Multi-factor Evaluation of Tumor-infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma and its Prognostic Value

Multi-factor Evaluation of Tumor-infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma and its Prognostic Value | 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 Primary research Multi-factor Evaluation of Tumor-infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma and its Prognostic Value susheng miao, xueying wang, Erliang Guo, Lunhua Guo, Changming An, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-323430/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Laryngeal squamous cell carcinoma (LSCC) is a heterogeneous disease. In clinical practice, patients with similar clinicopathological characteristics often show different outcomes. This study evaluated the levels of primary LSCC intratumoral infiltrating lymphocytes (iTILs), tumor-infiltrating lymphocyte volume (TILV), frontier tumor-infiltrating lymphocytes (fTILs), and their relations to the patient's clinical outcome. Materials and methods: According to the 2017 study of the International TILs Working Group, hematoxyline and eosin-stained slides from 412 patients were evaluated for their morphology of tumor immune infiltration status. Results : Kaplan-Meier analysis showed that high levels of iTILs, TILV, and fTILs were significantly correlated with OS (all P<0.05). Cox regression model analysis showed that high levels of iTILs, TILV, and fTILs were independently associated with better OS (all P<0.05). Conclusion : Local inflammatory markers in patients with laryngeal squamous cell carcinoma, especially the levels of iTILs, TILV, and fTILs, are reliable prognostic factors. Cancer Biology Laryngeal squamous cell carcinoma (LSCC) intratumoral infiltrating lymphocytes (iTILs) tumor-infiltrating lymphocyte volume (TILV) frontier tumor-infiltrating lymphocytes (fTILs) overall survival (OS) recurrence-free survival (RFS) Figures Figure 1 Figure 2 Figure 3 Introduction Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. At present, the treatment strategy of LSCC includes a combination of CO 2 laser-assisted oral surgery, open surgery, oral robotic surgery, radiotherapy, and chemotherapy[ 1 ]. However, despite the development of improved strategies and more accurate treatments, the 5-year survival rate of laryngeal squamous cell carcinoma has decreased from 66–63% unfortunately in the past 40 years [ 2 ]. In recent years, oncology research on LSCC has been focusing on the tumor biology, especially for the advanced LSCC, to find prognostic markers and potential therapeutic targets [ 3 – 6 ]. Tumor-infiltrating lymphocytes (TILs) are a heterogeneous group of lymphocytes that are found in the tumor microenvironment. Mainly T lymphocytes, TILs participate in the formation of tumor immune microenvironment locally and the body's anti-tumor immune response. Current studies have found that TILs are responsible for the microenvironment composition and effects in various types of malignant tumors, such as head and neck tumors, melanoma, breast cancer, bladder cancer, urothelial tumors, ovarian cancer, colorectal cancer, kidney cancer, prostate cancer, and lung cancer[ 7 – 10 ]. It has also been reported that the immune response of the tumor cell matrix has important prognostic and predictive significance [ 8 ]. The dysfunction of the immune system is a key factor in the occurrence and development of LSCC, and immune checkpoints are an important mechanism for tumor immune escape[ 11 ]. According to these studies, the presence of TILs is an important biomarker for predicting cervical lymph node metastasis in LSCC. It is therefore necessary to determine the pathological markers that predict survival and recurrence in order to optimize the treatment and reduce potentially preventable adverse effects on patients. However, there is no research up to date that determines the relationship between TIL and the prognosis of LSCC. The TIL-related parameters evaluated are the following: the intratumoral infiltrating lymphocyte (iTILs), tumor-infiltrating lymphocyte volume (TILV), and the frontier tumor-infiltrating lymphocytes (fTILs). The iTIL score is defined as the percentage of tumor islands occupied by lymphocytes. TILV=% stroma in tumor×% stroma iTILs. Frontier TILs (fTILs) are defined as the percentage of infiltrating lymphocytes in the tissues before tumor invasion. The International Immunological Biomarker Working Group used H&E-stained sections to evaluate TILs of solid tumors in 2017 and developed a standardized method for the microscopic detection of iTILs in H&E-stained sections[ 12 ]. These standards are repeatable and applied to daily practice [ 13 ]. However, the evaluation of the iTILs does not involve the tumor-stroma ratio and the percentage of tumor-infiltrating lymphocytes in the invasion front, which is one-sided for the evaluation of the local immune status of the tumor. To our knowledge, this study is the first to evaluate the relation between lymphocyte infiltration in different parts of the tumor and the prognosis and recurrence of LSCC after surgery. We first proposed the concept of TILV and fTILs at LSCC. Although the histological evaluation of tumor-infiltrating lymphocytes in our H&E-stained samples did not reveal different subpopulations of lymphocytes, it might still be a useful biomarker for evaluating tumor behavior. This method is advantageous in several ways. It is cost-effective and does not require expensive or specific tools or antibodies. At the same time, it is also easy to incorporate into standard pathology reports. In our study, we conducted a detailed assessment of the real-time immune status in the three-dimensional tumor structure, and explored the relation between the TILs (iTILs, TILV and fTILs) and the LSCC outcomes overall survival (OS) and recurrence-free survival (RFS). Materials And Methods 1.Patients A total of 412 cases were retrospectively analyzed. These patients were all diagnosed pathologically and underwent laryngectomy at the Department of Head and Neck Nasopharyngeal Surgery, Affiliated Tumor Hospital of Harbin Medical University or the Head and Neck Department of Tumor Hospital of Chinese Academy of Medical Sciences between December 2011 and December 2014. This study was reviewed and approved by the ethics committees of the two institutions, and proceeded in accordance with the principles of the Declaration of Helsinki and its amendments. All participants provided informed consents to participate in the study. The clinical data (sex, age, BMI, history of drinking and smoking, tumor location, differentiation, TNM, T-stage and N-stage,) and follow-up information (clinical outcome and survival time) were collected through from the electronic medical records. The prescribed inclusion criteria are as follows: 1) LSCC confirmed by histopathology; 2) No history of anti-cancer treatment; 3) Complete clinical, laboratory, imaging, and follow-up data; 4) The remaining paraffin-fixed tissue is sufficient, and the structure is clear; 5) Has at least one slice to assess the edge of tumor invasion; 6) No history of other malignant tumors and no distant metastasis. In this study, a total of 412 patients with laryngeal squamous cell carcinoma were enrolled. There were 2 to 3 pathological tissue slices in each case, and a total of 1112 pathological tissue slices were reviewed. The samples were reviewed by two pathologists in a double-blind manner, and the patients were staged according to the eighth edition of the American Joint Committee on Cancer (AJCC) staging system. Table 1 lists the main clinicopathological characteristics of the patients. 2. Experimental methods 2.1 Tumor tissue sampling and laryngeal cancer tissue wax block preparation 1) Surgically excised laryngeal tissue specimens are cut and fixed with 10% formalin solution; 2) 3*3*0.5 cm tissue blocks are cut from the laryngeal cancer tissue and placed in a tissue embedding box and placed in 10% formalin solution; 3) Laryngeal cancer tissue blocks are dehydrated by gradient alcohol of low concentration to high concentration; 4) Laryngeal cancer tissue blocks are soaked in xylene to remove alcohol transparent tissue; 5) Laryngeal cancer tissue blocks are embedded in paraffin to make laryngeal cancer Tissue wax blocks. 2.2 Preparation of white slices of laryngeal cancer tissue 1) Slice the laryngeal cancer tissue wax blocks with a microtome 4 µm in thickness; 2) Place the slices in 30°C water and flatten with a glass slide; 3) Bake the slides at 72°C for 1-2 hours. 2.3 Hematoxylin-Eosin staining (H&E staining) 1) White slices of laryngeal cancer tissue are deparaffinized in xylene solution; 2) White slices are hydrated with high to low concentration gradient alcohol; 3) White slices are stained with hematoxylin 4) After washing, the sections are placed in hydrochloric acid alcohol to return to blue and differentiated in the differentiation solution; 5) After the sections are rinsed, they are dehydrated in low to high concentration gradient alcohol; 6) The sections are stained in alcohol and eosin; 7) The sections are placed Dehydrate in pure alcohol; 8) place the slices in xylene to be transparent; 9) use neutral resin to seal the slices after drying. 3. TIL histological scoring in laryngeal cancer tissues We evaluated TIL-related parameters according to the scoring method introduced by the International Immuno-Tumor Biomarker Working Group recently[14] . The evaluation of iTILs does not include any stromal areas that are not directly related to the tumor. In addition, areas of fibrosis or central necrosis are not included in the iTILs assessment. The percentage of iTILs was evaluated in 2 areas of each sample (the front and the center of the tumor invasion). The TIL working group guidelines recommend "Don't focus on hot spots" 1.2. Therefore, the average value of TIL in the region should be used when reporting iTILs and fTILs. We evaluated at least five regions to assess the average value of TIL. As recommended, we used the whole untrimmed tumor sections. Each case in our study had at least one representative section (4 - 5 µm). Low-quality tumor sections, such as tumor sections without tumor-stroma interface, were excluded. 4. Follow-up methods The demographic, clinicopathological and treatment data of each patient were extracted from the electronic medical record system. The demographic data and clinicopathological characteristics of the patients were collected from the database of two institutions/hospitals. All patients who met the inclusion criteria were followed up by a combination of inpatient case review and telephone through January, 2020. The median follow-up time was 59.9 months (range: 1.9-83.2 months). The median overall survival time was 68.1 months (95% CI: 65.6-70.5 months). The primary outcome was overall survival (OS) from diagnosis to death and the second outcome was recurrence-free survival (RFS) from cancer diagnosis to disease recurrence or metastasis or cancer specific death, whichever came first. 