Survival analysis of patients with early distant metastasis of tongue cancer undergoing radiotherapy

Survival analysis of patients with early distant metastasis of tongue cancer undergoing radiotherapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Survival analysis of patients with early distant metastasis of tongue cancer undergoing radiotherapy yi quan chen, Yi-chun Man, Haijun Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6350109/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 Tongue cancer is a common head - neck malignancy, and lung is the most frequent site of its distant metastasis. Chemotherapy is widely used for tongue cancer with pulmonary metastasis, yet the effectiveness of radiotherapy as a local treatment lacks clear recommendation in clinical guidelines. The core objective of this study is to delve into whether, for patients with early - stage metastatic tongue cancer, the combined treatment approach of adding radiotherapy to chemotherapy can effectively extend their effective survival period. Methods Based on the SEER database, we analyzed tongue cancer patients with pulmonary metastasis diagnosed from January 1, 2010, to December 31, 2021. Inclusion criteria were tongue cancer (M1 stage) with pulmonary metastasis. Kaplan - Meier survival curves and Cox regression models evaluated radiotherapy's effect on OS. Results Among 135 patients, 68 received radiotherapy (RT group) and 67 did not (Non - RT group). Kaplan - Meier analysis showed the RT group had a significantly longer median OS ((P = 0.0063)). Multivariate Cox regression indicated radiotherapy significantly reduced the death risk (HR = 0.57, (P = 0.007)). Conclusion Radiotherapy may positively impact the OS of tongue cancer patients with pulmonary metastasis, especially when combined with chemotherapy. Although it's an effective survival predictor in some models, further prospective studies are needed to verify its independent effect for personalized treatment. It may be effective to consider radiotherapy as a complementary treatment measure while exercising chemotherapy. Tongue cancer pulmonary metastasis radiotherapy overall survival SEER database survival analysis Cox regression Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Head and neck squamous cell carcinoma (HNSCC) is a common and aggressive type of cancer, typically occurring in the oral cavity, pharynx, and larynx( 10 , 13 , 20 ). Treatment for this type of cancer generally relies on a combination of surgery, radiation therapy, and chemotherapy, with specific treatment plans determined by tumor stage, location, and the patient's overall health condition( 1 , 19 ). However, among all types of HNSCC, tongue cancer presents a significant challenge due to its complex anatomical location and its tendency for early metastasis( 2 , 4 , 7 ). Current treatment guidelines recommend chemotherapy for patients with metastatic tongue cancer, as it is considered the standard treatment for distant metastasis( 14 ). Research indicates that the lungs are the most common site for metastasis in tongue cancer, with approximately 9.1% of patients developing pulmonary metastasis during disease progression( 24 ). This makes lung metastasis a common and prognostically significant phenomenon that occurs early in the disease course, significantly affecting the patient's overall survival (OS) and complicating treatment strategies( 3 , 24 ). Although chemotherapy remains the primary treatment for tongue cancer patients with pulmonary metastasis, radiotherapy—a local treatment modality—can help by delivering high-energy radiation to kill tumor cells, alleviating tumor pressure on the lungs and controlling symptoms( 6 , 8 ). However, the role of radiotherapy in improving survival for these patients has not yet been clearly recommended in clinical guidelines. Currently, most treatment guidelines classify tongue cancer as part of HNSCC, treating it under the same protocol as other head and neck cancers( 6 , 8 ). This approach does not consider the potential biological and metastatic differences between tongue cancer and other HNSCCs, underscoring the need for independent research specifically on tongue cancer( 13 ) . This study aims to explore whether radiotherapy can be an effective treatment option to extend survival in tongue cancer patients with pulmonary metastasis( 15 ). By analyzing clinical data from these patients, we seek to provide scientific evidence that fills the current gap in clinical guidelines for treating tongue cancer with pulmonary metastasis, offering new insights into the clinical management of this condition, especially in the application of combined treatment regimen for patients with lung metastasis. 