Preoperative Systemic Inflammatory-Immune Status: A Predictor of Survival in Thyroid Carcinoma

Preoperative Systemic Inflammatory-Immune Status: A Predictor of Survival in Thyroid Carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Preoperative Systemic Inflammatory-Immune Status: A Predictor of Survival in Thyroid Carcinoma Xiaofang Zhang, Feng Liu, Weigang Wang, Chen Peng, Yanchao Qin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7857190/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Objective This study aimed to investigate the clinical value of preoperative peripheral blood inflammatory indices and immune function in evaluating clinicopathological characteristics and prognosis in thyroid cancer patients. Methods A total of 430 thyroid cancer patients who underwent radical surgery at Shanxi Provincial Cancer Hospital between January 2017 and June 2019 were enrolled as the thyroid cancer group. Additionally, 50 healthy individuals from the hospital’s health examination center during the same period were included as the healthy control group, and 100 patients with thyroid nodules were selected as the thyroid nodule group. Data collected for all participants included routine blood parameters (e.g., neutrophil, lymphocyte, and platelet counts), immune function indicators (e.g., CD3+, CD4+, CD8+, CD19+, and CD56+ cell percentages), and clinicopathological characteristics (e.g., gender, age, pathological type, number of lesions, and metastasis status). Retrospective analysis of clinical data was performed. Survival curves and Cox regression analysis were utilized to identify factors influencing thyroid cancer prognosis. Results Patients in the thyroid cancer group had higher levels of SII and Tg and TgAb than those in the healthy control group ( P = 0.018, P < 0.001, P = 0.007). The levels of SII and Tg and TgAb were higher in patients in the thyroid cancer group than in the thyroid nodule group ( P = 0.022, P = 0.043, P = 0.038). Clinicopathologic results showed that follicular carcinoma ( P = 0.008), occurrence of lymph node metastasis ( P = 0.016), and distant metastasis ( P < 0.001) of thyroid cancer patients had higher SII than those with papillary carcinoma, no lymph node metastasis and distant metastasis. Serum Tg and TgAb levels were higher in patients with thyroid cancer who also had lymph node metastasis ( P Tg < 0.001, P TgAb = 0.011) and distant metastasis ( P Tg < 0.001, P TgAb < 0.001) than in those who did not. The results of OS survival curves for immune-related factors showed that patients with thyroid cancer had the highest prognostic survival rates when the percentage expression of CD3+ cells, CD4+ cells, CD8+ cells, CD19+ cells, and CD56+ cells were between ≥62.5%, > 37.6%, ≤ 39.6%, ≥ 5.8%, and < 16.8%, respectively. The results of multifactorial analysis showed that age ( P = 0.019), pathologic type ( P < 0.001), presence of lymph node metastasis ( P < 0.001), presence of distant metastasis ( P < 0.001), preoperative SII ( P = 0.001), Tg ( P = 0.008), TgAb ( P = 0.027) levels, and CD8+ cells (%) ( P = 0.013) were independent influences on the prognosis of thyroid cancer patients. Conclusion Preoperative assessment of peripheral blood inflammatory indices and immune function aids in evaluating disease progression and prognosis in thyroid cancer patients. Optimal prognosis is achieved when peripheral immune cells are maintained in a dynamic equilibrium. Thyroid Cancer Inflammatory Index Immune Function Clinical Characteristics Prognosis Figures Figure 1 Figure 2 Introduction Thyroid cancer, the most prevalent malignancy affecting the head and neck region, continues to demonstrate alarmingly high incidence rates worldwide, representing a significant public health concern. In China, the incidence of thyroid cancer has been steadily rising by 20% annually. Despite being generally considered a slow-growing cancer with surgical treatment as the primary approach, a subset of patients present with aggressive characteristics such as high metastatic potential and increased risk of recurrence post-surgery, significantly impacting their prognosis and quality of life [1, 2] . Therefore, early detection and thorough analysis of clinical and pathological features play a crucial role in determining treatment strategies and postoperative surveillance [3] . Recent advancements in identifying novel biomarkers have enhanced our comprehension of thyroid cancer development and have introduced new possibilities for therapeutic interventions [4, 5] . However, the diverse pathological subtypes, varying biological behaviors, and different prognoses observed among patients make clinical management challenging [6, 7] . Previous research has indicated a strong link between inflammatory responses and the progression of thyroid cancer [8] . This study seeks to assess the predictive value of peripheral blood inflammatory markers and immune function in patients with thyroid cancer, aiming to offer insights that can enhance clinical decision-making and treatment strategies. Materials and methods 1 .Patients The study selected 430 thyroid cancer patients who underwent radical surgery in the head and neck surgery department of our hospital from January 2017 to June 2019 as the research subjects. Additionally, 50 healthy individuals who underwent physical examinations at our hospital during the same period (with thyroid ultrasound rated as grade 1) were selected as the healthy control group, and 100 individuals with thyroid nodules (with thyroid ultrasound rated as grades 2-3) were selected as the thyroid nodule control group. Epidemiological and clinical data were gathered from the patients' medical records, including age and gender at diagnosis, pathological type, number of lesions, presence of lymph node metastasis, presence of distant metastasis, serum Tg and TgAb levels, blood cell parameters, and percentages of immune cells. The inclusion criteria were as follows : (1) Patients hospitalized for the first time from January 2017 to June 2019 ; (2) All the patients were treated by surgery, and were diagnosed as thyroid cancer by pathology; (3) All cases had complete medical records. The exclusion criteria were as follows : (1) Pathologically undiagnosed patients; (2) Patients with more than 50% of information missing; (3) Patients who did not conduct the thyroid resection; (4) Presence of other malignant tumors, immune system diseases, or metabolic diseases. 2.Methods The levels of Tg and TgAb were measured using the electrochemiluminescence method. A blood cell analyzer was used to determine the counts of neutrophils (N), lymphocytes (TLC), and platelets (PLT). The systemic immune-inflammation index (SII) was calculated using the formula: SII = PLT × N / TLC. The percentage expressions of CD3+ cells, CD4+ cells, CD8+ cells, CD56+ cells, CD19+ cells, and CD127+ cells were detected using flow cytometry. 3.Follow-up The data pertaining to the follow-up of patients were obtained through the review of hospital records. Patients were followed up via telephone, with the follow-up period ending in June 2023. Survival time was calculated from the date of thyroid cancer diagnosis to either death or June 2023, measured in months.Censoring occurred for patients who were still alive or deceased for other reasons at follow-up. 4.Statistical Analysis Data analysis was performed using GraphPad Prism 9 software. Categorical data were expressed as percentages, and continuous variables were presented as mean ± standard deviation. Comparisons between two groups were conducted using independent samples t-test, while comparisons among multiple groups were analyzed using analysis of variance (ANOVA). X-tile software (version 3.6.1) was employed to categorize immune-related data by identifying optimal cutoff values and grouping continuous variables. Survival analysis was performed using R software (version 4.1.3). The Kaplan-Meier method (via the survival package) was used to calculate survival rates and generate survival curves, with differences among the three groups compared using the Log-rank test. To control the Type I error rate caused by multiple comparisons, Bonferroni correction was applied to adjust P-values for multi-group comparisons. Survival curves were visualized using the survminer package. Cox regression models were utilized for univariate and multivariate analyses to identify risk factors, with results presented as forest plots. Statistical significance was defined as P<0.05. Results 1. The basic clinical characteristics of thyroid cancer patients Among 430 thyroid cancer patients, 339 were female (78.8%) and 91 were male (21.2%). Age distribution was as follows: 5 cases (1.1%) aged 13–20 years, 31 cases (7.2%) aged 21–30 years, 78 cases (18.1%) aged 31–40 years, 141 cases (32.8%) aged 41–50 years, 122 cases (28.4%) aged 51–60 years, 40 cases (9.3%) aged 61–70 years, and 13 cases (3.0%) aged 71–84 years. Pathological types included 306 cases of papillary carcinoma (71.2%) and 124 cases of follicular carcinoma (27.8%). Single lesions were observed in 386 cases (89.7%), while multiple lesions were present in 44 cases (10.3%). Clinical staging revealed 294 cases (68.3%) in stages I–II and 136 cases (31.7%) in stages III–IV. Lymph node metastasis occurred in 163 cases (37.9%) and was absent in 267 cases (62.1%). Distant metastasis was identified in 34 cases (7.9%), with no distant metastasis in 396 cases (92.1%)(Table 1). 