5. Data analysis We first divided the patients into two groups according to the optimal cut-off point of each iTIL, TILV and fTILs level, which was determined by Receiver operating characteristic (ROC) curves with overall survival status as the dependent variable (0, alive; 1, death). We reported means and standard deviations or counts and frequencies for continuous or categorical variables, respectively. Differences in continuous and categorical covariates between groups were compared with Student’s t tests and chi-square (χ2) tests, respectively. We then conducted univariate and multivariate Cox regression analyses and reported hazard ratios (HRs) and 95% confidence intervals (CIs) to assess the association between iTILs, TILV and fTILs and the prognosis of laryngocarcinoma patients. The likelihood ratio backward stepwise selection was used for the multivariate Cox regression analysis. Kaplan-Meier curves and log-rank tests were then conducted to compare the OS and RFS rates between groups. Two-sided statistical significance was defined as P < 0.05. ROC analyses were performed with MedCalc version 12.6.1.0, and all other statistical analyses were performed with SPSS Statistics version 23.0 (IBM, Inc., USA). Results Cutoff values for iTILs, TILV and fTILs According to the ROC curve, the areas under the curve (AUCs) of iTILs, TILV, and fTILs are 0.589 (95% CI 0.540-0.637, P=0.00319), 0.577 (95% CI 0.527-0.625, P=0.0308,) and 0.553 (95 % CI 0.503-0.602, P=0.0323) respectively, and the best cut-off values were 10%, 12% and 50% respectively (Fig.1). A total of 336 men (81.6%) and 76 women (18.4%) were eligible for this study. Most subjects (72.3%) had a current or past history of smoking. As shown in Table 1, 52.2% of patients had supraglottic squamous cell carcinoma, and 47.8% of patients had glottal laryngeal squamous cell carcinoma. Most patients (65.3%) had localized early tumors (T1 or T2), most (59.0%) being moderately or poorly differentiated. Survival analysis based on tumor inflammation markers In our study, 330 patients had higher iTILs (80.1%, Figure 2A), 82 patients had lower iTILs (19.9%, Figure 2B). The 5-year OS rate was significantly higher in the high iTILs group (75.76%) than in the low iTILs group (59.76%, p < 0.05, Figure 3A). When the patients were stratified into high TILV group (137 patients or 33.3%, Figure 2C) and low TILV group (275 patients or 66.7%, Figure 2D), the 5-year OS rate is significantly higher in the high TILV group (81.20%) than in the low TILC group (68.36%, p < 0.05, Figure 3B). Finally, we stratified the patients again, according to fTILs. 240 patients had higher fTILs (58.3%, Figure 2E), and 172 patients had lower fTILs (41.7%%, Figure 2F). The 5-year OS rate of the high fTILs group (77.50%) was significantly higher than that of the low fTILs group (65.70%, P<0.05, Figure 3C). Therefore, the levels of iTILs, TILV, and fTILs are related to the patient’s survival. Furthermore, we analyzed the levels of iTILs, TILV, and fTILs and the recurrence of the disease and found no significant correlation (P>0.05, Figure 2.) Single- and multiple-factor analyses Clinicopathological parameters, including the levels of iTILs, TILV and fTILs, and OS and RFS, were subjected to univariate multivariate analyses to determine independent predictors of OS and RFS in LSCC patients. BMI<24, history of drinking, low levels of differentiation, supraglottic carcinoma, high T/N stage or TNM, and low iTILs/TILV/fTILs levels were identified as predictors of poor prognosis (Table 1). These factors are determined by the single-factor analysis. Next, we established multiple linear regression models to observe the main effects of iTILs, TILV, and fTILs. age, alcohol consumption, and T4 tumor stage showed statistical significance in these three models. More importantly, the three linear regression models showed that high iTILs (P=0.002, HR: 0.518, 95%CI 0.341-0.785), high TILV (P=0.026, HR: 0.604, 95%CI: 0.387-0.943) and high FTILs (P=0.011, HR: 0.605, 95%CI: 0.410-0.892) were significantly correlated with better OS (Table 2). Therefore, we believe that high levels of iTILs, TILV, and fTILs are independent predictors of good prognosis. In the Cox regression model analysis to determine the statistically significant factors related to RFS, the relationship between the three factors and the recurrence was not found to be statistically significant, in either single-factor or multivariate analyses (Table 1 & 2). Table 1 Patient baseline characteristics and univariate analysis of OS and RFS Items No. (%) Univariate OS Univariate RFS HR 95% CI P-value HR 95% CI P-value Gender Male 336（81.6%） ref ref ref ref ref ref Female 76（18.4%） 0.980 0.610-1.574 0.932 0.893 0.492-1.618 0.708 Age (yr) <60 223（54.1%） ref ref ref ref ref ref ≥60 189（45.9%） 1.367 0.945-1.978 0.097 1.120 0.720-1.742 0.615 BMI (kg/m2) <24 273（66.3%） ref ref ref ref ref ref ≥24 139（33.7%） 0.577 0.374-0.889 0.013 0.754 0.464-1.226 0.255 Smoking No 114（27.7%） ref ref ref ref ref ref Yes 298（72.3%） 1.305 0.847-2.011 0.228 1.615 0.933-2.797 0.087 Alcohol No 226（54.9%） ref ref ref ref ref ref Yes 186（45.1%） 1.519 1.049-2.198 0.027 1.571 1.009-2.447 0.046 Initial Site supraglottic 215（52.2%） ref ref ref ref ref ref glottic larynx 197（47.8%） 0.611 0.417-0.895 0.011 0.681 0.435-1.068 0.094 Differentiation Low-moderate 243（59.0%） ref ref ref ref ref ref high 169（41.0%） 0.477 0.314-0.724 0.001 0.403 0.240-0.675 0.001 T-Stage T1 135（32.3%） ref ref ref ref ref ref T2 209（50.7%） 1.423 0.905-2.238 0.126 2.158 1.226-3.801 0.008 T3 52（12.6%） 2.204 1.251-3.883 0.006 1.820 0.826-4.012 0.137 T4 16（3.9%） 2.312 1.010-5.294 0.047 3.357 1.230-9.164 0.018 N-Stage N0 312（75.7%） ref ref ref ref ref ref N1 38（9.2%） 1.792 0.987-3.253 0.055 1.785 0.906-3.516 0.094 N2 62（15.1%） 3.941 2.609-5.954 <0.001 2.567 1.497-4.400 0.001 TNM Stage 1 119（28.9%） ref ref ref ref ref ref 2 150（36.4%） 1.166 0.668-2.037 0.589 2.013 1.053-3.848 0.034 3 71（17.2%） 2.042 1.129-3.691 0.018 2.327 1.119-4.838 0.024 4 72（17.5%） 4.416 2.594-7.516 <0.001 3.464 1.709-7.022 0.001 iTILs Lower 82（19.9%） ref ref ref ref ref ref Higher 330（80.1%） 0.545 0.363-0.818 0.003 1.025 0.584-1.798 0.933 TILV Lower 275（66.7%） ref ref ref ref ref ref Higher 137（33.3%） 0.548 0.354-0.850 0.007 1.179 0.748-1.857 0.478 fTILs Lower 172（41.7%） ref ref ref ref ref ref Higher 240（58.3%） 0.611 0.422-0.884 0.009 0.895 0.574-1.396 0.626 Table 2 Multi-model multi-factor analysis of factors related to LSCC OS Items Multivariate iTILs Multivariate TILV Multivariate fTILs HR 95% CI P-value HR 95% CI P-value HR 95% CI P-value Gender Male（ref） ref ref ref ref ref ref ref ref ref Female 1.065 0.618-1.836 0.820 1.057 0.613-1.820 0.843 1.249 0.719-2.169 0.430 Age (yr) <60 （ref） ref ref ref ref ref ref ref ref ref ≥60 1.500 1.029-2.186 0.035 1.500 1.029-2.188 0.035 1.520 1.042-2.219 0.030 BMI (kg/m2) <24 （ref） ref ref ref ref ref ref ref ref ref ≥24 0.667 0.430-1.033 0.070 0.670 0.432-1.040 0.074 0.665 0.429-1.031 0.068 Alcohol No （ref） ref ref ref ref ref ref ref ref ref Yes 1.533 1.018-2.308 0.041 1.525 1.014-2.292 0.043 1.632 1.080-2.467 0.020 Initial Site supraglottic ref ref ref ref ref ref ref ref ref glottic larynx 1.068 0.660-1.728 0.790 1.114 0.685-1.811 0.663 1.049 0.645-1.706 0.848 Differentiation Low-moderate ref ref ref ref ref ref ref ref ref high 0.581 0.365-0.925 0.022 0.660 0.411-1.060 0.086 0.619 0.388-0.987 0.044 TNM Stage 1 ref ref ref ref ref ref ref ref ref 2 1.099 0.622-1.942 0.745 1.144 0.649-2.018 0.642 1.063 0.599-1.886 0.835 3 1.627 0.860-3.080 0.135 1.828 0.972-3.437 0.061 1.674 0.888-3.159 0.111 4 3.584 1.966-6.533 <0.001 3.730 2.043-6.811 <0.001 3.375 1.828-6.325 <0.001 iTILs Lower ref ref ref Higher 0.518 0.341-0.785 0.002 TILV Lower ref ref ref Higher 0.604 0.387-0.943 0.026 fTILs Lower ref ref ref Higher 0.605 0.410-0.892 0.011 Table 3 Multi-model multi-factor analysis of factors related to LSCC RFS Items Multivariate iTILs Multivariate TILV Multivariate fTILs HR 95% CI P-value HR 95% CI P-value HR 95% CI P-value Gender Male ref ref ref ref ref ref ref ref ref Female 0.930 0.478-1.809 0.831 0.953 0.490-1.853 0.887 0.946 0.482-1.856 0.871 Age (yr) <60 （ref） ref ref ref ref ref ref ref ref ref ≥60 1.215 0.774-1.907 0.396 1.209 0.771-1.896 0.409 1.221 0.777-1.919 0.386 BMI (kg/m2) <24 （ref） ref ref ref ref ref ref ref ref ref ≥24 0.778 0.475-1.274 0.318 0.772 0.472-1.263 0.302 0.782 0.477-1.282 0.329 Alcohol No （ref） ref ref ref ref ref ref ref ref ref Yes 1.521 0.925-2.501 0.098 1.532 0.933-2.517 0.092 1.529 0.928-2.519 0.095 Differentiation Low-moderate ref ref ref ref ref ref ref ref ref high 0.454 0.265-0.778 0.004 0.439 0.257-0.753 0.003 0.453 0.265-0.774 0.004 TNM Stage 1 ref ref ref ref ref ref ref ref ref 2 1.904 0.991-3.662 0.053 1.912 0.996-3.670 0.052 1.882 0.975-3.633 0.059 3 1.868 0.886-3.941 0.101 1.862 0.885-3.914 0.101 1.854 0.880-3.905 0.104 4 2.605 1.258-5.394 0.010 2.651 1.282-5.482 0.009 2.567 1.231-5.351 0.012 iTILs Lower ref ref ref Higher 0.997 0.565-1.759 0.993 TILV Lower ref ref ref Higher 1.324 0.835-2.097 0.233 fTILs Lower ref ref ref Higher 0.933 0.591-1.473 0.766 Discussion As far as we know, this is the largest study in sample size assessing the prognostic value of TILs in LSCC. We analyzed the relationship between TILs and the prognosis/recurrence from multiple aspects. We are also the first to propose the concepts of TILV and fTILs in LSCC, which are useful for understanding tumor immune status in detail. In addition, our work confirms and extends other studies that have successfully quantified TIL levels in tissues and shown the correlations between the TIL levels and the outcomes[ 15 – 18 ]. Unlike the results of the 120 LSCC cohort study by Want et al [ 17 ], neither the Kaplan-Meir curve nor the single-factor multivariate analysis showed significant correlations between iTILs/TILV/fTILs and tumor recurrence in our study cohort. Despite the discrepancy, we believe this non-correlation to be credible, given the large size of our retrospective analysis (412 LSCC cohort). Our findings should add reliable indicators for the prognosis of LSCC patients, and contribute to future TNM stagings. Tumor infiltration by chronic inflammatory cells includes lymphocytes, plasma cells, and macrophages [ 19 ]. Lymphocytes are the main type of infiltrating immune cells, represented by T cells, B cells, and natural killer cells. TILs are considered to be a manifestation of the host's immune response to tumor cells. Some studies have reported the potential of TILs as prognostic indicators in various human malignancies [ 20 – 23 ]. Formalin-fixed paraffin-embedded sections can be used to assess tumor immunity from multiple perspectives such as TIL morphology [ 23 ], T cell subsets (e.g. CD3(+) or CD8(+)) immune score [ 24 ], and immunophenotype reaction [ 25 ]. In our study, only three aspects of TILs were evaluated morphologically. The results show that high levels of iTILs, TILV, and fTILs are good prognostic indicators for LSCC. In addition, the morphological evaluation of TILs is simple, can be performed routinely in clinical practice, and can provide better histopathological predictions on top of immune response without additional costs. This prediction is helpful for clinical decision-making. For instance, multimodal treatment is advised for early LSCC cases with low levels of TILs. A recent study demonstrated the important role of immune cells in regulating cancer invasion and metastasis [ 26 ]. The immune response is believed to be one of the main factors affecting the clinical outcome of tumors. In fact, tumors of the same clinical stage and/or the same histopathological grade may have very different immune responses [ 27 ]. Therefore, the immune heterogeneity of early LSCC can be used to divide patients into low- and high-risk groups, which is essential for the personalized treatment of patients to improve patient prognosis. The role of immunotherapy in patients with relapsed or metastatic LSCC continues to expand, promising new treatment approaches for potentially curable LSCC patients. The characterization of the immune status in the tumor microenvironment is a key prerequisite for understanding which patients may benefit from immune regulation, and will be very important for the introduction of immunotherapy [ 28 – 30 ]. How to efficiently, reliably, and timely measure the immune status in TME is currently unclear. Simple histological methods provide advantages because they are easy to obtain, quickly and quantitatively describe the tumor immune status in real-time. Recent studies have described the correlation between tumor genetics and immune-inflammatory