2. Materials and Methods 2.1 Data Source This study is based on data from the SEER (Surveillance, Epidemiology, and End Results) database, which is established by the National Cancer Institute (NCI) and covers multiple regions in the United States, representing approximately 34.6% of the U.S. population (https://seer.cancer.gov, accessed on 30 January 2021). The SEER database contains demographic characteristics of patients, tumor pathology, treatment details, and follow-up data, providing high-quality retrospective data for this study(9). The cohort includes patients diagnosed with Tongue Cancer with Pulmonary Metastases (TCPM) from January 1, 2010, to December 31, 2021. Since the SEER database provides publicly available data with patient-identifiable information removed, ethical approval or patient written informed consent was not required for this study. The data used in this study were extracted through R (version 4.4.2) and based on the SEER research data submitted in November 2023(5). 2.2 Study Cohort Selection The study cohort was selected from the SEER database based on the following criteria: Inclusion Criteria: (i) Patients diagnosed with tongue cancer (ICD codes CD1.9-CD2.3, CD2.8-CD2.9) with pulmonary metastasis (M1 stage) between January 1, 2010, and December 31, 2019. (ii) Complete demographic records (gender, age, race, marital status) and tumor characteristics (T/N stage, differentiation) available. (iii) Clear treatment history, including whether the patient received radiotherapy (RT) and/or chemotherapy (CT). Exclusion Criteria:(i) Patients with other distant metastases (e.g., liver, bone, brain) to ensure the study population only includes patients with pulmonary metastasis. (ii) Patients with missing treatment data (including radiotherapy or chemotherapy). (iii) Patients with a survival time of less than one month, to avoid the instability of treatment intervention effects due to early death. A total of 135 patients diagnosed with TCPM meeting the inclusion criteria were selected. The cohort was divided into two groups based on whether they received radiotherapy (RT): RT group and Non-RT group(Table 2). 2.3 Variables Collected The following variables were collected: (i) Gender (ii) Age (either continuous or categorized) (iii) Race (White, Black, Other) (iv) Marital status (Married, Single/Divorced/Widowed) (v) Tumor grade (I–II vs III–IV) (vi) AJCC TNM staging (T stage, N stage) (vii) Radiotherapy (RT vs Non-RT) (viii) Chemotherapy (CT vs Non-CT) (ix) Overall survival (OS), defined as the time from diagnosis to death (measured in months).The SEER database does not contain information on specific chemotherapy regimens or patient quality of life. However, it provides reliable data support for large-scale population studies. The final follow-up for this study was conducted on December 31, 2021. 2.4 Matching method In this study, PSM was not conducted due to the following reasons: (i) Baseline Balance Between Groups: After selection, the ratio of RT group to Non-RT group was 1:1, and the variables, except chemotherapy, had P > 0.05, indicating no significant imbalance, making matching unnecessary. (ii) Standard Treatment and Clinical Practice: Although current guidelines recommend chemotherapy as the standard treatment for distant metastasis in tongue cancer, clinical practice often involves adding radiotherapy (RT) to improve local control or alleviate symptoms. (iii) Clinical Practice Trends: Patients who refuse chemotherapy are unlikely to undergo radiotherapy, and matching such patients might lead to a significant reduction in sample size, decreasing the representativeness of the study. (iv) Adjustment for Bias Using Alternative Methods: To adjust for the impact of chemotherapy on OS, Cox regression models were used for multivariate survival analysis, avoiding potential data loss and statistical bias caused by PSM. Considering the data balance and clinical practice, direct survival analysis was deemed more appropriate than PSM in this study(17). 2.5 Survival Analysis This study employed the following survival analysis methods: (i)Kaplan-Meier survival curves were used to assess survival rates in the different treatment groups, with Log-rank tests comparing the survival differences between the RT and Non-RT groups. (ii)Cox Proportional Hazard Model was used to calculate the effect of radiotherapy (RT) on survival for TCPM patients and conduct multivariate adjustment for potential confounding factors such as age, tumor grade, and T/N stage. (iii)Results were expressed in terms of hazard ratios (HR) with their 95% confidence intervals (CI). A P-value < 0.05 was considered statistically significant. All data analyses were performe d using R( version 4.4.2.) 