. In the attempt to find markers that differentiate between benign and malignant thyroid nodules and help select appropriate treatments, our data show that fibrinogen and platelet count could be promising, inexpensive, independent predictors for the presence of PTC when compared with benign thyroid disorders.  Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and the study was approved by the Ethics Committee of Elias Hospital (1489/18.02.2021).

Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author.