response. This may help profile patients into different sub-populations for more personalized treatments[ 31 ]. Tumor patients with depleted immune cells have different responses to cell reduction therapy [ 32 , 33 ]. Therefore, it is possible to provide different treatment options for patients with the same tumor in clinical and imaging. Evaluating the changes in TME immune cells after chemotherapy and/or immunotherapy may also play an important role in evaluating response or drug selection/delivery. In the multivariate model, we found that the combination of iTILs, TILV, and fTILs can predict prognosis independent of other clinical variables. This finding provides further evidence that the evaluation of iTILs, TILV, and fTILs should be included in the clinicopathological prognosis model of LSCC patients. Similar proposal has been made in breast cancer. Loi et al.'s comprehensive analysis of 2148 patients with the early triple-negative disease showed that TILs increase the prognostic value of known clinical variables [ 34 ]. In addition, the International Immuno-oncology Biomarker Breast Cancer Working Group has proposed a standardized method for pathologists to evaluate iTILs in a post-assisted residual disease setting [ 35 ]. This standardization will be a necessary step to expand the use of iTILs in LSCC. Although the concept of evaluating TILs in LSCC in relation to clinical outcomes is not new, there are inadequate consistent data to support TILs as reliable prognostic factors [ 34 ]. In this study, we thoroughly assessed the local tumor immune microenvironment status and introduced two indicators, TILV, and fTILs for the following reasons: First, iTILs only reflects the content of tumor stroma, which may be incomplete information. On the other hand, TILV considers the percentage of stroma to the overall tumor when calculating iTILs, hence TILV may be more illuminative than iTILs. Secondly, many studies have shown that the frontier of tumor invasion is the part that best represents the real-time immune status of tumors [ 36 – 38 ]. Finally, when iTILs alone are not enough to evaluate the local immune status of tumors, TILV, and fTILs may provide additional information. This research will make a further contribution to this debate, providing reliable indicators for the prognosis of LSCC patients, and adding new knowledge for new TNM staging in the future. This study has several limitations. although this study is based on the largest cohort of 412 eligible patients, these analyses still need to be validated in larger patient cohorts. In addition, LSCC is a male-dominated disease, hence there is inevitably a significant gender bias in our patient cohort. Lastly, this is a retrospective analysis that needs to be verified in a prospective study. Conclusion In the age of LSCC heterogeneity, tumor immunogenicity, and immunotherapy, our study confirmed that higher levels of TILs are beneficial to the prognosis of patients with laryngeal SCC and proposed two new standards, TILV, and fTILs, that can satisfactorily evaluate the local immune status of the tumor. Our results indicate that not only can iTILs, TILV, and fTILs predict longer OS, they are important independent prognostic factors for the LSCC patients after surgery. Although our study did not detect any significant relationship between immune infiltration and relapse, a thorough examination for local inflammatory markers is worthy of consideration for the evaluation of OS in LSCC. Declarations Ethics approval and consent to participate The present study was approved by the ethical review committee of Affiliated Tumor Hospital of Harbin Medical University and Tumor Hospital of Chinese Academy of Medical Sciences. Consent for publication Written informed consent for publication was obtained from all participants. Availability of data and materials The datasets used or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests None. Funding This work was supported by” Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province (LBH-Q18088), Key projects of Haiyan Foundation of Harbin Medical University Cancer Hospital (JJZD2020-14)”. Authors' contributions Susheng Miao and Xueying Wang wrote the manuscript, Erliang Guo, Lunhua Guo, Changming An, Cong Zhang, Kaibin Song, Guohui Wang, Chunbin Duan, Xiwei Zhang, Xianguang Yang1, Zhennan Yuan Y collected the samples and clinical data. Ji Sun, Weiwei Yang, and Xionghui Mao, Xiaomei Li conceived the structure and revised the manuscript. All authors read and approved the final manuscript. Acknowledgements We would like show sincere appreciation to the reviewers for critical comments on this article. References Lucioni M, Marioni G, Bertolin A, Giacomelli L, Rizzotto G. Glottic laser surgery: outcomes according to 2007 ELS classification. Eur Arch Otorhinolaryngol. 2011;268(12):1771-8. Steuer CE, El-Deiry M, Parks JR, Higgins KA, Saba NF. An update on larynx cancer. CA Cancer J Clin. 2017;67(1):31-50. Ma Y, Gong Z, Wang H, Liang Y, Huang X, Yu G. Anti-cancer effect of miR-139-3p on laryngeal squamous cell carcinoma by targeting rab5a: In vitro and in vivo studies. Pathol Res Pract. 2020;216(11):153194. Zhong F, Lu HP, Chen G, Dang YW, Li GS, Chen XY, et al. The clinical significance and potential molecular mechanism of integrin subunit beta 4 in laryngeal squamous cell carcinoma. Pathol Res Pract. 2020;216(2):152785. Yuan YJ, Sun Y, Gao R, Yin ZZ, Yuan ZY, Xu LM. Abnormal spindle-like microcephaly-associated protein (ASPM) contributes to the progression of Lung Squamous Cell Carcinoma (LSCC) by regulating CDK4. J Cancer. 2020;11(18):5413-23. Chang K, Wei Z, Cao H. miR-375-3p inhibits the progression of laryngeal squamous cell carcinoma by targeting hepatocyte nuclear factor-1beta. Oncol Lett. 2020;20(4):80. Oshi M, Asaoka M, Tokumaru Y, Yan L, Matsuyama R, Ishikawa T, et al. CD8 T Cell Score as a Prognostic Biomarker for Triple Negative Breast Cancer. Int J Mol Sci. 2020;21(18). Donisi G, Capretti G, Cortese N, Rigamonti A, Gavazzi F, Nappo G, et al. Immune infiltrating cells in duodenal cancers. J Transl Med. 2020;18(1):340. Wu A, Zhang S, Liu J, Huang Y, Deng W, Shu G, et al. Integrated Analysis of Prognostic and Immune Associated Integrin Family in Ovarian Cancer. Front Genet. 2020;11:705. Ha SY, Choi S, Park S, Kim JM, Choi GS, Joh JW, et al. Prognostic effect of preoperative neutrophil-lymphocyte ratio is related with tumor necrosis and tumor-infiltrating lymphocytes in hepatocellular carcinoma. Virchows Arch. 2020;477(6):807-16. Economopoulou P, Agelaki S, Perisanidis C, Giotakis EI, Psyrri A. The promise of immunotherapy in head and neck squamous cell carcinoma. Ann Oncol. 2016;27(9):1675-85. Hendry S, Salgado R, Gevaert T, Russell PA, John T, Thapa B, et al. Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non-Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors. Adv Anat Pathol. 2017;24(6):311-35. Kojima YA, Wang X, Sun H, Compton F, Covinsky M, Zhang S. Reproducible evaluation of tumor-infiltrating lymphocytes (TILs) using the recommendations of International TILs Working Group 2014. Ann Diagn Pathol. 2018;35:77-9. Salgado R, Denkert C, Demaria S, Sirtaine N, Klauschen F, Pruneri G, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol. 2015;26(2):259-71. Distel LV, Fickenscher R, Dietel K, Hung A, Iro H, Zenk J, et al. Tumour infiltrating lymphocytes in squamous cell carcinoma of the oro- and hypopharynx: prognostic impact may depend on type of treatment and stage of disease. Oral Oncol. 2009;45(10):e167-74. Kim HR, Ha SJ, Hong MH, Heo SJ, Koh YW, Choi EC, et al. PD-L1 expression on immune cells, but not on tumor cells, is a favorable prognostic factor for head and neck cancer patients. Sci Rep. 2016;6:36956. Pretscher D, Distel LV, Grabenbauer GG, Wittlinger M, Buettner M, Niedobitek G. Distribution of immune cells in head and neck cancer: CD8+ T-cells and CD20+ B-cells in metastatic lymph nodes are associated with favourable outcome in patients with oro- and hypopharyngeal carcinoma. BMC Cancer. 2009;9:292. Ward MJ, Thirdborough SM, Mellows T, Riley C, Harris S, Suchak K, et al. Tumour-infiltrating lymphocytes predict for outcome in HPV-positive oropharyngeal cancer. Br J Cancer. 2014;110(2):489-500. Wang J, Wang S, Song X, Zeng W, Wang S, Chen F, et al. The prognostic value of systemic and local inflammation in patients with laryngeal squamous cell carcinoma. Onco Targets Ther. 2016;9:7177-85. Baldan V, Griffiths R, Hawkins RE, Gilham DE. Efficient and reproducible generation of tumour-infiltrating lymphocytes for renal cell carcinoma. Br J Cancer. 2015;112(9):1510-8. Fortes C, Mastroeni S, Mannooranparampil TJ, Passarelli F, Zappala A, Annessi G, et al. Tumor-infiltrating lymphocytes predict cutaneous melanoma survival. Melanoma Res. 2015;25(4):306-11. Kang BW, Seo AN, Yoon S, Bae HI, Jeon SW, Kwon OK, et al. Prognostic value of tumor-infiltrating lymphocytes in Epstein-Barr virus-associated gastric cancer. Ann Oncol. 2016;27(3):494-501. Vassilakopoulou M, Avgeris M, Velcheti V, Kotoula V, Rampias T, Chatzopoulos K, et al. Evaluation of PD-L1 Expression and Associated Tumor-Infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma. Clin Cancer Res. 2016;22(3):704-13. West NR, Milne K, Truong PT, Macpherson N, Nelson BH, Watson PH. Tumor-infiltrating lymphocytes predict response to anthracycline-based chemotherapy in estrogen receptor-negative breast cancer. Breast Cancer Res. 2011;13(6):R126. Galon J, Mlecnik B, Bindea G, Angell HK, Berger A, Lagorce C, et al. Towards the introduction of the 'Immunoscore' in the classification of malignant tumours. J Pathol. 2014;232(2):199-209. Kitamura T, Qian BZ, Pollard JW. Immune cell promotion of metastasis. Nat Rev Immunol. 2015;15(2):73-86. Galon J, Pages F, Marincola FM, Angell HK, Thurin M, Lugli A, et al. Cancer classification using the Immunoscore: a worldwide task force. J Transl Med. 2012;10:205. Bauml J, Seiwert TY, Pfister DG, Worden F, Liu SV, Gilbert J, et al. Pembrolizumab for Platinum- and Cetuximab-Refractory Head and Neck Cancer: Results From a Single-Arm, Phase II Study. J Clin Oncol. 2017;35(14):1542-9. Ferris RL, Blumenschein G, Jr., Fayette J, Guigay J, Colevas AD, Licitra L, et al. Nivolumab vs investigator's choice in recurrent or metastatic squamous cell carcinoma of the head and neck: 2-year long-term survival update of CheckMate 141 with analyses by tumor PD-L1 expression. Oral Oncol. 2018;81:45-51. Saada-Bouzid E, Peyrade F, Guigay J. Immunotherapy in recurrent and or metastatic squamous cell carcinoma of the head and neck. Curr Opin Oncol. 2019;31(3):146-51. Bai S, Zhang P, Zhang JC, Shen J, Xiang X, Yan YB, et al. A gene signature associated with prognosis and immune processes in head and neck squamous cell carcinoma. Head Neck. 2019;41(8):2581-90. Bradford CR, Kumar B, Bellile E, Lee J, Taylor J, D'Silva N, et al. Biomarkers in advanced larynx cancer. Laryngoscope. 2014;124(1):179-87. Denkert C, von Minckwitz G, Brase JC, Sinn BV, Gade S, Kronenwett R, et al. Tumor-infiltrating lymphocytes and response to neoadjuvant chemotherapy with or without carboplatin in human epidermal growth factor receptor 2-positive and triple-negative primary breast cancers. J Clin Oncol. 2015;33(9):983-91. Loi S, Drubay D, Adams S, Pruneri G, Francis PA, Lacroix-Triki M, et al. Tumor-Infiltrating Lymphocytes and Prognosis: A Pooled Individual Patient Analysis of Early-Stage Triple-Negative Breast Cancers. J Clin Oncol. 2019;37(7):559-69. Dieci MV, Radosevic-Robin N, Fineberg S, van den Eynden G, Ternes N, Penault-Llorca F, et al. Update on tumor-infiltrating lymphocytes (TILs) in breast cancer, including recommendations to assess TILs in residual disease after neoadjuvant therapy and in carcinoma in situ: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer. Semin Cancer Biol. 2018;52(Pt 2):16-25. Chrisafis G, Wang T, Moissoglu K, Gasparski AN, Ng Y, Weigert R, et al. Collective cancer cell invasion requires RNA accumulation at the invasive front. Proc Natl Acad Sci U S A. 2020;117(44):27423-34. Sun Y, He J, Shi DB, Zhang H, Chen X, Xing AY, et al. Elevated ZBTB7A expression in the tumor invasive front correlates with more tumor budding formation in gastric adenocarcinoma. J Cancer Res Clin Oncol. 