3. Results 3.1 Selection of Study Cohort and Baseline Characteristics A total of 135 patients with tongue cancer and pulmonary metastases (TCPM) were included in this study. Among them, 68 patients received radiotherapy (RT) and 67 patients did not (Non-RT group), with a near 1:1 ratio (Table 1). Baseline characteristics comparison showed no significant differences between the two groups for most variables, except for chemotherapy, which was statistically significant. This suggests that patients receiving radiotherapy were more likely to have chemotherapy, while patients who did not receive chemotherapy typically did not undergo radiotherapy. Due to the balanced characteristics between the groups, propensity score matching (PSM) was not conducted, and Cox regression models were directly used to adjust for the impact of chemotherapy on survival outcomes, to avoid sample size reduction and loss of statistical power from matching. 3.2 Survival Outcomes Kaplan-Meier survival analysis (Figure 2a) revealed that the RT group had a significantly longer median overall survival (OS) compared to the Non-RT group (P = 0.0063), suggesting that radiotherapy may have a positive impact on survival. The forest plot (Figure 1) further illustrated the median OS and 95% confidence intervals for different subgroups of patients. Overall, radiotherapy showed survival advantages in multiple subgroups, although there was considerable variability in the results for some subgroups, indicating that the exact survival benefits need further verification. 3.3 Prognostic Factors, Model Evaluation, and Clinical Implications Prognostic Factors Analysis: Multivariate Cox regression analysis (Figures 3 and 5) showed that radiotherapy (RT), chemotherapy (chemo), tumor grade (Grade), age, and sex all significantly influenced survival outcomes in tongue cancer patients with pulmonary metastasis: (i) Radiotherapy (RT): HR = 0.57 (P = 0.007), indicating that radiotherapy significantly reduces the risk of death. (ii) Chemotherapy (chemo): HR = 0.43 (P = 0.006), suggesting that chemotherapy is also an important factor in improving survival. (iii) Tumor Grade: Patients with poorly differentiated tumors (Grade III-IV) had a lower survival rate compared to those with well-differentiated tumors (Grade I-II), but the result did not reach statistical significance. (iv) Age: Patients over 60 years had a higher risk of mortality (HR > 1), suggesting that older age may be a potential negative factor for survival. (v) Sex: Male patients had a slightly higher risk of death compared to females, but this difference was not statistically significant. Model Evaluation: Analysis of Akaike Information Criterion corrected (AICc) (Figure 4) showed that the best-fitting Cox regression model had an AICc = 899.37, with the top four models having similar AICc values, indicating the importance of radiotherapy (RT) in survival prediction. Multiple high-ranking models included the radiotherapy variable, further supporting its role as an important factor influencing survival. Clinical Implications of the Findings: The results of this study suggest that the combined use of radiotherapy and chemotherapy can improve survival rates in tongue cancer patients with pulmonary metastasis. Additionally, tumor differentiation, age, and sex may influence individual survival outcomes. Radiotherapy was included in several of the optimal survival prediction models, further supporting its role as a key component of treatment for tongue cancer with pulmonary metastasis. However, the independent role of radiotherapy still requires further prospective studies to verify and optimize personalized treatment strategies, ultimately improving patients’ long-term survival rates. 4. Discussion The comparison of matched cohorts in the SEER database showed that TCPM who received radiotherapy had significantly longer survival compared to those who did not undergo radiotherapy. Additionally, chemotherapy, age, and tumor differentiation were identified as important prognostic factors. The study suggests that radiotherapy is most effective in patients under 60 years old, those who received chemotherapy, and those with well-differentiated tumors. However, for patients with poorer prognoses, radiotherapy still provides survival benefits and should be considered in a variety of clinical situations. This may be related to the specific tumor microenvironment of tongue cancer and the rich lymphatic system surrounding it( 21 ). 