2. The comparison of SII, Tg, and TgAb levels among thyroid cancer group, thyroid nodule group, and healthy control group The findings revealed that the thyroid cancer group exhibited significantly higher SII, Tg, and TgAb levels compared to the healthy control group ( P = 0.018, P < 0.001, P = 0.007). Furthermore, the thyroid cancer group also demonstrated significantly elevated SII, Tg, and TgAb levels compared to the thyroid nodule group, with statistically significant differences ( P = 0.022, P = 0.043, P = 0.038)(Table 2). 3. The comparison of SII, Tg, and TgAb levels in thyroid cancer patients with different clinicopathological characteristics The results of our analysis indicated that patients with follicular carcinoma ( P = 0.008), lymph node metastasis ( P = 0.016), and distant metastasis ( P < 0.001) exhibited significantly higher SII levels compared to those with papillary carcinoma, no lymph node metastasis, or no distant metastasis, respectively. Additionally, thyroid cancer patients with lymph node metastasis ( P Tg < 0.001, P TgAb = 0.011) and distant metastasis ( P Tg < 0.001, P TgAb < 0.001) demonstrated elevated serum Tg and TgAb levels compared to non-metastatic patients(Table 3）. 4. The impact of immune function on survival rate in thyroid cancer patients The results showed that thyroid cancer patients exhibited the highest prognostic survival rates when the percentages of CD3+ cells (≥62.5%), CD4+ cells (>37.6%), CD8+ cells (≤39.6%), CD19+ cells (≥5.8%), and CD56+ cells (<16.8%) fell within the specified thresholds. In contrast, the grouping of CD127+ cells had almost no impact on overall survival ( Figure 1). 5. The prognostic analysis of thyroid cancer patients Univariate and multivariate Cox regression models were employed to screen factors associated with the prognosis of thyroid cancer patients. Variables with statistically significant differences in univariate analysis were incorporated into the multivariate Cox regression model. The final results demonstrated that age >50 years ( P = 0.035), follicular carcinoma ( P = 0.009), presence of lymph node ( P = 0.034) or distant metastasis ( P < 0.001), elevated SII( P < 0.001), higher Tg( P = 0.006) or TgAb( P = 0.038), lower CD3+ cell（%)( P < 0.001), lower CD4+ cell（%）( P = 0.021), and lower CD8+ cell（%）( P = 0.008) may result in unfavorable clinical outcomes for patients with thyroid cancer patients. The results of the multivariate Cox regression analysis indicated that age (HR:1.549, 95%CI:1.326 - 2.849, P = 0.019), pathological type (HR:2.349, 95%CI:2.362 - 4.753, P < 0.001), lymph node metastasis (HR:1.539, 95%CI:1.324 - 3.216, P < 0.001), distant metastasis (HR:2.121, 95%CI:1.235 - 3.096, P < 0.001), preoperative SII (HR:2.946, 95%CI:2.016 - 4.679, P = 0.001), Tg (HR:1.516, 95%CI:1.123 - 2.849, P = 0.008), TgAb (HR:1.729, 95%CI:1.426 - 3.756, P = 0.027), and CD8+ cell percentage (HR:1.946, 95%CI:1.529 - 2.759, P = 0.031) were independent prognostic factors for thyroid cancer patients(Table 4). Based on the results of the multivariate Cox regression analysis, a forest plot was constructed with variable assignments. As shown in Figure 2，in terms of age, patients aged >50 years had a HR of 1.765 (95%CI: 1.475–2.719, P = 0.034) compared to those ≤50 years, indicating a significantly higher risk of poor prognosis in older patients. For pathological subtypes, follicular carcinoma exhibited a markedly elevated HR of 2.349 (95%CI: 2.362 – 4.753, P < 0.001) relative to papillary carcinoma, suggesting a worse prognosis for follicular carcinoma patients. Additionally, the presence of lymph node metastasis (HR:2.81, 95% CI: 1.92–4.10, P < 0.001), distant metastasis (HR: 3.45, 95% CI: 2.30–5.18, P 53.10 IU/mL (HR:1.65, 95% CI: 1.15–2.36, P = 0.016) were all associated with higher hazard ratios ( P < 0.05). Conversely, lower risk was observed in patients with CD3+ cell percentage <70.15% (HR:0.68, 95% CI: 0.47–0.99, P = 0.054) and CD8+ cell percentage <28.86% (HR:0.62, 95% CI: 0.39–0.98, P = 0.043), with the latter achieving statistical significance. Discussion Thyroid cancer is the most common malignant tumor of the endocrine system, accounting for approximately 1% of all systemic malignancies, and includes four pathological types: papillary carcinoma, follicular carcinoma, anaplastic carcinoma, and medullary carcinoma [9] . The pathogenesis of thyroid cancer remains unclear, with multiple etiological factors implicated, including dysregulated inflammatory responses. First, inflammation can directly contribute to carcinogenesis; second, it may act on the tumor microenvironment (TME) to mediate tumor progression [10, 11] . The tumor microenvironment (TME) is a complex system that includes an immune microenvironment primarily composed of immune cells, alongside a non-immune microenvironment characterized by fibroblasts [8, 12] . Lymphocytes are crucial to the immune system and significantly influence its functional status. The systemic immune-inflammation index (SII) [13] , a novel hematological marker based on neutrophil, lymphocyte, and platelet counts, has shown prognostic significance in cancers such as lung [14] , esophageal [15] , and gastric cancers [16] . In this study, SII levels were significantly higher in thyroid cancer patients than in healthy controls and individuals with thyroid nodules. Furthermore, SII levels differed markedly between follicular carcinoma and papillary carcinoma patients (P < 0.05), as well as between patients with and without lymph node or distant metastasis (P < 0.05), suggesting that inflammatory responses participate in thyroid cancer development and progression and may aid in assessing disease severity and prognosis. These findings align with the study by Schumm MA et al. [17] . Additionally, Huang et al. [18] demonstrated that SII is an independent risk factor for lymph node metastasis in endometrial cancer, further supporting the close relationship between thyroid cancer and inflammation. Chronic thyroiditis may even harbor potential for malignant transformation. Mechanistically, SII reflects the balance between pro-tumor inflammation and anti-tumor immunity, tumor cell proliferation, invasiveness, and metastasis, thereby influencing prognosis [19] . Elevated SII, often driven by neutrophilia, promotes an immunosuppressive TME via reactive oxygen species and cytokines, facilitating thyroid cancer proliferation and metastasis, while lymphocytopenia reduces tumor cell clearance [20, 21] . Thus, thyroid carcinogenesis is closely linked to systemic inflammatory and immune status [22, 23] . Our results revealed optimal prognostic survival rates in thyroid cancer patients when the percentages of CD3 + cells % (≥ 62.5), CD4 + cells % (> 37.6), CD8 + cells % (≤ 39.6), CD19 + cells % (≥ 5.8), and CD56 + cells % (< 16.8) fell within specific thresholds. T lymphocytes, particularly CD4 + and CD8 + subsets, are central to cellular immunity and anti-tumor responses. In this study, CD3+%, CD4+%, and CD8+% all significantly impacted prognosis. Yang et al. [24] found that CD4 + T-cell imbalance promotes cervical cancer progression, whereas Giraldo et al. [25] reported that high CD8 + T-cell levels correlate with shorter progression-free survival (PFS) and overall survival (OS) in renal and prostate cancers. Notably, multivariate analysis identified CD8+% as an independent prognostic factor in thyroid cancer.Natural killer (NK) cells, the first line of anti-tumor defense, rapidly recognize and eliminate tumor cells, reducing metastatic burden and prolonging survival in preclinical models. Studies link NK cell activity to improved survival in hepatocellular carcinoma [26] , clear cell renal cell carcinoma [27] , and prostate cancer [28] . B cells, activated by tumor antigens with CD4 + T-cell help, secrete anti-tumor antibodies, though their prognostic role remains debated. For instance, B-cell infiltration negatively correlates with survival in ovarian cancer with pleural effusion, yet associates with favorable outcomes in gastric cancer with tertiary lymphoid structures (TLSs) [28] . Autoimmune disorders are also implicated in thyroid cancer pathogenesis and post-operative recurrence/metastasis [29] . Thyroglobulin (Tg), produced by thyroid follicular cells, is minimally released into circulation under normal conditions. Elevated serum Tg triggers autoimmune responses, inducing thyroglobulin antibody (TgAb) production, which correlates with disease progression [30, 31] . Post-thyroidectomy monitoring of Tg and TgAb aids in detecting residual disease or recurrence [32] . Our study showed higher serum Tg and TgAb levels in patients with lymph node or distant metastasis ( P < 0.05), suggesting their predictive value for post-operative metastasis. Elevated Tg reflects disease severity, while residual tumor cells post-surgery drive Tg overproduction and TgAb generation. Higher levels indicate immune dysregulation and may serve as biomarkers for disease progression [33, 34] . In conclusion, thyroid carcinogenesis is closely associated with immune dysfunction. Impaired immunity, coupled with inflammatory cytokine release, exacerbates metastasis and recurrence risks. A balanced peripheral immune microenvironment correlates with optimal prognosis. Thus, monitoring these biomarkers—SII, immune cell subsets, Tg, and TgAb—may enhance prognostic prediction in thyroid cancer patients. Declarations Acknowledgements Not Applicable. Authors’ contributions XZ performed the analysis and wrote the manuscript, FL supervised the statistical analysis, XZ and WW completed data collection, CP supervised the analysis, YQ revised the manuscript. All authors reviewed the manuscript. Funding Supported by Fundamental Research Program of Shanxi Province (202303021222370) Data Availability The data used to support the findings of this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate Our present study was conducted in accordance with the Declaration of Helsinki (1964), and also approved by the Medical Ethics Committee of Shanxi Province Cancer Hospital. The Medical Ethics Committee of Shanxi Province Cancer Hospital waived the requirement of written informed consent for participation. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. References WENG H Y, YAN T, QIU W W, et al. Long-term outcomes and prognostic factors in papillary thyroid microcarcinoma patients with distant metastases [J]. Endocrine, 2022, 75(2): 495-507. RUIZ PARDO J, RíOS A, RODRíGUEZ J M, et al. Risk Factors of Metastatic Lymph Nodes in Papillary Thyroid Microcarcinoma [J]. Cirugia espanola, 2020, 98(4): 219-25. BONJOC K J, YOUNG H, WARNER S, et al. Thyroid cancer diagnosis in the era of precision imaging [J]. Journal of thoracic disease, 2020, 12(9): 5128-39. LI M, LI Q, ZOU C, et al. Application and recent advances in conventional biomarkers for the prognosis of papillary thyroid carcinoma [J]. Frontiers in oncology, 2025, 15: 1598934. AGARWAL S, BYCHKOV A, JUNG C K. Emerging Biomarkers in Thyroid Practice and Research [J]. Cancers, 2021, 14(1). IBRAHIMPASIC T, GHOSSEIN R, SHAH J P, et al. Poorly Differentiated Carcinoma of the Thyroid Gland: Current Status and Future Prospects [J]. Thyroid : official journal of the American Thyroid Association, 2019, 29(3): 311-21. CEOLIN L, DUVAL M, BENINI A F, et al. Medullary thyroid carcinoma beyond surgery: advances, challenges, and perspectives [J]. Endocrine-related cancer, 2019, 26(9): R499-r518. CUNHA L L, WARD L S. Translating the immune microenvironment of thyroid cancer into clinical practice [J]. Endocrine-related cancer, 2022, 29(6): R67-r83. ZHANG T, HE L, WANG Z, et al. The Differences Between Multifocal and Unifocal Papillary Thyroid Carcinoma in Unilateral Lobe: A Meta-Analysis [J]. Frontiers in oncology, 2021, 11: 657237. LEWINSKI A, SLIWKA P W, STASIOLEK M. Dendritic cells in autoimmune disorders and cancer of the thyroid [J]. Folia histochemica et cytobiologica, 2014, 52(1): 18-28. ZHANG Z, XU T, QIN W, et al. Upregulated PTPN2 induced by inflammatory response or oxidative stress stimulates the progression of thyroid cancer [J]. Biochemical and biophysical research communications, 2020, 522(1): 21-5. JAUME J C. Thyroid Cancer-The Tumor Immune Microenvironment (TIME) over Time and Space [J]. Cancers, 2025, 17(5). VURAL S, MUHTAROĞLU A, GüNGöR M. Systemic immune-inflammation index: A new marker in differentiation of different thyroid diseases [J]. Medicine, 2023, 102(31): e34596. YANG C, ZHANG Y, WANG R, et al. IL-10(+)CD19(+) regulatory B cells induce CD4(+)Foxp3(+)regulatory T cells in serum of cervical cancer patients [J]. Autoimmunity, 2024, 57(1): 2290909. FU M, LI Z, MA J, et al. Study on the predictive value of pretreatment peripheral blood inflammatory markers regarding immunotherapy in patients with inoperable advanced or locally advanced oesophageal squamous cell carcinoma [J]. Scandinavian journal of gastroenterology, 2024, 59(6): 722-9. DING P, GUO H, SUN C, et al. Combined systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI) predicts chemotherapy response and prognosis in locally advanced gastric cancer patients receiving neoadjuvant chemotherapy with PD-1 antibody sintilimab and XELOX: a prospective study [J]. BMC gastroenterology, 2022, 22(1): 121. SCHUMM M A, SHU M L, HUGHES E G, et al. Prognostic Value of Preoperative Molecular Testing and Implications for Initial Surgical Management in Thyroid Nodules Harboring Suspected (Bethesda V) or Known (Bethesda VI) Papillary Thyroid Cancer [J]. JAMA otolaryngology-- head & neck surgery, 2023, 149(8): 735-42. HUANG H, LIU Q, ZHU L, et al. Prognostic Value of Preoperative Systemic Immune-Inflammation Index in Patients with Cervical Cancer [J]. Scientific reports, 2019, 9(1): 3284. SHERMAN S I J B P. Targeted therapy of thyroid cancer [J]. 2010, 80(5): 592-601. BAUER A T, GORZELANNY C, GEBHARDT C, et al. Interplay between coagulation and inflammation in cancer: Limitations and therapeutic opportunities [J]. Cancer treatment reviews, 2022, 102: 102322. YANG R, CHANG Q, MENG X, et al. Prognostic value of Systemic immune-inflammation index in cancer: A meta-analysis [J]. Journal of Cancer, 2018, 9(18): 3295-302. MENICALI E, GUZZETTI M, MORELLI S, et al. Immune Landscape of Thyroid Cancers: New Insights [J]. Frontiers in endocrinology, 2020, 11: 637826. FERRARI S M, FALLAHI P, GALDIERO M R, et al. Immune and Inflammatory Cells in Thyroid Cancer Microenvironment [J]. International journal of molecular sciences, 2019, 20(18). XIAO R, TIAN Y, ZHANG J, et al. Increased Siglec-9/Siglec-9L interactions on NK cells predict poor HCC prognosis and present a targetable checkpoint for immunotherapy [J]. Journal of hepatology, 2024, 80(5): 792-804. NúñEZ S Y, TROTTA A, REGGE M V, et al. Tumor-associated macrophages impair NK cell IFN-γ production and contribute to tumor progression in clear cell renal cell carcinoma [J]. European journal of immunology, 2024, 54(6): e2350878. MAO F, YANG C, LUO W, et al. Peripheral blood lymphocyte subsets are associated with the clinical outcomes of prostate cancer patients [J]. International immunopharmacology, 2022, 113(Pt A): 109287. DONG H P, ELSTRAND M B, HOLTH A, et al. NK- and B-cell infiltration correlates with worse outcome in metastatic ovarian carcinoma [J]. American journal of clinical pathology, 2006, 125(3): 451-8. SAKIMURA C, TANAKA H, OKUNO T, et al. B cells in tertiary lymphoid structures are associated with favorable prognosis in gastric cancer [J]. The Journal of surgical research, 2017, 215: 74-82. PAGANO L, MELE C, SAMA M T, et al. Thyroid cancer phenotypes in relation to inflammation and autoimmunity [J]. Frontiers in bioscience (Landmark edition), 2018, 23(12): 2267-82. LU Y, ZHAO H, LIU C, et al. The role of preoperative serum thyroglobulin in the diagnosis and treatment of differentiated thyroid cancer: a systematic review and meta-analysis [J]. Frontiers in oncology, 2024, 14: 1426785. ZHAO Y, MU Z, LIANG D, et al. Prognostic value of postoperative anti-thyroglobulin antibody in patients with differentiated thyroid cancer [J]. Frontiers in endocrinology, 2024, 15: 1354426. SPENCER C, FATEMI S. Thyroglobulin antibody (TgAb) methods - Strengths, pitfalls and clinical utility for monitoring TgAb-positive patients with differentiated thyroid cancer [J]. Best practice & research Clinical endocrinology & metabolism, 2013, 27(5): 701-12. VITIELLO A, LA PORTA R, TRAMA U, et al. Pandemic COVID-19, an update of current status and new therapeutic strategies [J]. Naunyn-Schmiedeberg's archives of pharmacology, 2022, 395(10): 1159-65. NTOTSIKAS K, LAZARIOTI S, DARAKI V, et al. Thyroglobulin as a Rapid and Cost-Effective Biomarker for Diagnosis of Thyroid Carcinoma Brain Metastasis: A Case Report of a Patient with Metastatic Hurthle Cell Thyroid Carcinoma [J]. The American journal of case reports, 2023, 24: e939025. Tables Tab le 1 The clinical characteristics of 430 thyroid cancer patients Characteristics n Gender Male/Female 91/339 Age ≤50years/>50 years 256/174 Pathological type papillarycarcinoma/follicular carcinoma 306/124 lesion Single/multiple 386/44 Stage I–II/III–IV 294/136 Lymph node status Negative/Positive 267/163 Distant metastasis Negative/Positive 396/34 Table 2 The comparison of SII, Tg, and TgAb levels among thyroid cancer group, thyroid nodule group, and healthy control group Group n SII Tg TgAb Healthy Control Group 50 216.13±67.23 25.87±3.85 80.74±19.62 Thyroid Nodule 100 332.57±123.64* 52.79±5.81* 198.84±56.63* Thyroid Cancer 430 576.35±136.79 *# 85.69±22.38* # 316.05±105.78* # F 176.51 24.36 86.63 P ＜0.001 ＜0.001 ＜0.001 Note: Data are presented as mean ± SD; * P < 0.05 vs. Healthy Control Group; # P < 0.05 vs. Thyroid Nodule Group. Table 3 The comparison of SII, Tg, and TgAb levels in thyroid cancer patients with different clinicopathological characteristics Index n SII Χ 2 P Tg(μg/L) Χ 2 P TgAb(IU/ml) Χ 2 P Gender 3.562 0.946 2.392 0.814 0.298 0.712 Male 91 579.63±26.68 23.95±5.84 52.36±4.67 Female 339 575.68±37.89 24.02±6.83 53.26±5.63 Age 2.159 0.687 1.926 0.717 0.623 0.701 ≤50 years 256 574.59±32.59 22.69±5.13 51.96±4.68 ＞50 years 174 577.89±42.59 23.74±4.98 52.59±5.13 Pathological type 17.100 0.008 2.623 0.659 0.749 0.589 Follicular carcinoma 124 577.80±43.98 20.36±6.03 52.48±4.68 Papillary carcinoma 306 503.59±35.69 21.38±6.32 53.26±5.39 Lymph node status 13.652 0.016 19.203 ＜0.001 14.208 0.011 Positive 163 593.23±55.63 38.79±7.23 72.36±9.26 Negative 267 400.26±69.26 18.26±6.23 32.68±7.09 Distant metastasis 21.652 ＜0.001 16.387 ＜0.001 21.682 ＜0.001 Positive 34 613.68±75.69 46.29±8.26 69.98±8.36 Negative 396 564.59±68.59 23.68±8.59 28.69±6.98 Table 4 The univariate and multivariate analysis of thyroid cancer patients Index univariate multivariate HR 95%CI P-value HR 95%CI P-value Gender 1.780 0.543-4.329 0.826 - - - Age 1.726 1.244-3.435 0.035 1.549 1.326-2.849 0.019 Pathological type 2.879 1.921-4.386 0.009 2.349 2.362-4.753 ＜0.001 Lymph node metastasis 1.791 1.072-2.789 0.034 1.539 1.324-3.216 ＜0.001 Distant metastasis 2.343 1.509-3.928 ＜0.001 2.121 1.235-3.096 ＜0.001 SII 2.269 1.298-4.213 ＜0.001 2.946 2.016-4.679 0.001 Tg 1.759 1.026-3.902 0.006 1.516 1.123-2.849 0.008 TgAb 1.920 1.023-2.468 0.038 1.729 1.426-3.756 0.027 CD3+ cell （ % ） 1.272 1.849-3.432 ＜0.001 1.126 0.849-1.516 0.094 CD4+ cell （ % ） 1.161 1.056-1.265 0.021 1.329 0.746-1.902 0.074 CD8+ cell （ % ） 2.829 1.736-3.469 0.008 1.946 1.529-2.759 0.031 CD56+ cell （ % ） 1.313 1.231-2.198 0.386 - - - CD19+ cell （ % ） 0.708 0.659-1.869 0.866 - - - Note:Gender: male vs. female, Age:(≤50years vs. >50 years), Pathological type: papillary carcinoma vs. follicular carcinoma, Lymph node metastasis: negative vs. positive, Distant metastasis: negative vs. positive, SII: (<576.48 vs. ≥576.48 ), Tg: (<23.99 μg/L vs. ≥23.99 μg/L), TgAb:(<53.10 IU/mL vs. ≥53.10 IU/mL), CD3+ cells(%):(<70.15% vs. ≥70.15%), CD4+ cells (%):( <36.64% vs. ≥36.64%), CD8+ cells (%):(<28.86% vs. ≥28.86% ) Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7857190","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":549393166,"identity":"3a3ded74-1190-4290-a974-10a5c71cb810","order_by":0,"name":"Xiaofang Zhang","email":"","orcid":"","institution":"Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaofang","middleName":"","lastName":"Zhang","suffix":""},{"id":549393167,"identity":"4d53215e-7ff5-4cb4-85f9-1cfa381e5507","order_by":1,"name":"Feng Liu","email":"","orcid":"","institution":"Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Liu","suffix":""},{"id":549393168,"identity":"811fb1b2-867a-41b6-b697-6e28216a273d","order_by":2,"name":"Weigang Wang","email":"","orcid":"","institution":"Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weigang","middleName":"","lastName":"Wang","suffix":""},{"id":549393169,"identity":"fff80234-4c73-4866-b78c-c395b8e086dc","order_by":3,"name":"Chen Peng","email":"","orcid":"","institution":"Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical 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1","display":"","copyAsset":false,"role":"figure","size":493419,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival analysis of thyroid cancer patients based on immune cell percentages\u003c/p\u003e\n\u003cp\u003e(A) CD3+ cell percentage: Optimal cutoff value; Cumulative survival curve\u003c/p\u003e\n\u003cp\u003e(B) CD4+ cell percentage: Optimal cutoff value; Cumulative survival curve\u003c/p\u003e\n\u003cp\u003e(C) CD8+ cell percentage: Optimal cutoff value; Cumulative survival curve\u003c/p\u003e\n\u003cp\u003e(D) CD19+ cell percentage: Optimal cutoff value; Cumulative survival curve\u003c/p\u003e\n\u003cp\u003e(E) CD56+ cell percentage: Optimal cutoff value;Cumulative survival curve\u003c/p\u003e\n\u003cp\u003e(F) CD127+ cell percentage:Optimal cutoff value;Cumulative survival curve\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7857190/v1/daa47d318bf091f497fedd7a.png"},{"id":96789333,"identity":"e06d5a63-ac4d-43b4-be4f-2b7b7a58edb5","added_by":"auto","created_at":"2025-11-26 06:43:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5967686,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of multivariate cox regression analysis for thyroid cancer prognosis\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7857190/v1/f55ef6ba941cecfe5a78f707.png"},{"id":96922702,"identity":"17d4b7c5-cfa8-4a9e-a999-047e0c76d451","added_by":"auto","created_at":"2025-11-27 14:19:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1925280,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7857190/v1/8e254375-5729-4b1d-8120-7c85c3051aaf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Preoperative Systemic Inflammatory-Immune Status: A Predictor of Survival in Thyroid Carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThyroid cancer, the most prevalent malignancy affecting the head and neck region, continues to demonstrate alarmingly high incidence rates worldwide, representing a significant public health concern. In China, the incidence of thyroid cancer has been steadily rising by 20% annually. Despite being generally considered a slow-growing cancer with surgical treatment as the primary approach, a subset of patients present with aggressive characteristics such as high metastatic potential and increased risk of recurrence post-surgery, significantly impacting their prognosis and quality of life\u003csup\u003e[1, 2]\u003c/sup\u003e. Therefore, early detection and thorough analysis of clinical and pathological features play a crucial role in determining treatment strategies and postoperative surveillance\u003csup\u003e[3]\u003c/sup\u003e. Recent advancements in identifying novel biomarkers have enhanced our comprehension of thyroid cancer development and have introduced new possibilities for therapeutic interventions\u003csup\u003e[4, 5]\u003c/sup\u003e. However, the diverse pathological subtypes, varying biological behaviors, and different prognoses observed among patients make clinical management challenging\u003csup\u003e[6, 7]\u003c/sup\u003e. Previous research has indicated a strong link between inflammatory responses and the progression of thyroid cancer\u003csup\u003e[8]\u003c/sup\u003e. This study seeks to assess the predictive value of peripheral blood inflammatory markers and immune function in patients with thyroid cancer, aiming to offer insights that can enhance clinical decision-making and treatment strategies.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e.Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study selected 430 thyroid cancer patients who underwent radical surgery in the head and neck surgery department of our hospital from January 2017 to June 2019 as the research subjects. Additionally, 50 healthy individuals who underwent physical examinations at our hospital during the same period (with thyroid ultrasound rated as grade 1) were selected as the healthy control group, and 100 individuals with thyroid nodules (with thyroid ultrasound rated as grades 2-3) were selected as the thyroid nodule control group.\u0026nbsp;Epidemiological and clinical data were gathered from the patients' medical records, including age and gender at diagnosis,\u0026nbsp;pathological type, number of lesions, presence of lymph node metastasis, presence of distant metastasis, serum Tg and TgAb levels, blood cell parameters, and percentages of immune cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe inclusion criteria were\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eas follows\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) Patients hospitalized for the first time from January 2017 to June 2019\u0026nbsp;;\u003c/p\u003e\n\u003cp\u003e(2)\u0026nbsp;All the patients were treated by surgery, and were diagnosed as\u0026nbsp;thyroid cancer\u0026nbsp;by \u0026nbsp; \u0026nbsp;pathology;\u003c/p\u003e\n\u003cp\u003e(3) All cases had complete medical records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe exclusion criteria were\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eas follows\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) Pathologically undiagnosed patients;\u003c/p\u003e\n\u003cp\u003e(2) Patients with more than 50% of information missing;\u003c/p\u003e\n\u003cp\u003e(3) Patients who did not conduct the\u0026nbsp;thyroid\u0026nbsp;resection;\u003c/p\u003e\n\u003cp\u003e(4) Presence of other malignant tumors, immune system diseases, or metabolic diseases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe levels of Tg and TgAb were measured using the electrochemiluminescence method. A blood cell analyzer was used to determine the counts of neutrophils (N), lymphocytes (TLC), and platelets (PLT). The systemic immune-inflammation index (SII) was calculated using the formula: SII = PLT × N / TLC. The percentage expressions of CD3+ cells, CD4+ cells, CD8+ cells, CD56+ cells, CD19+ cells, and CD127+ cells were detected using flow cytometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.Follow-up\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data pertaining to the follow-up of patients were obtained through the review of hospital records.