2020. Zhao C, Wu M, Zeng N, Xiong M, Hu W, Lv W, et al. Cancer-associated adipocytes: emerging supporters in breast cancer. J Exp Clin Cancer Res. 2020;39(1):156. 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06:40:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-323430/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-323430/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":7218576,"identity":"d1ed67bb-e2f9-4252-98d0-0d0ed9687d0d","added_by":"auto","created_at":"2021-03-22 14:13:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82619,"visible":true,"origin":"","legend":"Receiver operating characteristic (ROC) curve analysis for iTILs, TILV and fTILs.","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-323430/v1/516b77aecdf0ed75ccfcb6c8.png"},{"id":7218080,"identity":"15d7aec5-0870-4c9f-8a3f-92639a55addb","added_by":"auto","created_at":"2021-03-22 14:10:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":305809,"visible":true,"origin":"","legend":"Kaplan-Meier curves for iTILs(A), TILV(B), fTILs(C) with OS and RFS","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-323430/v1/adafa14e648f91cbad2ade5b.png"},{"id":7219121,"identity":"0c2688e0-10ce-4fe2-a707-ce245c268acb","added_by":"auto","created_at":"2021-03-22 14:16:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2158098,"visible":true,"origin":"","legend":"iTILs, TILV and fTILs calculations in six differentinvasive laryngeal cancer cases.A and B, iTILs are less than 10% and greater than 10%, respectively. C and D, TILV are less than 12% and greater than 12%, respectively. D and E fTILs are less than 50% and greater than 50%, respectively.","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-323430/v1/e7b7310e6b3df7a5fcdc925a.png"},{"id":13681893,"identity":"570d422d-4f8f-47cb-bf89-78b4e9984414","added_by":"auto","created_at":"2021-09-17 11:54:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3262289,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-323430/v1/26c81e84-e18c-4366-a7c9-2c698abfc21c.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eMulti-factor Evaluation of Tumor-infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma and its Prognostic Value\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eLaryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. At present, the treatment strategy of LSCC includes a combination of CO\u003csub\u003e2\u003c/sub\u003e laser-assisted oral surgery, open surgery, oral robotic surgery, radiotherapy, and chemotherapy[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, despite the development of improved strategies and more accurate treatments, the 5-year survival rate of laryngeal squamous cell carcinoma has decreased from 66\u0026ndash;63% unfortunately in the past 40 years [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In recent years, oncology research on LSCC has been focusing on the tumor biology, especially for the advanced LSCC, to find prognostic markers and potential therapeutic targets [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTumor-infiltrating lymphocytes (TILs) are a heterogeneous group of lymphocytes that are found in the tumor microenvironment. Mainly T lymphocytes, TILs participate in the formation of tumor immune microenvironment locally and the body's anti-tumor immune response. Current studies have found that TILs are responsible for the microenvironment composition and effects in various types of malignant tumors, such as head and neck tumors, melanoma, breast cancer, bladder cancer, urothelial tumors, ovarian cancer, colorectal cancer, kidney cancer, prostate cancer, and lung cancer[\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It has also been reported that the immune response of the tumor cell matrix has important prognostic and predictive significance [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The dysfunction of the immune system is a key factor in the occurrence and development of LSCC, and immune checkpoints are an important mechanism for tumor immune escape[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. According to these studies, the presence of TILs is an important biomarker for predicting cervical lymph node metastasis in LSCC. It is therefore necessary to determine the pathological markers that predict survival and recurrence in order to optimize the treatment and reduce potentially preventable adverse effects on patients. However, there is no research up to date that determines the relationship between TIL and the prognosis of LSCC.\u003c/p\u003e \u003cp\u003eThe TIL-related parameters evaluated are the following: the intratumoral infiltrating lymphocyte (iTILs), tumor-infiltrating lymphocyte volume (TILV), and the frontier tumor-infiltrating lymphocytes (fTILs). The iTIL score is defined as the percentage of tumor islands occupied by lymphocytes. TILV=% stroma in tumor\u0026times;% stroma iTILs. Frontier TILs (fTILs) are defined as the percentage of infiltrating lymphocytes in the tissues before tumor invasion. The International Immunological Biomarker Working Group used H\u0026amp;E-stained sections to evaluate TILs of solid tumors in 2017 and developed a standardized method for the microscopic detection of iTILs in H\u0026amp;E-stained sections[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These standards are repeatable and applied to daily practice [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the evaluation of the iTILs does not involve the tumor-stroma ratio and the percentage of tumor-infiltrating lymphocytes in the invasion front, which is one-sided for the evaluation of the local immune status of the tumor. To our knowledge, this study is the first to evaluate the relation between lymphocyte infiltration in different parts of the tumor and the prognosis and recurrence of LSCC after surgery. We first proposed the concept of TILV and fTILs at LSCC.\u003c/p\u003e \u003cp\u003eAlthough the histological evaluation of tumor-infiltrating lymphocytes in our H\u0026amp;E-stained samples did not reveal different subpopulations of lymphocytes, it might still be a useful biomarker for evaluating tumor behavior. This method is advantageous in several ways. It is cost-effective and does not require expensive or specific tools or antibodies. At the same time, it is also easy to incorporate into standard pathology reports. In our study, we conducted a detailed assessment of the real-time immune status in the three-dimensional tumor structure, and explored the relation between the TILs (iTILs, TILV and fTILs) and the LSCC outcomes overall survival (OS) and recurrence-free survival (RFS).\u003c/p\u003e "},{"header":"Materials And Methods","content":"\u003ch2\u003e1.Patients\u003c/h2\u003e\n\u003cp\u003eA total of 412 cases were retrospectively analyzed. These patients were all diagnosed pathologically and underwent laryngectomy at the Department of Head and Neck Nasopharyngeal Surgery, Affiliated Tumor Hospital of Harbin Medical University or the Head and Neck Department of Tumor Hospital of Chinese Academy of Medical Sciences between December 2011 and December 2014. This study was reviewed and approved by the ethics committees of the two institutions, and proceeded in accordance with the principles of the Declaration of Helsinki and its amendments. All participants provided informed consents to participate in the study. The clinical data (sex, age, BMI, history of drinking and smoking, tumor location, differentiation, TNM, T-stage and N-stage,) and follow-up information (clinical outcome and survival time) were collected through \u0026nbsp;from the electronic medical records. The prescribed inclusion criteria are as follows: 1) LSCC confirmed by histopathology; 2) No history of anti-cancer treatment; 3) Complete clinical, laboratory, imaging, and follow-up data; 4) The remaining paraffin-fixed tissue is sufficient, and the structure is clear; 5) Has at least one slice to assess the edge of tumor invasion; 6) No history of other malignant tumors and no distant metastasis. In this study, a total of 412 patients with laryngeal squamous cell carcinoma were enrolled. There were 2 to 3 pathological tissue slices in each case, and a total of 1112 pathological tissue slices were reviewed. The samples were reviewed by two pathologists in a double-blind manner, and the patients were staged according to the eighth edition of the American Joint Committee on Cancer (AJCC) staging system. Table 1 lists the main clinicopathological characteristics of the patients.\u003c/p\u003e\n\u003ch2\u003e2. Experimental methods\u003c/h2\u003e\n\u003ch2\u003e2.1 Tumor tissue sampling and laryngeal cancer tissue wax block preparation\u003c/h2\u003e\n\u003cp\u003e1) Surgically excised laryngeal tissue specimens are cut and fixed with 10% formalin solution; 2) 3*3*0.5 cm tissue blocks are cut from the laryngeal cancer tissue and placed in a tissue embedding box and placed in 10% formalin solution; 3) Laryngeal cancer tissue blocks are dehydrated by gradient alcohol of low concentration to high concentration; 4) Laryngeal cancer tissue blocks are soaked in xylene to remove alcohol transparent tissue; 5) Laryngeal cancer tissue blocks are embedded in paraffin to make laryngeal cancer Tissue wax blocks.\u003c/p\u003e\n\u003ch2\u003e2.2 Preparation of white slices of laryngeal cancer tissue\u003c/h2\u003e\n\u003cp\u003e1) Slice the laryngeal cancer tissue wax blocks with a microtome 4 \u0026micro;m in thickness; 2) Place the slices in 30\u0026deg;C water and flatten with a glass slide; 3) Bake the slides at 72\u0026deg;C for 1-2 hours.\u003c/p\u003e\n\u003ch2\u003e2.3 Hematoxylin-Eosin staining (H\u0026amp;E staining)\u003c/h2\u003e\n\u003cp\u003e1) White slices of laryngeal cancer tissue are deparaffinized in xylene solution; 2) White slices are hydrated with high to low concentration gradient alcohol; 3) White slices are stained with hematoxylin 4) After washing, the sections are placed in hydrochloric acid alcohol to return to blue and differentiated in the differentiation solution; 5) After the sections are rinsed, they are dehydrated in low to high concentration gradient alcohol; 6) The sections are stained in alcohol and eosin; 7) The sections are placed Dehydrate in pure alcohol; 8) place the slices in xylene to be transparent; 9) use neutral resin to seal the slices after drying.\u003c/p\u003e\n\u003ch2\u003e3. TIL histological scoring in laryngeal cancer tissues\u003c/h2\u003e\n\u003cp\u003eWe evaluated TIL-related parameters according to the scoring method introduced by the International Immuno-Tumor Biomarker Working Group recently[14] . The evaluation of iTILs does not include any stromal areas that are not directly related to the tumor. In addition, areas of fibrosis or central necrosis are not included in the iTILs assessment. The percentage of iTILs was evaluated in 2 areas of each sample (the front and the center of the tumor invasion). The TIL working group guidelines recommend \"Don't focus on hot spots\" 1.2. Therefore, the average value of TIL in the region should be used when reporting iTILs and fTILs. We evaluated at least five regions to assess the average value of TIL. As recommended, we used the whole untrimmed tumor sections. Each case in our study had at least one representative section (4 - 5 \u0026micro;m). Low-quality tumor sections, such as tumor sections without tumor-stroma interface, were excluded.