4.1 Comparison with Previous SEER Analyses Currently, there is limited specific data on the use of radiotherapy for tongue cancer with pulmonary metastasis, making direct comparisons with previous studies difficult( 25 ). Most existing studies group head and neck squamous cell carcinoma (HNSCC) as a whole, and cases of tongue cancer are seldom analyzed separately. The distance from the tumor to the midline is a crucial factor in tongue cancer, and it may influence the response to radiotherapy( 11 ). This issue should be given special attention in future research. 4.2 Limitations of SEER Analysis The analysis of the SEER database has limitations, particularly the low resolution of data, especially in the incomplete recording of key clinical variables. For example, the database does not provide detailed information on the specific site and dose variations of radiotherapy, nor does it include data on the neutrophil-to-lymphocyte ratio (NLR), which are critical for clinical treatment and prognosis assessment( 18 , 22 ). Furthermore, the database does not include specific chemotherapy regimens, limiting the ability to further analyze the prognostic role of chemotherapy. Although immunotherapy is an emerging research focus, the SEER database does not separate it as a category, which is another limitation of this study( 16 ). Despite these constraints, the large sample size in our SEER analysis enhances the representativeness of the study, though there are still gaps in clinical detail. 4.3 Future Applications of Radiotherapy Our study demonstrates that the combined use of chemotherapy and radiotherapy significantly improves survival in tongue cancer patients with pulmonary metastasis, and radiotherapy has been confirmed as an effective survival predictor in multiple models. (Fig. 4 )However, the independent effect of radiotherapy still requires further prospective studies to verify its value in personalized treatment and to improve the long-term survival of these patients. Furthermore, in the future, if immunotherapy can be combined with radiotherapy, it may harness the abscopal effect of radiotherapy, synergizing with immunotherapy to target and eliminate distant metastatic tumors( 12 , 26 ). This approach holds promise not only for enhancing treatment efficacy but also for potentially reducing additional side effects( 23 ). 5. Conclusion This study indicates that radiotherapy may play a significant role in improving overall survival (OS) for tongue cancer patients with pulmonary metastasis, especially when combined with chemotherapy. The analysis revealed that patients receiving radiotherapy had a significantly longer median survival compared to those who did not receive radiotherapy. Moreover, several prognostic factors, including age, tumor differentiation, and chemotherapy, were identified as significant contributors to survival outcomes. Despite these findings, the independent impact of radiotherapy remains uncertain and warrants further investigation in prospective studies to fully assess its efficacy in tongue cancer patients with pulmonary metastasis. Additionally, the lack of specific data regarding radiotherapy sites and dosage in large databases like SEER limits the ability to draw comprehensive conclusions on the optimal radiotherapy protocols. However, the inclusion of radiotherapy in multiple high-ranking survival prediction models supports its continued use as a key treatment modality. Future research should aim to optimize treatment strategies, considering radiotherapy as part of a multimodal approach to improve the long-term survival of these patients. Declarations Consent to Publish declaration not applicable Author Contribution YQ C( Yiquan Chen) and YCM(Yichun Man ) contributed equally as co-first authors. YQC and YCM performed the research, analyzed data, and drafted the main manuscript text. HJ W(Haijun Wu) acted as the corresponding author, leading the study design, critically revising the manuscript, and supervising the publication process. All authors reviewed, revised, and approved the final version of the manuscript. Declaration of conflict of interest: None. Human Ethics and Consent to Participate declarations: not applicable. Fund Statement: Fund Statement Not Applicable. Clinical trial number: not applicable. Acknowledgement We acknowledge the Surveillance, Epidemiology, and End Results (SEER) Program for providing the data used in this study. Financial support is not applicable. The datasets analyzed in