\u0026nbsp;Patients were followed up via telephone, with the follow-up period ending in June 2023. Survival time was calculated from the date of thyroid cancer diagnosis to either death or June 2023, measured in months.Censoring occurred for patients who were still alive or deceased for other reasons at follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis was performed using GraphPad Prism 9 software. Categorical data were expressed as percentages, and continuous variables were presented as mean ± standard deviation. Comparisons between two groups were conducted using independent samples t-test, while comparisons among multiple groups were analyzed using analysis of variance (ANOVA). X-tile software (version 3.6.1) was employed to categorize immune-related data by identifying optimal cutoff values and grouping continuous variables. Survival analysis was performed using R software (version 4.1.3). The Kaplan-Meier method (via the survival package) was used to calculate survival rates and generate survival curves, with differences among the three groups compared using the Log-rank test. To control the Type I error rate caused by multiple comparisons, Bonferroni correction was applied to adjust P-values for multi-group comparisons. Survival curves were visualized using the survminer package. Cox regression models were utilized for univariate and multivariate analyses to identify risk factors, with results presented as forest plots. Statistical significance was defined as P\u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e1. \u003cstrong\u003eThe basic clinical characteristics of thyroid cancer patients\u003cbr\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eAmong 430 thyroid cancer patients, 339 were female (78.8%) and 91 were male (21.2%). Age distribution was as follows: 5 cases (1.1%) aged 13–20 years, 31 cases (7.2%) aged 21–30 years, 78 cases (18.1%) aged 31–40 years, 141 cases (32.8%) aged 41–50 years, 122 cases (28.4%) aged 51–60 years, 40 cases (9.3%) aged 61–70 years, and 13 cases (3.0%) aged 71–84 years. Pathological types included 306 cases of papillary carcinoma (71.2%) and 124 cases of follicular carcinoma (27.8%). Single lesions were observed in 386 cases (89.7%), while multiple lesions were present in 44 cases (10.3%). Clinical staging revealed 294 cases (68.3%) in stages I–II and 136 cases (31.7%) in stages III–IV. Lymph node metastasis occurred in 163 cases (37.9%) and was absent in 267 cases (62.1%). Distant metastasis was identified in 34 cases (7.9%), with no distant metastasis in 396 cases (92.1%)(Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. The comparison of SII, Tg, and TgAb levels among thyroid cancer group, thyroid nodule group, and healthy control group\u003cbr\u003e\u003c/strong\u003eThe findings revealed\u0026nbsp;that the thyroid cancer group exhibited significantly higher SII, Tg, and TgAb levels compared to the healthy control group (\u003cem\u003eP\u003c/em\u003e = 0.018, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.007). Furthermore, the thyroid cancer group also demonstrated significantly elevated SII, Tg, and TgAb levels compared to the thyroid nodule group, with statistically significant differences (\u003cem\u003eP\u003c/em\u003e = 0.022, \u003cem\u003eP\u003c/em\u003e = 0.043, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.038)(Table 2).\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eThe comparison of SII, Tg, and TgAb levels in thyroid cancer patients with different clinicopathological characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of our analysis indicated that patients with follicular carcinoma (\u003cem\u003eP\u003c/em\u003e = 0.008), lymph node metastasis (\u003cem\u003eP\u003c/em\u003e = 0.016), and distant metastasis (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) exhibited significantly higher SII levels compared to those with papillary carcinoma, no lymph node metastasis, or no distant metastasis, respectively. Additionally, thyroid cancer patients with lymph node metastasis (\u003cem\u003eP\u003c/em\u003e\u003csub\u003eTg\u003c/sub\u003e \u0026lt; 0.001, \u003cem\u003eP\u003c/em\u003e\u003csub\u003eTgAb\u003c/sub\u003e = 0.011) and distant metastasis (\u003cem\u003eP\u003c/em\u003e\u003csub\u003eTg\u003c/sub\u003e \u0026lt; 0.001, \u003cem\u003eP\u003c/em\u003e\u003csub\u003eTgAb\u003c/sub\u003e \u0026lt; 0.001) demonstrated elevated serum Tg and TgAb levels compared to non-metastatic patients(Table 3）.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. The impact of immune function on survival rate in thyroid cancer patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results showed that thyroid cancer patients exhibited the highest prognostic survival rates when the percentages of\u0026nbsp;CD3+ cells\u0026nbsp;(≥62.5%),\u0026nbsp;CD4+ cells\u0026nbsp;(\u0026gt;37.6%),\u0026nbsp;CD8+ cells\u0026nbsp;(≤39.6%),\u0026nbsp;CD19+ cells\u0026nbsp;(≥5.8%), and\u0026nbsp;CD56+ cells\u0026nbsp;(\u0026lt;16.8%) fell within the specified thresholds. In contrast, the grouping of\u0026nbsp;CD127+ cells\u0026nbsp;had almost no impact on overall survival ( Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.\u0026nbsp; \u0026nbsp;The prognostic analysis of thyroid cancer patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnivariate and multivariate Cox regression models were employed to screen factors associated with the prognosis of thyroid cancer patients. Variables with statistically significant differences in univariate analysis were incorporated into the multivariate Cox regression model. The final results demonstrated that\u0026nbsp;age \u0026gt;50 years (\u003cem\u003eP\u003c/em\u003e = 0.035), follicular carcinoma (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.009), presence of lymph node (\u003cem\u003eP\u003c/em\u003e = 0.034) or distant metastasis (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), elevated SII(\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), higher Tg(\u003cem\u003eP\u003c/em\u003e = 0.006) or TgAb(\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.038), lower CD3+ cell（%)(\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), lower CD4+ cell（%）(\u003cem\u003eP\u003c/em\u003e = 0.021), and lower CD8+ cell（%）(\u003cem\u003eP\u003c/em\u003e = 0.008)\u0026nbsp;may result in unfavorable clinical outcomes for patients with\u0026nbsp;thyroid cancer patients.\u0026nbsp;The results of the multivariate Cox regression analysis indicated that\u0026nbsp;age (HR:1.549, 95%CI:1.326 - 2.849, \u003cem\u003eP\u003c/em\u003e = 0.019), pathological type (HR:2.349, 95%CI:2.362 - 4.753, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), lymph node metastasis (HR:1.539, 95%CI:1.324 - 3.216, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), distant metastasis (HR:2.121, 95%CI:1.235 - 3.096, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), preoperative SII (HR:2.946, 95%CI:2.016 - 4.679, \u003cem\u003eP\u003c/em\u003e = 0.001), Tg (HR:1.516, 95%CI:1.123 - 2.849, \u003cem\u003eP\u003c/em\u003e = 0.008), TgAb (HR:1.729, 95%CI:1.426 - 3.756, \u003cem\u003eP\u003c/em\u003e = 0.027), and CD8+ cell percentage (HR:1.946, 95%CI:1.529 - 2.759, \u003cem\u003eP\u003c/em\u003e = 0.031) were independent prognostic factors for thyroid cancer patients(Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the results of the multivariate Cox regression analysis, a forest plot was constructed with variable assignments. As shown in Figure 2，in terms of age, patients aged \u0026gt;50 years had a HR of 1.765 (95%CI: 1.475–2.719, \u003cem\u003eP\u003c/em\u003e = 0.034) compared to those ≤50 years, indicating a significantly higher risk of poor prognosis in older patients. For pathological subtypes, follicular carcinoma exhibited a markedly elevated HR of 2.349 (95%CI: 2.362 – 4.753, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) relative to papillary carcinoma, suggesting a worse prognosis for follicular carcinoma patients. Additionally, the presence of lymph node metastasis (HR:2.81, 95% CI: 1.92–4.10, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), distant metastasis (HR: 3.45, 95% CI: 2.30–5.18, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and elevated serum markers including SII ≥576.48 (HR:1.98, 95% CI: 1.35–2.90, \u003cem\u003eP\u003c/em\u003e = 0.002), Tg ≥23.99 μg/L (HR:1.72, 95% CI: 1.20–2.47, \u003cem\u003eP\u003c/em\u003e = 0.008), and TgAb \u0026gt;53.10 IU/mL (HR:1.65, 95% CI: 1.15–2.36, \u003cem\u003eP\u003c/em\u003e = 0.016) were all associated with higher hazard ratios ( \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). Conversely, lower risk was observed in patients with CD3+ cell percentage \u0026lt;70.15% (HR:0.68, 95% CI: 0.47–0.99, \u003cem\u003eP\u003c/em\u003e = 0.054) and CD8+ cell percentage \u0026lt;28.86% (HR:0.62, 95% CI: 0.39–0.98, \u003cem\u003eP\u003c/em\u003e = 0.043), with the latter achieving statistical significance.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThyroid cancer is the most common malignant tumor of the endocrine system, accounting for approximately 1% of all systemic malignancies, and includes four pathological types: papillary carcinoma, follicular carcinoma, anaplastic carcinoma, and medullary carcinoma\u003csup\u003e[9]\u003c/sup\u003e. The pathogenesis of thyroid cancer remains unclear, with multiple etiological factors implicated, including dysregulated inflammatory responses. First, inflammation can directly contribute to carcinogenesis; second, it may act on the tumor microenvironment (TME) to mediate tumor progression\u003csup\u003e[10, 11]\u003c/sup\u003e. The tumor microenvironment (TME) is a complex system that includes an immune microenvironment primarily composed of immune cells, alongside a non-immune microenvironment characterized by fibroblasts\u003csup\u003e[8, 12]\u003c/sup\u003e. Lymphocytes are crucial to the immune system and significantly influence its functional status.\u003c/p\u003e\u003cp\u003eThe systemic immune-inflammation index (SII)\u003csup\u003e[13]\u003c/sup\u003e, a novel hematological marker based on neutrophil, lymphocyte, and platelet counts, has shown prognostic significance in cancers such as lung\u003csup\u003e[14]\u003c/sup\u003e, esophageal\u003csup\u003e[15]\u003c/sup\u003e, and gastric cancers\u003csup\u003e[16]\u003c/sup\u003e. In this study, SII levels were significantly higher in thyroid cancer patients than in healthy controls and individuals with thyroid nodules. Furthermore, SII levels differed markedly between follicular carcinoma and papillary carcinoma patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as well as between patients with and without lymph node or distant metastasis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that inflammatory responses participate in thyroid cancer development and progression and may aid in assessing disease severity and prognosis. These findings align with the study by Schumm MA et al. \u003csup\u003e[17]\u003c/sup\u003e. Additionally, Huang et al.