\u003c/p\u003e\n\u003ch2\u003e4. Follow-up methods\u003c/h2\u003e\n\u003cp\u003eThe demographic, clinicopathological and treatment data of each patient were extracted from the electronic medical record system. The demographic data and clinicopathological characteristics of the patients were collected from the database of two institutions/hospitals. All patients who met the inclusion criteria were followed up by a combination of inpatient case review and telephone through January, 2020. The median follow-up time was 59.9 months (range: 1.9-83.2 months). The median overall survival time was 68.1 months (95% CI: 65.6-70.5 months). The primary outcome was overall survival (OS) from diagnosis to death and the second outcome was recurrence-free survival (RFS) from cancer diagnosis to disease recurrence or metastasis or cancer specific death, whichever came first.\u003c/p\u003e\n\u003ch2\u003e5. Data analysis\u003c/h2\u003e\n\u003cp\u003eWe first divided the patients into two groups according to the optimal cut-off point of each iTIL, TILV and fTILs level, which was determined by Receiver operating characteristic (ROC) curves with overall survival status as the dependent variable (0, alive; 1, death). We reported means and standard deviations or counts and frequencies for continuous or categorical variables, respectively. Differences in continuous and categorical covariates between groups were compared with Student\u0026rsquo;s t tests and chi-square (\u0026chi;2) tests, respectively.\u003c/p\u003e\n\u003cp\u003eWe then conducted univariate and multivariate Cox regression analyses and reported hazard ratios (HRs) and 95% confidence intervals (CIs) to assess the association between iTILs, TILV and fTILs and the prognosis of laryngocarcinoma patients. The likelihood ratio backward stepwise selection was used for the multivariate Cox regression analysis. Kaplan-Meier curves and log-rank tests were then conducted to compare the OS and RFS rates between groups. Two-sided statistical significance was defined as P \u0026lt; 0.05. ROC analyses were performed with MedCalc version 12.6.1.0, and all other statistical analyses were performed with SPSS Statistics version 23.0 (IBM, Inc., USA).\u003c/p\u003e"},{"header":"Results","content":"\u003col\u003e\n\u003cli\u003e\n\u003ch2\u003eCutoff values\u0026nbsp;for iTILs, TILV and fTILs\u003c/h2\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAccording to the ROC curve, the areas under the curve (AUCs) of iTILs, TILV, and fTILs are 0.589 (95% CI 0.540-0.637, P=0.00319), 0.577 (95% CI 0.527-0.625, P=0.0308,) and 0.553 (95 % CI 0.503-0.602, P=0.0323) respectively, and the best cut-off values were 10%, 12% and 50% respectively (Fig.1).\u003c/p\u003e\n\u003cp\u003eA total of 336 men (81.6%) and 76 women (18.4%) were eligible for this study. Most subjects (72.3%) had a current or past history of smoking. As shown in Table 1, 52.2% of patients had supraglottic squamous cell carcinoma, and 47.8% of patients had glottal laryngeal squamous cell carcinoma. Most patients (65.3%) had localized early tumors (T1 or T2), most (59.0%) being moderately or poorly differentiated.\u003c/p\u003e\n\u003col start=\"2\"\u003e\n\u003cli\u003e\n\u003ch2\u003eSurvival analysis based on tumor inflammation markers\u003c/h2\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eIn our study, 330 patients had higher iTILs (80.1%, Figure 2A), 82 patients had lower iTILs (19.9%, Figure 2B). The 5-year OS rate was significantly higher in the high iTILs group (75.76%) than in the low iTILs group (59.76%, p \u0026lt; 0.05, Figure 3A). When the patients were stratified into high TILV group (137 patients or 33.3%, Figure 2C) and low TILV group (275 patients or 66.7%, Figure 2D), the 5-year OS rate is significantly higher in the high TILV group (81.20%) than in the low TILC group (68.36%, p \u0026lt; 0.05, Figure 3B). Finally, we stratified the patients again, according to fTILs. 240 patients had higher fTILs (58.3%, Figure 2E), and 172 patients had lower fTILs (41.7%%, Figure 2F). The 5-year OS rate of the high fTILs group (77.50%) was significantly higher than that of the low fTILs group (65.70%, P\u0026lt;0.05, Figure 3C). Therefore, the levels of iTILs, TILV, and fTILs are related to the patient\u0026rsquo;s survival. Furthermore, we analyzed the levels of iTILs, TILV, and fTILs and the recurrence of the disease and found no significant correlation (P\u0026gt;0.05, Figure 2.)\u003c/p\u003e\n\u003col start=\"3\"\u003e\n\u003cli\u003e\n\u003ch2\u003eSingle- and multiple-factor analyses\u003c/h2\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eClinicopathological parameters, including the levels of iTILs, TILV and fTILs, and OS and RFS, were subjected to univariate multivariate analyses to determine independent predictors of OS and RFS in LSCC patients. BMI\u0026lt;24, history of drinking, low levels of differentiation, supraglottic carcinoma, high T/N stage or TNM, and low iTILs/TILV/fTILs levels were identified as predictors of poor prognosis (Table 1). These factors are determined by the single-factor analysis. Next, we established multiple linear regression models to observe the main effects of iTILs, TILV, and fTILs. age, alcohol consumption, and T4 tumor stage showed statistical significance in these three models. More importantly, the three linear regression models showed that high iTILs (P=0.002, HR: 0.518, 95%CI 0.341-0.785), high TILV (P=0.026, HR: 0.604, 95%CI: 0.387-0.943) and high FTILs (P=0.011, HR: 0.605, 95%CI: 0.410-0.892) were significantly correlated with better OS (Table 2). Therefore, we believe that high levels of iTILs, TILV, and fTILs are independent predictors of good prognosis. In the Cox regression model analysis to determine the statistically significant factors related to RFS, the relationship between the three factors and the recurrence was not found to be statistically significant, in either single-factor or multivariate analyses (Table 1 \u0026amp; 2).\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eTable 1\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003ePatient baseline characteristics and univariate analysis of OS and RFS\u003c/p\u003e\n\u003ctable style=\"margin-left: auto; margin-right: auto;\" border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo. (%)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"184\"\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOS\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"180\"\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRFS\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e336（81.6%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e76（18.4%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e0.980\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.610-1.574\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.932\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.893\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.492-1.618\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.708\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge (yr)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026lt;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e223（54.1%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e189（45.9%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e1.367\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.945-1.978\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.097\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.120\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.720-1.742\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.615\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI (kg/m2)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026lt;24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e273（66.3%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026ge;24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e139（33.7%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.577 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.374-0.889\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.013 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.754\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.464-1.226\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.255\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eSmoking \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e114（27.7%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e298（72.3%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e1.305\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.847-2.011\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.228\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.615\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.933-2.797\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.087\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e226（54.9%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e186（45.1%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.519 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.049-2.198\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.027 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.571 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.009-2.447\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.046 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eInitial Site\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003esupraglottic\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e215（52.2%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eglottic larynx\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e197（47.8%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.611 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.417-0.895\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.011 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.681\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.435-1.068\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.094\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eDifferentiation\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eLow-moderate\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e243（59.0%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003ehigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e169（41.0%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.477 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.314-0.724\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.403 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.240-0.675\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eT-Stage\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eT1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e135（32.3%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eT2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e209（50.7%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e1.423\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.905-2.238\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.158 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.226-3.801\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.008 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eT3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e52（12.6%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.204 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.251-3.883\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.006 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.826-4.012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eT4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e16（3.9%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.312 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.010-5.294\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.047 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e3.357 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.230-9.164\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.018 