this study are publicly available. Consent to publish is not required as per the data provider’s terms of use. Consent to Publish declaration: not applicable Data Availability Statement The datasets analyzed during the current study are publicly available from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute ( https://seer.cancer.gov/ ). Access to SEER data requires submission of a research application. Processed data and supplementary tables/figures supporting the findings of this study are included in the manuscript and its supplementary information files. References Algudaibi LY, AlMeaigel S, AlQahtani N, Shaheen NA, Aboalela A. Oral and oropharyngeal cancer: Knowledge, attitude and practices among medical and dental practitioners. Cancer reports (Hoboken, N.J.) 4 (4): e1349, 2021. Almangush A, Mäkitie AA, Triantafyllou A, de Bree R, Strojan P, Rinaldo A, Hernandez-Prera JC, Suárez C, Kowalski LP, Ferlito A, Leivo I. Staging and grading of oral squamous cell carcinoma: An update. Oral oncology 107: 104799, 2020. Ansarin M, Bruschini R, Navach V, Giugliano G, Calabrese L, Chiesa F, Medina JE, Kowalski LP, Shah JP. Classification of GLOSSECTOMIES: Proposal for tongue cancer resections. Head & neck 41 (3): 821-827, 2019. Chakraborty PS, Das AK, Vatsyayan A, Rahman T, Das R, Medhi SK, Das K, Sharma JD. 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Yamagata K, Onizawa K, Otsuka Y, Yoshida H. Treatment for lung metastasis from head and neck squamous cell carcinoma: a preliminary study of docetaxel. Oral Maxillofac Surg 12 (1): 13-8, 2008. Yu D, Guo R, Zhu L. The risk and prognostic factors for lung metastases in oral squamous cell carcinoma: A population-based analysis of the SEER database. Journal of stomatology, oral and maxillofacial surgery 125 (3): 101713, 2024. Zhang Z, Liu X, Chen D, Yu J. Radiotherapy combined with immunotherapy: the dawn of cancer treatment. Signal Transduct Target Ther 7 (1): 258, 2022. Tables Table 1Clinical Characteristics of Tongue Cancer Patients with Pulmonary Metastasis. (N=67) (N=135) (N=68) Age χ2 = 0.44781 p = 0.799 Age19_30 2 (3.0%) 3 (2.2%) 1 (1.5%) Age30_60 15 (22.4%) 29 (21.5%) 14 (20.6%) Age60 50 (74.6%) 103 (76.3%) 53 (77.9%) Sex χ2 = 2.9638 p = 0.085 Female 19 (28.4%) 29 (21.5%) 10 (14.7%) Male 48 (71.6%) 106 (78.5%) 58 (85.3%) Race χ2 = 2.7391 p = 0.254 Black 1 (1.5%) 6 (4.4%) 5 (7.4%) Other 8 (11.9%) 16 (11.9%) 8 (11.8%) White 58 (86.6%) 113 (83.7%) 55 (80.9%) Marital.status χ2 = 1.5848 p = 0.903 Divorced 12 (17.9%) 22 (16.3%) 10 (14.7%) Married 30 (44.8%) 67 (49.6%) 37 (54.4%) Separated 2 (3.0%) 3 (2.2%) 1 (1.5%) Single 15 (22.4%) 29 (21.5%) 14 (20.6%) Unknown 3 (4.5%) 5 (3.7%) 2 (2.9%) Widowed 5 (7.5%) 9 (6.7%) 4 (5.9%) Grade χ2 = 3.7339 p = 0.443 Grade II 13 (19.4%) 25 (18.5%) 12 (17.6%) Grade III 16 (23.9%) 26 (19.3%) 10 (14.7%) Unknown 37 (55.2%) 79 (58.5%) 42 (61.8%) Grade I 1 (1.5%) 4 (3.0%) 3 (4.4%) Grade IV 0 (0%) 1 (0.7%) 1 (1.5%) T χ2 = 3.0271 p = 0.805 Blank(s) 35 (52.2%) 74 (54.8%) 39 (57.4%) T1 1 (1.5%) 2 (1.5%) 1 (1.5%) T2 7 (10.4%) 11 (8.1%) 4 (5.9%) T3 7 (10.4%) 15 (11.1%) 8 (11.8%) T4a 7 (10.4%) 10 (7.4%) 3 (4.4%) T4b 1 (1.5%) 3 (2.2%) 2 (2.9%) TX 9 (13.4%) 18 (13.3%) 9 (13.2%) Missing 0 (0%) 2 (1.5%) 2 (2.9%) N χ2 = 6.4677 p = 0.595 Blank(s) 35 (52.2%) 74 (54.8%) 39 (57.4%) N0 4 (6.0%) 8 (5.9%) 4 (5.9%) N1 1 (1.5%) 5 (3.7%) 4 (5.9%) N2b 12 (17.9%) 19 (14.1%) 7 (10.3%) N2c 7 (10.4%) 14 (10.4%) 7 (10.3%) N2NOS 1 (1.5%) 1 (0.7%) 0 (0%) N3 4 (6.0%) 7 (5.2%) 3 (4.4%) NX 3 (4.5%) 4 (3.0%) 1 (1.5%) N2a 0 (0%) 1 (0.7%) 1 (1.5%) Missing 0 (0%) 2 (1.5%) 2 (2.9%) Chemotherapy χ2 = 12.919 p < 0.001 No/Unknown 37 (55.2%) 53 (39.3%) 16 (23.5%) Yes 30 (44.8%) 82 (60.7%) 52 (76.5%) Table 2 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table2Flowchartforpatientscreening.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6350109","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448898915,"identity":"d63da664-1f57-4033-9e27-87a62aab7248","order_by":0,"name":"yi quan chen","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"yi","middleName":"quan","lastName":"chen","suffix":""},{"id":448898916,"identity":"209b1c48-e86a-4fa8-8bf1-c67deeaa179c","order_by":1,"name":"Yi-chun Man","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Yi-chun","middleName":"","lastName":"Man","suffix":""},{"id":448898917,"identity":"85b0e7e6-58b9-4287-9d14-3262b6d7a35f","order_by":2,"name":"Haijun Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3PsWvCUBDH8QuBZHmQ9SSQ/gsngUIh4L9yIrxNyOjWgqBDla4Ogv+Cm+vDA10irhk6RATnZGuhSO1aSpJuDu8z/74cB2BZ98j15fxBGPVWx6rgUdIi8ZWOIU1iQoipyHSLJAAKodT9NcJj5zTZtijGwHFK4mzCFz1iz0AwfeXaBMUx5wWJ+7Q0u5zVO2B2WNefEWBSJB6Y/iRnvADhsD55kNvmligwAy9lkubkZxMq0ki59oC5RdIVpbsLSqgzy1xko1XjL9FxL0X5hc9v/sypPq9JFEznDe//pv43tyzLsv70DQe0TF9Zve9XAAAAAElFTkSuQmCC","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Haijun","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2025-04-01 06:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6350109/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6350109/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82150377,"identity":"ef08de7c-0a6a-4049-8203-103cccac0233","added_by":"auto","created_at":"2025-05-07 07:15:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58137,"visible":true,"origin":"","legend":"\u003cp\u003eForest Plot of Median Survival Analysis for Various Factors.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/9454fcd3fbc2e1f401706d98.png"},{"id":82147193,"identity":"39574d1c-9a1d-4307-bdff-71c013caa4aa","added_by":"auto","created_at":"2025-05-07 06:59:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":169639,"visible":true,"origin":"","legend":"\u003cp\u003ea Kaplan - Meier Curve for Whether Receiving Radiotherapy.\u003c/p\u003e\n\u003cp\u003eb Kaplan - Meier Curve for Chemotherapy Sub - group Analysis.\u003c/p\u003e\n\u003cp\u003ec Kaplan - Meier Curve for Grade Sub - group Analysis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/ecc1f6b30915fcec18017386.png"},{"id":82147195,"identity":"2d0c81fb-9141-459e-b6f8-0bf30536a533","added_by":"auto","created_at":"2025-05-07 06:59:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":36868,"visible":true,"origin":"","legend":"\u003cp\u003eMultifactorial competitive risk model\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/855c55f797fb7b203adc5c79.png"},{"id":82148465,"identity":"a06c21d8-d115-45a7-a9ca-125cf969aa9c","added_by":"auto","created_at":"2025-05-07 07:07:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":134470,"visible":true,"origin":"","legend":"\u003cp\u003eSet of models created with forward-stepwise selection, ranked by corrected AIC.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/3eb2410891177015883ce209.png"},{"id":82148468,"identity":"9a518832-b2fd-4864-88c0-b13e6f4676c9","added_by":"auto","created_at":"2025-05-07 07:07:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":135915,"visible":true,"origin":"","legend":"\u003cp\u003everaged Cox proportional hazard ratios with 95% confidence intervals.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/75a6014d4e351d078833c11f.png"},{"id":85912838,"identity":"eaebf3bb-3518-4ce1-8cdc-c0dc1718babe","added_by":"auto","created_at":"2025-07-03 06:06:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1607870,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/3baab9b1-a58f-4ddd-85d1-0e021b2d94f5.pdf"},{"id":82147191,"identity":"f6aa9bf6-1fa4-48d2-865d-c0aa3bae0057","added_by":"auto","created_at":"2025-05-07 06:59:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24298,"visible":true,"origin":"","legend":"","description":"","filename":"Table2Flowchartforpatientscreening.docx","url":"https://assets-eu.researchsquare.com/files/rs-6350109/v1/c9c9394a366cfa01c7174db8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Survival analysis of patients with early distant metastasis of tongue cancer undergoing radiotherapy","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHead and neck squamous cell carcinoma (HNSCC) is a common and aggressive type of cancer, typically occurring in the oral cavity, pharynx, and larynx(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Treatment for this type of cancer generally relies on a combination of surgery, radiation therapy, and chemotherapy, with specific treatment plans determined by tumor stage, location, and the patient's overall health condition(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). However, among all types of HNSCC, tongue cancer presents a significant challenge due to its complex anatomical location and its tendency for early metastasis(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrent treatment guidelines recommend chemotherapy for patients with metastatic tongue cancer, as it is considered the standard treatment for distant metastasis(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Research indicates that the lungs are the most common site for metastasis in tongue cancer, with approximately 9.1% of patients developing pulmonary metastasis during disease progression(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This makes lung metastasis a common and prognostically significant phenomenon that occurs early in the disease