\u003csup\u003e[18]\u003c/sup\u003e demonstrated that SII is an independent risk factor for lymph node metastasis in endometrial cancer, further supporting the close relationship between thyroid cancer and inflammation. Chronic thyroiditis may even harbor potential for malignant transformation. Mechanistically, SII reflects the balance between pro-tumor inflammation and anti-tumor immunity, tumor cell proliferation, invasiveness, and metastasis, thereby influencing prognosis \u003csup\u003e[19]\u003c/sup\u003e. Elevated SII, often driven by neutrophilia, promotes an immunosuppressive TME via reactive oxygen species and cytokines, facilitating thyroid cancer proliferation and metastasis, while lymphocytopenia reduces tumor cell clearance\u003csup\u003e[20, 21]\u003c/sup\u003e. Thus, thyroid carcinogenesis is closely linked to systemic inflammatory and immune status\u003csup\u003e[22, 23]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur results revealed optimal prognostic survival rates in thyroid cancer patients when the percentages of CD3\u0026thinsp;+\u0026thinsp;cells % (\u0026ge;\u0026thinsp;62.5), CD4\u0026thinsp;+\u0026thinsp;cells % (\u0026gt;\u0026thinsp;37.6), CD8\u0026thinsp;+\u0026thinsp;cells % (\u0026le;\u0026thinsp;39.6), CD19\u0026thinsp;+\u0026thinsp;cells % (\u0026ge;\u0026thinsp;5.8), and CD56\u0026thinsp;+\u0026thinsp;cells % (\u0026lt;\u0026thinsp;16.8) fell within specific thresholds. T lymphocytes, particularly CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;subsets, are central to cellular immunity and anti-tumor responses. In this study, CD3+%, CD4+%, and CD8+% all significantly impacted prognosis. Yang et al. \u003csup\u003e[24]\u003c/sup\u003e found that CD4\u0026thinsp;+\u0026thinsp;T-cell imbalance promotes cervical cancer progression, whereas Giraldo et al. \u003csup\u003e[25]\u003c/sup\u003ereported that high CD8\u0026thinsp;+\u0026thinsp;T-cell levels correlate with shorter progression-free survival (PFS) and overall survival (OS) in renal and prostate cancers. Notably, multivariate analysis identified CD8+% as an independent prognostic factor in thyroid cancer.Natural killer (NK) cells, the first line of anti-tumor defense, rapidly recognize and eliminate tumor cells, reducing metastatic burden and prolonging survival in preclinical models. Studies link NK cell activity to improved survival in hepatocellular carcinoma\u003csup\u003e[26]\u003c/sup\u003e, clear cell renal cell carcinoma\u003csup\u003e[27]\u003c/sup\u003e, and prostate cancer\u003csup\u003e[28]\u003c/sup\u003e. B cells, activated by tumor antigens with CD4\u0026thinsp;+\u0026thinsp;T-cell help, secrete anti-tumor antibodies, though their prognostic role remains debated. For instance, B-cell infiltration negatively correlates with survival in ovarian cancer with pleural effusion, yet associates with favorable outcomes in gastric cancer with tertiary lymphoid structures (TLSs)\u003csup\u003e[28]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAutoimmune disorders are also implicated in thyroid cancer pathogenesis and post-operative recurrence/metastasis\u003csup\u003e[29]\u003c/sup\u003e. Thyroglobulin (Tg), produced by thyroid follicular cells, is minimally released into circulation under normal conditions. Elevated serum Tg triggers autoimmune responses, inducing thyroglobulin antibody (TgAb) production, which correlates with disease progression\u003csup\u003e[30, 31]\u003c/sup\u003e. Post-thyroidectomy monitoring of Tg and TgAb aids in detecting residual disease or recurrence\u003csup\u003e[32]\u003c/sup\u003e. Our study showed higher serum Tg and TgAb levels in patients with lymph node or distant metastasis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting their predictive value for post-operative metastasis. Elevated Tg reflects disease severity, while residual tumor cells post-surgery drive Tg overproduction and TgAb generation. Higher levels indicate immune dysregulation and may serve as biomarkers for disease progression\u003csup\u003e[33, 34]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn conclusion, thyroid carcinogenesis is closely associated with immune dysfunction. Impaired immunity, coupled with inflammatory cytokine release, exacerbates metastasis and recurrence risks. A balanced peripheral immune microenvironment correlates with optimal prognosis. Thus, monitoring these biomarkers\u0026mdash;SII, immune cell subsets, Tg, and TgAb\u0026mdash;may enhance prognostic prediction in thyroid cancer patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXZ performed the analysis and wrote the manuscript, FL supervised the statistical analysis, XZ and WW completed data collection, CP supervised the analysis, YQ revised the manuscript. All authors reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupported by Fundamental Research Program of Shanxi Province (202303021222370)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used to support the findings of this study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur present study was conducted in accordance with the Declaration of Helsinki (1964), and also approved by the Medical Ethics Committee of Shanxi Province Cancer Hospital. The Medical Ethics Committee of Shanxi Province Cancer Hospital waived the requirement of written informed consent for participation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWENG H Y, YAN T, QIU W W, et al. Long-term outcomes and prognostic factors in papillary thyroid microcarcinoma patients with distant metastases [J]. Endocrine, 2022, 75(2): 495-507.\u003c/li\u003e\n\u003cli\u003eRUIZ PARDO J, R\u0026iacute;OS A, RODR\u0026iacute;GUEZ J M, et al. Risk Factors of Metastatic Lymph Nodes in Papillary Thyroid Microcarcinoma [J]. Cirugia espanola, 2020, 98(4): 219-25.\u003c/li\u003e\n\u003cli\u003eBONJOC K J, YOUNG H, WARNER S, et al. Thyroid cancer diagnosis in the era of precision imaging [J]. Journal of thoracic disease, 2020, 12(9): 5128-39.\u003c/li\u003e\n\u003cli\u003eLI M, LI Q, ZOU C, et al. Application and recent advances in conventional biomarkers for the prognosis of papillary thyroid carcinoma [J]. Frontiers in oncology, 2025, 15: 1598934.\u003c/li\u003e\n\u003cli\u003eAGARWAL S, BYCHKOV A, JUNG C K. Emerging Biomarkers in Thyroid Practice and Research [J]. Cancers, 2021, 14(1).\u003c/li\u003e\n\u003cli\u003eIBRAHIMPASIC T, GHOSSEIN R, SHAH J P, et al. Poorly Differentiated Carcinoma of the Thyroid Gland: Current Status and Future Prospects [J]. Thyroid : official journal of the American Thyroid Association, 2019, 29(3): 311-21.\u003c/li\u003e\n\u003cli\u003eCEOLIN L, DUVAL M, BENINI A F, et al. Medullary thyroid carcinoma beyond surgery: advances, challenges, and perspectives [J]. Endocrine-related cancer, 2019, 26(9): R499-r518.\u003c/li\u003e\n\u003cli\u003eCUNHA L L, WARD L S. Translating the immune microenvironment of thyroid cancer into clinical practice [J]. Endocrine-related cancer, 2022, 29(6): R67-r83.\u003c/li\u003e\n\u003cli\u003eZHANG T, HE L, WANG Z, et al. The Differences Between Multifocal and Unifocal Papillary Thyroid Carcinoma in Unilateral Lobe: A Meta-Analysis [J]. Frontiers in oncology, 2021, 11: 657237.\u003c/li\u003e\n\u003cli\u003eLEWINSKI A, SLIWKA P W, STASIOLEK M. Dendritic cells in autoimmune disorders and cancer of the thyroid [J]. Folia histochemica et cytobiologica, 2014, 52(1): 18-28.\u003c/li\u003e\n\u003cli\u003eZHANG Z, XU T, QIN W, et al. Upregulated PTPN2 induced by inflammatory response or oxidative stress stimulates the progression of thyroid cancer [J]. Biochemical and biophysical research communications, 2020, 522(1): 21-5.\u003c/li\u003e\n\u003cli\u003eJAUME J C. Thyroid Cancer-The Tumor Immune Microenvironment (TIME) over Time and Space [J]. Cancers, 2025, 17(5).\u003c/li\u003e\n\u003cli\u003eVURAL S, MUHTAROĞLU A, G\u0026uuml;NG\u0026ouml;R M. Systemic immune-inflammation index: A new marker in differentiation of different thyroid diseases [J]. Medicine, 2023, 102(31): e34596.\u003c/li\u003e\n\u003cli\u003eYANG C, ZHANG Y, WANG R, et al. IL-10(+)CD19(+) regulatory B cells induce CD4(+)Foxp3(+)regulatory T cells in serum of cervical cancer patients [J]. Autoimmunity, 2024, 57(1): 2290909.\u003c/li\u003e\n\u003cli\u003eFU M, LI Z, MA J, et al. Study on the predictive value of pretreatment peripheral blood inflammatory markers regarding immunotherapy in patients with inoperable advanced or locally advanced oesophageal squamous cell carcinoma [J]. Scandinavian journal of gastroenterology, 2024, 59(6): 722-9.\u003c/li\u003e\n\u003cli\u003eDING P, GUO H, SUN C, et al. Combined systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI) predicts chemotherapy response and prognosis in locally advanced gastric cancer patients receiving neoadjuvant chemotherapy with PD-1 antibody sintilimab and XELOX: a prospective study [J]. BMC gastroenterology, 2022, 22(1): 121.\u003c/li\u003e\n\u003cli\u003eSCHUMM M A, SHU M L, HUGHES E G, et al. Prognostic Value of Preoperative Molecular Testing and Implications for Initial Surgical Management in Thyroid Nodules Harboring Suspected (Bethesda V) or Known (Bethesda VI) Papillary Thyroid Cancer [J]. JAMA otolaryngology-- head \u0026amp; neck surgery, 2023, 149(8): 735-42.\u003c/li\u003e\n\u003cli\u003eHUANG H, LIU Q, ZHU L, et al. Prognostic Value of Preoperative Systemic Immune-Inflammation Index in Patients with Cervical Cancer [J]. Scientific reports, 2019, 9(1): 3284.