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eN-Stage\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eN0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e312（75.7%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eN1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e38（9.2%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e1.792\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.987-3.253\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.055\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.785\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.906-3.516\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.094\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eN2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e62（15.1%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e3.941 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.609-5.954\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.567 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.497-4.400\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eTNM Stage\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e119（28.9%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e150（36.4%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e1.166\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.668-2.037\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.589\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.013 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.053-3.848\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.034 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e71（17.2%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.042 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.129-3.691\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.018 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.327 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.119-4.838\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.024 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e72（17.5%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e4.416 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.594-7.516\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e3.464 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.709-7.022\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eiTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e82（19.9%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e330（80.1%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.545 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.363-0.818\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.003 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.025\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.584-1.798\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.933\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eTILV\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e275（66.7%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e137（33.3%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.548 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.354-0.850\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.007 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.748-1.857\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.478\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003efTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e172（41.7%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e240（58.3%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.611 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.422-0.884\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.009 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.895\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.574-1.396\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.626\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eTable 2\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eMulti-model multi-factor analysis of factors related to LSCC OS\u003c/p\u003e\n\u003ctable style=\"margin-left: auto; margin-right: auto;\" border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"175\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eiTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"164\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTILV\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"164\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eMale（ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.065\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.618-1.836\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e1.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.613-1.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.843\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e1.249\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e0.719-2.169\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.430\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge (yr)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026lt;60 （ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.500 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.029-2.186\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.035 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.500 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.029-2.188\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.035 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.520\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.042-2.219\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.030 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI (kg/m2)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026lt;24 （ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u0026ge;24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e0.667\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.430-1.033\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.070\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e0.670\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.432-1.040\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.074\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e0.665\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e0.429-1.031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.068\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eNo （ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.533 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.018-2.308\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.041 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.525 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.014-2.292\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.043 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.632\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.080-2.467\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.020 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003eInitial Site\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003esupraglottic\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eglottic larynx\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.068\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.660-1.728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.790\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e1.114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.685-1.811\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.663\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e1.049\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e0.645-1.706\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.848\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003eDifferentiation\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eLow-moderate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003ehigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e0.581\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.365-0.925\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e0.660\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.411-1.060\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.086\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e0.619\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.388-0.987\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd 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width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.604 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.387-0.943\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.026 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e\u003cstrong\u003efTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"41\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.605\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.410-0.892\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.011 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eTable 3\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003eMulti-model multi-factor analysis of factors related to LSCC RFS\u003c/p\u003e\n\u003ctable style=\"margin-left: auto; margin-right: auto;\" border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"180\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eiTILs \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"180\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTILV\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"180\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.930\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.478-1.809\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.831\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.953\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.490-1.853\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.887\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.946\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.482-1.856\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.871\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge (yr)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026lt;60 （ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.215\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.774-1.907\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.396\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.209\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.771-1.896\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.409\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.777-1.919\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.386\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI (kg/m2)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026lt;24 （ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026ge;24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.778\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.475-1.274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.318\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.772\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.472-1.263\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.302\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.782\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.477-1.282\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eNo （ref）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.521\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.925-2.501\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.098\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.532\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.933-2.517\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.092\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.529\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.928-2.519\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.095\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eDifferentiation\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eLow-moderate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003ehigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.454 