course, significantly affecting the patient's overall survival (OS) and complicating treatment strategies(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough chemotherapy remains the primary treatment for tongue cancer patients with pulmonary metastasis, radiotherapy\u0026mdash;a local treatment modality\u0026mdash;can help by delivering high-energy radiation to kill tumor cells, alleviating tumor pressure on the lungs and controlling symptoms(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, the role of radiotherapy in improving survival for these patients has not yet been clearly recommended in clinical guidelines. Currently, most treatment guidelines classify tongue cancer as part of HNSCC, treating it under the same protocol as other head and neck cancers(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This approach does not consider the potential biological and metastatic differences between tongue cancer and other HNSCCs, underscoring the need for independent research specifically on tongue cancer(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eThis study aims to explore whether radiotherapy can be an effective treatment option to extend survival in tongue cancer patients with pulmonary metastasis(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). By analyzing clinical data from these patients, we seek to provide scientific evidence that fills the current gap in clinical guidelines for treating tongue cancer with pulmonary metastasis, offering new insights into the clinical management of this condition, especially in the application of combined treatment regimen for patients with lung metastasis.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Data Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is based on data from the SEER (Surveillance, Epidemiology, and End Results) database, which is established by the National Cancer Institute (NCI) and covers multiple regions in the United States, representing approximately 34.6% of the U.S. population (https://seer.cancer.gov, accessed on 30 January 2021). The SEER database contains demographic characteristics of patients, tumor pathology, treatment details, and follow-up data, providing high-quality retrospective data for this study(9). The cohort includes patients diagnosed with Tongue Cancer with Pulmonary Metastases (TCPM) from January 1, 2010, to December 31, 2021. Since the SEER database provides publicly available data with patient-identifiable information removed, ethical approval or patient written informed consent was not required for this study. The data used in this study were extracted through R (version 4.4.2) and based on the SEER research data submitted in November 2023(5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Study Cohort Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study cohort was selected from the SEER database based on the following criteria:\u003cbr\u003e\u0026nbsp;Inclusion Criteria: (i) Patients diagnosed with tongue cancer (ICD codes CD1.9-CD2.3, CD2.8-CD2.9) with pulmonary metastasis (M1 stage) between January 1, 2010, and December 31, 2019. (ii) Complete demographic records (gender, age, race, marital status) and tumor characteristics (T/N stage, differentiation) available. (iii) Clear treatment history, including whether the patient received radiotherapy (RT) and/or chemotherapy (CT).\u003c/p\u003e\n\u003cp\u003eExclusion Criteria:(i) Patients with other distant metastases (e.g., liver, bone, brain) to ensure the study population only includes patients with pulmonary metastasis. (ii) Patients with missing treatment data (including radiotherapy or chemotherapy). (iii) Patients with a survival time of less than one month, to avoid the instability of treatment intervention effects due to early death.\u003c/p\u003e\n\u003cp\u003eA total of 135 patients diagnosed with TCPM meeting the inclusion criteria were selected. The cohort was divided into two groups based on whether they received radiotherapy (RT): RT group and Non-RT group(Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Variables Collected\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following variables were collected: (i) Gender (ii) Age (either continuous or categorized) (iii) Race (White, Black, Other) (iv) Marital status (Married, Single/Divorced/Widowed) (v) Tumor grade (I\u0026ndash;II vs III\u0026ndash;IV) (vi) AJCC TNM staging (T stage, N stage) (vii) Radiotherapy (RT vs Non-RT) (viii) Chemotherapy (CT vs Non-CT) (ix) Overall survival (OS), defined as the time from diagnosis to death (measured in months).The SEER database does not contain information on specific chemotherapy regimens or patient quality of life. However, it provides reliable data support for large-scale population studies. The final follow-up for this study was conducted on December 31, 2021.