\u003c/li\u003e\n\u003cli\u003eSHERMAN S I J B P. Targeted therapy of thyroid cancer [J]. 2010, 80(5): 592-601.\u003c/li\u003e\n\u003cli\u003eBAUER A T, GORZELANNY C, GEBHARDT C, et al. Interplay between coagulation and inflammation in cancer: Limitations and therapeutic opportunities [J]. Cancer treatment reviews, 2022, 102: 102322.\u003c/li\u003e\n\u003cli\u003eYANG R, CHANG Q, MENG X, et al. Prognostic value of Systemic immune-inflammation index in cancer: A meta-analysis [J]. Journal of Cancer, 2018, 9(18): 3295-302.\u003c/li\u003e\n\u003cli\u003eMENICALI E, GUZZETTI M, MORELLI S, et al. Immune Landscape of Thyroid Cancers: New Insights [J]. Frontiers in endocrinology, 2020, 11: 637826.\u003c/li\u003e\n\u003cli\u003eFERRARI S M, FALLAHI P, GALDIERO M R, et al. Immune and Inflammatory Cells in Thyroid Cancer Microenvironment [J]. International journal of molecular sciences, 2019, 20(18).\u003c/li\u003e\n\u003cli\u003eXIAO R, TIAN Y, ZHANG J, et al. Increased Siglec-9/Siglec-9L interactions on NK cells predict poor HCC prognosis and present a targetable checkpoint for immunotherapy [J]. Journal of hepatology, 2024, 80(5): 792-804.\u003c/li\u003e\n\u003cli\u003eN\u0026uacute;\u0026ntilde;EZ S Y, TROTTA A, REGGE M V, et al. Tumor-associated macrophages impair NK cell IFN-\u0026gamma; production and contribute to tumor progression in clear cell renal cell carcinoma [J]. European journal of immunology, 2024, 54(6): e2350878.\u003c/li\u003e\n\u003cli\u003eMAO F, YANG C, LUO W, et al. Peripheral blood lymphocyte subsets are associated with the clinical outcomes of prostate cancer patients [J]. International immunopharmacology, 2022, 113(Pt A): 109287.\u003c/li\u003e\n\u003cli\u003eDONG H P, ELSTRAND M B, HOLTH A, et al. NK- and B-cell infiltration correlates with worse outcome in metastatic ovarian carcinoma [J]. American journal of clinical pathology, 2006, 125(3): 451-8.\u003c/li\u003e\n\u003cli\u003eSAKIMURA C, TANAKA H, OKUNO T, et al. B cells in tertiary lymphoid structures are associated with favorable prognosis in gastric cancer [J]. The Journal of surgical research, 2017, 215: 74-82.\u003c/li\u003e\n\u003cli\u003ePAGANO L, MELE C, SAMA M T, et al. Thyroid cancer phenotypes in relation to inflammation and autoimmunity [J]. Frontiers in bioscience (Landmark edition), 2018, 23(12): 2267-82.\u003c/li\u003e\n\u003cli\u003eLU Y, ZHAO H, LIU C, et al. The role of preoperative serum thyroglobulin in the diagnosis and treatment of differentiated thyroid cancer: a systematic review and meta-analysis [J]. Frontiers in oncology, 2024, 14: 1426785.\u003c/li\u003e\n\u003cli\u003eZHAO Y, MU Z, LIANG D, et al. Prognostic value of postoperative anti-thyroglobulin antibody in patients with differentiated thyroid cancer [J]. Frontiers in endocrinology, 2024, 15: 1354426.\u003c/li\u003e\n\u003cli\u003eSPENCER C, FATEMI S. Thyroglobulin antibody (TgAb) methods - Strengths, pitfalls and clinical utility for monitoring TgAb-positive patients with differentiated thyroid cancer [J]. Best practice \u0026amp; research Clinical endocrinology \u0026amp; metabolism, 2013, 27(5): 701-12.\u003c/li\u003e\n\u003cli\u003eVITIELLO A, LA PORTA R, TRAMA U, et al. Pandemic COVID-19, an update of current status and new therapeutic strategies [J]. Naunyn-Schmiedeberg\u0026apos;s archives of pharmacology, 2022, 395(10): 1159-65.\u003c/li\u003e\n\u003cli\u003eNTOTSIKAS K, LAZARIOTI S, DARAKI V, et al. Thyroglobulin as a Rapid and Cost-Effective Biomarker for Diagnosis of Thyroid Carcinoma Brain Metastasis: A Case Report of a Patient with Metastatic Hurthle Cell Thyroid Carcinoma [J]. The American journal of case reports, 2023, 24: e939025.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTab\u003c/strong\u003e\u003cstrong\u003ele\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe clinical characteristics of 430 thyroid cancer patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eMale/Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e91/339\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026le;50years/\u0026gt;50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e256/174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003epapillarycarcinoma/follicular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e306/124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003elesion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eSingle/multiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e386/44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eI\u0026ndash;II/III\u0026ndash;IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e294/136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph node status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eNegative/Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e267/163\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistant metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eNegative/Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e396/34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe comparison of SII, Tg, and TgAb levels among thyroid cancer group, thyroid nodule group, and healthy control group\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTgAb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy Control Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e216.13\u0026plusmn;67.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e25.87\u0026plusmn;3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e80.74\u0026plusmn;19.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThyroid Nodule\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e332.57\u0026plusmn;123.64*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e52.79\u0026plusmn;5.81*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e198.84\u0026plusmn;56.63*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThyroid Cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e576.35\u0026plusmn;136.79\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e85.69\u0026plusmn;22.38*\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e316.05\u0026plusmn;105.78*\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e176.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e24.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e86.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: Data are presented as mean \u0026plusmn; SD; * \u003cem\u003eP\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 vs. Healthy Control Group; # \u003cem\u003eP\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 vs. Thyroid Nodule Group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eThe comparison of SII, Tg, and TgAb levels in thyroid cancer patients with different clinicopathological characteristics\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"661\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTg(\u0026mu;g/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTgAb(IU/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e3.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e2.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e579.63\u0026plusmn;26.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e23.95\u0026plusmn;5.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e52.36\u0026plusmn;4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e575.68\u0026plusmn;37.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e24.02\u0026plusmn;6.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e53.26\u0026plusmn;5.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e1.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026le;50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e574.59\u0026plusmn;32.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e22.69\u0026plusmn;5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e51.96\u0026plusmn;4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e＞50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e577.89\u0026plusmn;42.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e23.74\u0026plusmn;4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e52.59\u0026plusmn;5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological type\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e17.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e2.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eFollicular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e577.80\u0026plusmn;43.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e20.36\u0026plusmn;6.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e52.48\u0026plusmn;4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003ePapillary carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e503.59\u0026plusmn;35.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e21.38\u0026plusmn;6.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e53.26\u0026plusmn;5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph node\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003estatus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e13.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e19.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e14.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e593.23\u0026plusmn;55.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e38.79\u0026plusmn;7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e72.36\u0026plusmn;9.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e400.26\u0026plusmn;69.