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.265-0.778\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.004 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.439 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.257-0.753\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.003 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.453 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.265-0.774\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.004 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eTNM Stage\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.904\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.991-3.662\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.053\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.912\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.996-3.670\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.052\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.882\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.975-3.633\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.059\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.868\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.886-3.941\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.862\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.885-3.914\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.854\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.880-3.905\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.104\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.605 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.258-5.394\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.010 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.651 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.282-5.482\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.009 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.567 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.231-5.351\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.012 \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eiTILs\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.997\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.565-1.759\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.993\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eTILV\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e1.324\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.835-2.097\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.233\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003efTILs \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eLower\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eref\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003eHigher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"47\"\u003e\n\u003cp\u003e0.933\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.591-1.473\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.766\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eAs far as we know, this is the largest study in sample size assessing the prognostic value of TILs in LSCC. We analyzed the relationship between TILs and the prognosis/recurrence from multiple aspects. We are also the first to propose the concepts of TILV and fTILs in LSCC, which are useful for understanding tumor immune status in detail. In addition, our work confirms and extends other studies that have successfully quantified TIL levels in tissues and shown the correlations between the TIL levels and the outcomes[\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Unlike the results of the 120 LSCC cohort study by Want et al [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], neither the Kaplan-Meir curve nor the single-factor multivariate analysis showed significant correlations between iTILs/TILV/fTILs and tumor recurrence in our study cohort. Despite the discrepancy, we believe this non-correlation to be credible, given the large size of our retrospective analysis (412 LSCC cohort). Our findings should add reliable indicators for the prognosis of LSCC patients, and contribute to future TNM stagings.\u003c/p\u003e \u003cp\u003eTumor infiltration by chronic inflammatory cells includes lymphocytes, plasma cells, and macrophages [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Lymphocytes are the main type of infiltrating immune cells, represented by T cells, B cells, and natural killer cells. TILs are considered to be a manifestation of the host's immune response to tumor cells. Some studies have reported the potential of TILs as prognostic indicators in various human malignancies [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Formalin-fixed paraffin-embedded sections can be used to assess tumor immunity from multiple perspectives such as TIL morphology [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], T cell subsets (e.g. CD3(+) or CD8(+)) immune score [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and immunophenotype reaction [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In our study, only three aspects of TILs were evaluated morphologically. The results show that high levels of iTILs, TILV, and fTILs are good prognostic indicators for LSCC. In addition, the morphological evaluation of TILs is simple, can be performed routinely in clinical practice, and can provide better histopathological predictions on top of immune response without additional costs. This prediction is helpful for clinical decision-making. For instance, multimodal treatment is advised for early LSCC cases with low levels of TILs. A recent study demonstrated the important role of immune cells in regulating cancer invasion and metastasis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The immune response is believed to be one of the main factors affecting the clinical outcome of tumors. In fact, tumors of the same clinical stage and/or the same histopathological grade may have very different immune responses [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Therefore, the immune heterogeneity of early LSCC can be used to divide patients into low- and high-risk groups, which is essential for the personalized treatment of patients to improve patient prognosis.\u003c/p\u003e \u003cp\u003eThe role of immunotherapy in patients with relapsed or metastatic LSCC continues to expand, promising new treatment approaches for potentially curable LSCC patients. The characterization of the immune status in the tumor microenvironment is a key prerequisite for understanding which patients may benefit from immune regulation, and will be very important for the introduction of immunotherapy [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. How to efficiently, reliably, and timely measure the immune status in TME is currently unclear. Simple histological methods provide advantages because they are easy to obtain, quickly and quantitatively describe the tumor immune status in real-time. Recent studies have described the correlation between tumor genetics and immune-inflammatory response. This may help profile patients into different sub-populations for more personalized treatments[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Tumor patients with depleted immune cells have different responses to cell reduction therapy [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Therefore, it is possible to provide different treatment options for patients with the same tumor in clinical and imaging. Evaluating the changes in TME immune cells after chemotherapy and/or immunotherapy may also play an important role in evaluating response or drug selection/delivery.\u003c/p\u003e \u003cp\u003eIn the multivariate model, we found that the combination of iTILs, TILV, and fTILs can predict prognosis independent of other clinical variables. This finding provides further evidence that the evaluation of iTILs, TILV, and fTILs should be included in the clinicopathological prognosis model of LSCC patients. Similar proposal has been made in breast cancer. Loi et al.'s comprehensive analysis of 2148 patients with the early triple-negative disease showed that TILs increase the prognostic value of known clinical variables [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, the International Immuno-oncology Biomarker Breast Cancer Working Group has proposed a standardized method for pathologists to evaluate iTILs in a post-assisted residual disease setting [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This standardization will be a necessary step to expand the use of iTILs in LSCC. Although the concept of evaluating TILs in LSCC in relation to clinical outcomes is not new, there are inadequate consistent data to support TILs as reliable prognostic factors [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In this study, we thoroughly assessed the local tumor immune microenvironment status and introduced two indicators, TILV, and fTILs for the following reasons: First, iTILs only reflects the content of tumor stroma, which may be incomplete information. On the other hand, TILV considers the percentage of stroma to the overall tumor when calculating iTILs, hence TILV may be more illuminative than iTILs. Secondly, many studies have shown that the frontier of tumor invasion is the part that best represents the real-time immune status of tumors [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Finally, when iTILs alone are not enough to evaluate the local immune status of tumors, TILV, and fTILs may provide additional information. This research will make a further contribution to this debate, providing reliable indicators for the prognosis of LSCC patients, and adding new knowledge for new TNM staging in the future.\u003c/p\u003e \u003cp\u003eThis study has several limitations. although this study is based on the largest cohort of 412 eligible patients, these analyses still need to be validated in larger patient cohorts. In addition, LSCC is a male-dominated disease, hence there is inevitably a significant gender bias in our patient cohort. Lastly, this is a retrospective analysis that needs to be verified in a prospective study.\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eIn the age of LSCC heterogeneity, tumor immunogenicity, and immunotherapy, our study confirmed that higher levels of TILs are beneficial to the prognosis of patients with laryngeal SCC and proposed two new standards, TILV, and fTILs, that can satisfactorily evaluate the local immune status of the tumor. Our results indicate that not only can iTILs, TILV, and fTILs \u0026nbsp;predict longer OS, they are important independent prognostic factors for the LSCC patients after surgery. Although our study did not detect any significant relationship between immune infiltration and relapse, a thorough examination for local inflammatory markers is worthy of consideration for the evaluation of OS in LSCC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe present study was approved by the ethical review committee of Affiliated Tumor Hospital of Harbin Medical University and Tumor Hospital of Chinese Academy of Medical Sciences.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eWritten informed consent for publication was obtained from all participants.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by\u0026rdquo; Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province (LBH-Q18088), Key projects of Haiyan Foundation of Harbin Medical University Cancer Hospital (JJZD2020-14)\u0026rdquo;.