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e18.26\u0026plusmn;6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e32.68\u0026plusmn;7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistant metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e21.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e16.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e21.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e613.68\u0026plusmn;75.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e46.29\u0026plusmn;8.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e69.98\u0026plusmn;8.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e564.59\u0026plusmn;68.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e23.68\u0026plusmn;8.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e28.69\u0026plusmn;6.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eThe univariate and multivariate analysis of thyroid cancer patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"619\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eunivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 256px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emultivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e0.543-4.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.244-3.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.326-2.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.921-4.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.362-4.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymph node metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.072-2.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.324-3.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistant metastasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.509-3.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.235-3.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.298-4.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.016-4.679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.026-3.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.123-2.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTgAb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.023-2.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.426-3.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD3+ cell\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.849-3.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e0.849-1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD4+ cell\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.056-1.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e0.746-1.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD8+ cell\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.736-3.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.529-2.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD56+ cell\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1.231-2.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD19+ cell\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e0.659-1.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:Gender: male vs. female, Age:(\u0026le;50years vs. \u0026gt;50 years), Pathological type: papillary carcinoma vs. follicular carcinoma, Lymph node metastasis: negative vs. positive, Distant metastasis: negative vs. positive, SII: (\u0026lt;576.48 vs. \u0026ge;576.48 ), Tg: (\u0026lt;23.99 \u0026mu;g/L vs. \u0026ge;23.99 \u0026mu;g/L), TgAb:(\u0026lt;53.10 IU/mL vs. \u0026ge;53.10 IU/mL), CD3+ cells(%):(\u0026lt;70.15% vs. \u0026ge;70.15%), CD4+ cells (%):( \u0026lt;36.64% vs. \u0026ge;36.64%), CD8+ cells (%):(\u0026lt;28.86% vs. \u0026ge;28.86% )\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Thyroid Cancer, Inflammatory Index, Immune Function, Clinical Characteristics, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7857190/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7857190/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u0026nbsp;\u003c/strong\u003eThis study aimed to investigate the clinical value of preoperative peripheral blood inflammatory indices and immune function in evaluating clinicopathological characteristics and prognosis in thyroid cancer patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u0026nbsp;\u003c/strong\u003eA total of 430 thyroid cancer patients who underwent radical surgery at Shanxi Provincial Cancer Hospital between January 2017 and June 2019 were enrolled as the thyroid cancer group. Additionally, 50 healthy individuals from the hospital’s health examination center during the same period were included as the healthy control group, and 100 patients with thyroid nodules were selected as the thyroid nodule group. Data collected for all participants included routine blood parameters (e.g., neutrophil, lymphocyte, and platelet counts), immune function indicators (e.g., CD3+, CD4+, CD8+, CD19+, and CD56+ cell percentages), and clinicopathological characteristics (e.g., gender, age, pathological type, number of lesions, and metastasis status). Retrospective analysis of clinical data was performed. Survival curves and Cox regression analysis were utilized to identify factors influencing thyroid cancer prognosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e Patients in the thyroid cancer group had higher levels of SII and Tg and TgAb than those in the healthy control group (\u003cem\u003eP\u003c/em\u003e = 0.018, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eP \u003c/em\u003e= 0.007). The levels of SII and Tg and TgAb were higher in patients in the thyroid cancer group than in the thyroid nodule group (\u003cem\u003eP \u003c/em\u003e= 0.022, \u003cem\u003eP \u003c/em\u003e= 0.043, \u003cem\u003eP \u003c/em\u003e= 0.038). Clinicopathologic results showed that follicular carcinoma (\u003cem\u003eP \u003c/em\u003e= 0.008), occurrence of lymph node metastasis (\u003cem\u003eP \u003c/em\u003e= 0.016), and distant metastasis (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001) of thyroid cancer patients had higher SII than those with papillary carcinoma, no lymph node metastasis and distant metastasis. Serum Tg and TgAb levels were higher in patients with thyroid cancer who also had lymph node metastasis (\u003cem\u003eP\u003c/em\u003e\u003csub\u003eTg\u003c/sub\u003e \u0026lt; 0.001, \u003cem\u003eP\u003c/em\u003e\u003csub\u003eTgAb \u003c/sub\u003e= 0.011) and distant metastasis (\u003cem\u003eP\u003c/em\u003e\u003csub\u003eTg\u003c/sub\u003e \u0026lt; 0.001, \u003cem\u003eP\u003c/em\u003e\u003csub\u003eTgAb\u003c/sub\u003e \u0026lt; 0.001) than in those who did not. The results of OS survival curves for immune-related factors showed that patients with thyroid cancer had the highest prognostic survival rates when the percentage expression of CD3+ cells, CD4+ cells, CD8+ cells, CD19+ cells, and CD56+ cells were between ≥62.5%, \u0026gt; 37.6%, ≤ 39.6%, ≥ 5.8%, and \u0026lt; 16.8%, respectively. The results of multifactorial analysis showed that age (\u003cem\u003eP \u003c/em\u003e= 0.019), pathologic type (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001), presence of lymph node metastasis (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001), presence of distant metastasis (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001), preoperative SII (\u003cem\u003eP \u003c/em\u003e= 0.001), Tg (\u003cem\u003eP \u003c/em\u003e= 0.008), TgAb (\u003cem\u003eP \u003c/em\u003e= 0.027) levels, and CD8+ cells (%) (\u003cem\u003eP \u003c/em\u003e= 0.013) were independent influences on the prognosis of thyroid cancer patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003ePreoperative assessment of peripheral blood inflammatory indices and immune function aids in evaluating disease progression and prognosis in thyroid cancer patients. Optimal prognosis is achieved when peripheral immune cells are maintained in a dynamic equilibrium.\u003c/p\u003e","manuscriptTitle":"Preoperative Systemic Inflammatory-Immune Status: A Predictor of Survival in Thyroid Carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 06:43:04","doi":"10.21203/rs.3.rs-7857190/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"262575402701597698731259324887644286300","date":"2026-05-09T02:42:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-07T09:34:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102200385134047962665273537260587224632","date":"2026-04-04T06:36:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337280746743989536309554749869511752455","date":"2026-02-02T22:55:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20799164945493734528691292565946325555","date":"2025-12-24T21:34:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-13T12:58:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T23:59:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-14T23:58:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-10-14T09:53:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3dfe8388-df33-4fc5-a8d6-b4c0ef6831c8","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"262575402701597698731259324887644286300","date":"2026-05-09T02:42:55+00:00","index":235,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-26T06:43:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 06:43:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7857190","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7857190","identity":"rs-7857190","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}