\u003c/p\u003e\n\u003ch2\u003eAuthors' contributions\u003c/h2\u003e\n\u003cp\u003eSusheng Miao and Xueying Wang wrote the manuscript, Erliang Guo, Lunhua Guo, Changming An, Cong Zhang, Kaibin Song, Guohui Wang, Chunbin Duan, Xiwei Zhang, Xianguang Yang1, Zhennan Yuan Y collected the samples and clinical data. Ji Sun, Weiwei Yang, and Xionghui Mao, Xiaomei Li conceived the structure and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe would like show sincere appreciation to the reviewers for critical comments on this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLucioni M, Marioni G, Bertolin A, Giacomelli L, Rizzotto G. Glottic laser surgery: outcomes according to 2007 ELS classification. Eur Arch Otorhinolaryngol. 2011;268(12):1771-8.\u003c/li\u003e\n\u003cli\u003eSteuer CE, El-Deiry M, Parks JR, Higgins KA, Saba NF. An update on larynx cancer. CA Cancer J Clin. 2017;67(1):31-50.\u003c/li\u003e\n\u003cli\u003eMa Y, Gong Z, Wang H, Liang Y, Huang X, Yu G. Anti-cancer effect of miR-139-3p on laryngeal squamous cell carcinoma by targeting rab5a: In vitro and in vivo studies. Pathol Res Pract. 2020;216(11):153194.\u003c/li\u003e\n\u003cli\u003eZhong F, Lu HP, Chen G, Dang YW, Li GS, Chen XY, et al. The clinical significance and potential molecular mechanism of integrin subunit beta 4 in laryngeal squamous cell carcinoma. Pathol Res Pract. 2020;216(2):152785.\u003c/li\u003e\n\u003cli\u003eYuan YJ, Sun Y, Gao R, Yin ZZ, Yuan ZY, Xu LM. Abnormal spindle-like microcephaly-associated protein (ASPM) contributes to the progression of Lung Squamous Cell Carcinoma (LSCC) by regulating CDK4. J Cancer. 2020;11(18):5413-23.\u003c/li\u003e\n\u003cli\u003eChang K, Wei Z, Cao H. miR-375-3p inhibits the progression of laryngeal squamous cell carcinoma by targeting hepatocyte nuclear factor-1beta. Oncol Lett. 2020;20(4):80.\u003c/li\u003e\n\u003cli\u003eOshi M, Asaoka M, Tokumaru Y, Yan L, Matsuyama R, Ishikawa T, et al. CD8 T Cell Score as a Prognostic Biomarker for Triple Negative Breast Cancer. Int J Mol Sci. 2020;21(18).\u003c/li\u003e\n\u003cli\u003eDonisi G, Capretti G, Cortese N, Rigamonti A, Gavazzi F, Nappo G, et al. Immune infiltrating cells in duodenal cancers. J Transl Med. 2020;18(1):340.\u003c/li\u003e\n\u003cli\u003eWu A, Zhang S, Liu J, Huang Y, Deng W, Shu G, et al. Integrated Analysis of Prognostic and Immune Associated Integrin Family in Ovarian Cancer. Front Genet. 2020;11:705.\u003c/li\u003e\n\u003cli\u003eHa SY, Choi S, Park S, Kim JM, Choi GS, Joh JW, et al. Prognostic effect of preoperative neutrophil-lymphocyte ratio is related with tumor necrosis and tumor-infiltrating lymphocytes in hepatocellular carcinoma. Virchows Arch. 2020;477(6):807-16.\u003c/li\u003e\n\u003cli\u003eEconomopoulou P, Agelaki S, Perisanidis C, Giotakis EI, Psyrri A. The promise of immunotherapy in head and neck squamous cell carcinoma. Ann Oncol. 2016;27(9):1675-85.\u003c/li\u003e\n\u003cli\u003eHendry S, Salgado R, Gevaert T, Russell PA, John T, Thapa B, et al. Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non-Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors. Adv Anat Pathol. 2017;24(6):311-35.\u003c/li\u003e\n\u003cli\u003eKojima YA, Wang X, Sun H, Compton F, Covinsky M, Zhang S. Reproducible evaluation of tumor-infiltrating lymphocytes (TILs) using the recommendations of International TILs Working Group 2014. Ann Diagn Pathol. 2018;35:77-9.\u003c/li\u003e\n\u003cli\u003eSalgado R, Denkert C, Demaria S, Sirtaine N, Klauschen F, Pruneri G, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol. 2015;26(2):259-71.\u003c/li\u003e\n\u003cli\u003eDistel LV, Fickenscher R, Dietel K, Hung A, Iro H, Zenk J, et al. Tumour infiltrating lymphocytes in squamous cell carcinoma of the oro- and hypopharynx: prognostic impact may depend on type of treatment and stage of disease. Oral Oncol. 2009;45(10):e167-74.\u003c/li\u003e\n\u003cli\u003eKim HR, Ha SJ, Hong MH, Heo SJ, Koh YW, Choi EC, et al. PD-L1 expression on immune cells, but not on tumor cells, is a favorable prognostic factor for head and neck cancer patients. Sci Rep. 2016;6:36956.\u003c/li\u003e\n\u003cli\u003ePretscher D, Distel LV, Grabenbauer GG, Wittlinger M, Buettner M, Niedobitek G. Distribution of immune cells in head and neck cancer: CD8+ T-cells and CD20+ B-cells in metastatic lymph nodes are associated with favourable outcome in patients with oro- and hypopharyngeal carcinoma. BMC Cancer. 2009;9:292.\u003c/li\u003e\n\u003cli\u003eWard MJ, Thirdborough SM, Mellows T, Riley C, Harris S, Suchak K, et al. Tumour-infiltrating lymphocytes predict for outcome in HPV-positive oropharyngeal cancer. Br J Cancer. 2014;110(2):489-500.\u003c/li\u003e\n\u003cli\u003eWang J, Wang S, Song X, Zeng W, Wang S, Chen F, et al. The prognostic value of systemic and local inflammation in patients with laryngeal squamous cell carcinoma. Onco Targets Ther. 2016;9:7177-85.\u003c/li\u003e\n\u003cli\u003eBaldan V, Griffiths R, Hawkins RE, Gilham DE. Efficient and reproducible generation of tumour-infiltrating lymphocytes for renal cell carcinoma. Br J Cancer. 2015;112(9):1510-8.\u003c/li\u003e\n\u003cli\u003eFortes C, Mastroeni S, Mannooranparampil TJ, Passarelli F, Zappala A, Annessi G, et al. Tumor-infiltrating lymphocytes predict cutaneous melanoma survival. Melanoma Res. 2015;25(4):306-11.\u003c/li\u003e\n\u003cli\u003eKang BW, Seo AN, Yoon S, Bae HI, Jeon SW, Kwon OK, et al. Prognostic value of tumor-infiltrating lymphocytes in Epstein-Barr virus-associated gastric cancer. Ann Oncol. 2016;27(3):494-501.\u003c/li\u003e\n\u003cli\u003eVassilakopoulou M, Avgeris M, Velcheti V, Kotoula V, Rampias T, Chatzopoulos K, et al. Evaluation of PD-L1 Expression and Associated Tumor-Infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma. Clin Cancer Res. 2016;22(3):704-13.\u003c/li\u003e\n\u003cli\u003eWest NR, Milne K, Truong PT, Macpherson N, Nelson BH, Watson PH. Tumor-infiltrating lymphocytes predict response to anthracycline-based chemotherapy in estrogen receptor-negative breast cancer. Breast Cancer Res. 2011;13(6):R126.\u003c/li\u003e\n\u003cli\u003eGalon J, Mlecnik B, Bindea G, Angell HK, Berger A, Lagorce C, et al. Towards the introduction of the 'Immunoscore' in the classification of malignant tumours. J Pathol. 2014;232(2):199-209.\u003c/li\u003e\n\u003cli\u003eKitamura T, Qian BZ, Pollard JW. Immune cell promotion of metastasis. Nat Rev Immunol. 2015;15(2):73-86.\u003c/li\u003e\n\u003cli\u003eGalon J, Pages F, Marincola FM, Angell HK, Thurin M, Lugli A, et al. Cancer classification using the Immunoscore: a worldwide task force. J Transl Med. 2012;10:205.\u003c/li\u003e\n\u003cli\u003eBauml J, Seiwert TY, Pfister DG, Worden F, Liu SV, Gilbert J, et al. Pembrolizumab for Platinum- and Cetuximab-Refractory Head and Neck Cancer: Results From a Single-Arm, Phase II Study. J Clin Oncol. 2017;35(14):1542-9.\u003c/li\u003e\n\u003cli\u003eFerris RL, Blumenschein G, Jr., Fayette J, Guigay J, Colevas AD, Licitra L, et al. Nivolumab vs investigator's choice in recurrent or metastatic squamous cell carcinoma of the head and neck: 2-year long-term survival update of CheckMate 141 with analyses by tumor PD-L1 expression. Oral Oncol. 2018;81:45-51.\u003c/li\u003e\n\u003cli\u003eSaada-Bouzid E, Peyrade F, Guigay J. Immunotherapy in recurrent and or metastatic squamous cell carcinoma of the head and neck. Curr Opin Oncol. 2019;31(3):146-51.\u003c/li\u003e\n\u003cli\u003eBai S, Zhang P, Zhang JC, Shen J, Xiang X, Yan YB, et al. A gene signature associated with prognosis and immune processes in head and neck squamous cell carcinoma. Head Neck. 2019;41(8):2581-90.\u003c/li\u003e\n\u003cli\u003eBradford CR, Kumar B, Bellile E, Lee J, Taylor J, D'Silva N, et al. Biomarkers in advanced larynx cancer. Laryngoscope. 2014;124(1):179-87.\u003c/li\u003e\n\u003cli\u003eDenkert C, von Minckwitz G, Brase JC, Sinn BV, Gade S, Kronenwett R, et al. Tumor-infiltrating lymphocytes and response to neoadjuvant chemotherapy with or without carboplatin in human epidermal growth factor receptor 2-positive and triple-negative primary breast cancers. J Clin Oncol. 2015;33(9):983-91.\u003c/li\u003e\n\u003cli\u003eLoi S, Drubay D, Adams S, Pruneri G, Francis PA, Lacroix-Triki M, et al. Tumor-Infiltrating Lymphocytes and Prognosis: A Pooled Individual Patient Analysis of Early-Stage Triple-Negative Breast Cancers. J Clin Oncol. 2019;37(7):559-69.\u003c/li\u003e\n\u003cli\u003eDieci MV, Radosevic-Robin N, Fineberg S, van den Eynden G, Ternes N, Penault-Llorca F, et al. Update on tumor-infiltrating lymphocytes (TILs) in breast cancer, including recommendations to assess TILs in residual disease after neoadjuvant therapy and in carcinoma in situ: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer. Semin Cancer Biol. 2018;52(Pt 2):16-25.\u003c/li\u003e\n\u003cli\u003eChrisafis G, Wang T, Moissoglu K, Gasparski AN, Ng Y, Weigert R, et al. Collective cancer cell invasion requires RNA accumulation at the invasive front. Proc Natl Acad Sci U S A. 2020;117(44):27423-34.\u003c/li\u003e\n\u003cli\u003eSun Y, He J, Shi DB, Zhang H, Chen X, Xing AY, et al. Elevated ZBTB7A expression in the tumor invasive front correlates with more tumor budding formation in gastric adenocarcinoma. J Cancer Res Clin Oncol. 2020.\u003c/li\u003e\n\u003cli\u003eZhao C, Wu M, Zeng N, Xiong M, Hu W, Lv W, et al. Cancer-associated adipocytes: emerging supporters in breast cancer. J Exp Clin Cancer Res. 2020;39(1):156.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Laryngeal squamous cell carcinoma (LSCC), intratumoral infiltrating lymphocytes (iTILs), tumor-infiltrating lymphocyte volume (TILV), frontier tumor-infiltrating lymphocytes (fTILs), overall survival (OS), recurrence-free survival (RFS)","lastPublishedDoi":"10.21203/rs.3.rs-323430/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-323430/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Laryngeal squamous cell carcinoma (LSCC) is a heterogeneous disease. In clinical practice, patients with similar clinicopathological characteristics often show different outcomes. This study evaluated the levels of primary LSCC intratumoral infiltrating lymphocytes (iTILs), tumor-infiltrating lymphocyte volume (TILV), frontier tumor-infiltrating lymphocytes (fTILs), and their relations to the patient's clinical outcome. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMaterials and methods: \u003c/strong\u003eAccording to the 2017 study of the International TILs Working Group, \u0026nbsp;hematoxyline and eosin-stained slides from 412 patients were evaluated for their morphology of tumor immune infiltration status.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Kaplan-Meier analysis showed that high levels of iTILs, TILV, and fTILs were significantly correlated with OS (all P\u0026lt;0.05). Cox regression model analysis showed that high levels of iTILs, TILV, and fTILs were independently associated with better OS (all P\u0026lt;0.05). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Local inflammatory markers in patients with laryngeal squamous cell carcinoma, especially the levels of iTILs, TILV, and fTILs, are reliable prognostic factors.\u003c/p\u003e","manuscriptTitle":"Multi-factor Evaluation of Tumor-infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma and its Prognostic Value","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-22 14:10:57","doi":"10.21203/rs.3.rs-323430/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eeab5650-5da6-4ae1-8dcc-0cd3ecc45780","owner":[],"postedDate":"March 22nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":3133747,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2021-05-01T18:34:15+00:00","versionOfRecord":[],"versionCreatedAt":"2021-03-22 14:10:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-323430","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-323430","identity":"rs-323430","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}