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Matching method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, PSM was not conducted due to the following reasons: (i) Baseline Balance Between Groups: After selection, the ratio of RT group to Non-RT group was 1:1, and the variables, except chemotherapy, had P \u0026gt; 0.05, indicating no significant imbalance, making matching unnecessary. (ii) Standard Treatment and Clinical Practice: Although current guidelines recommend chemotherapy as the standard treatment for distant metastasis in tongue cancer, clinical practice often involves adding radiotherapy (RT) to improve local control or alleviate symptoms. (iii) Clinical Practice Trends: Patients who refuse chemotherapy are unlikely to undergo radiotherapy, and matching such patients might lead to a significant reduction in sample size, decreasing the representativeness of the study. (iv) Adjustment for Bias Using Alternative Methods: To adjust for the impact of chemotherapy on OS, Cox regression models were used for multivariate survival analysis, avoiding potential data loss and statistical bias caused by PSM. Considering the data balance and clinical practice, direct survival analysis was deemed more appropriate than PSM in this study(17).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Survival Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed the following survival analysis methods: (i)Kaplan-Meier survival curves were used to assess survival rates in the different treatment groups, with Log-rank tests comparing the survival differences between the RT and Non-RT groups. (ii)Cox Proportional Hazard Model was used to calculate the effect of radiotherapy (RT) on survival for TCPM patients and conduct multivariate adjustment for potential confounding factors such as age, tumor grade, and T/N stage. (iii)Results were expressed in terms of hazard ratios (HR) with their 95% confidence intervals (CI). A P-value \u0026lt; 0.05 was considered statistically significant. All data analyses were performe d using R( version 4.4.2.)\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Selection of Study Cohort and Baseline Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 135 patients with tongue cancer and pulmonary metastases (TCPM) were included in this study. Among them, 68 patients received radiotherapy (RT) and 67 patients did not (Non-RT group), with a near 1:1 ratio (Table 1).\u0026nbsp;\u003cbr\u003e\u0026nbsp;Baseline characteristics comparison showed no significant differences between the two groups for most variables, except for chemotherapy, which was statistically significant. This suggests that patients receiving radiotherapy were more likely to have chemotherapy, while patients who did not receive chemotherapy typically did not undergo radiotherapy. Due to the balanced characteristics between the groups, propensity score matching (PSM) was not conducted, and Cox regression models were directly used to adjust for the impact of chemotherapy on survival outcomes, to avoid sample size reduction and loss of statistical power from matching.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Survival Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaplan-Meier survival analysis (Figure 2a) revealed that the RT group had a significantly longer median overall survival (OS) compared to the Non-RT group (P = 0.0063), suggesting that radiotherapy may have a positive impact on survival. The forest plot (Figure 1) further illustrated the median OS and 95% confidence intervals for different subgroups of patients. Overall, radiotherapy showed survival advantages in multiple subgroups, although there was considerable variability in the results for some subgroups, indicating that the exact survival benefits need further verification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Prognostic Factors, Model Evaluation, and Clinical Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrognostic Factors Analysis: Multivariate Cox regression analysis (Figures 3 and 5) showed that radiotherapy (RT), chemotherapy (chemo), tumor grade (Grade), age, and sex all significantly influenced survival outcomes in tongue cancer patients with pulmonary metastasis:\u0026nbsp;\u003cbr\u003e\u0026nbsp;(i) Radiotherapy (RT): HR = 0.57 (P = 0.007), indicating that radiotherapy significantly reduces the risk of death. (ii) Chemotherapy (chemo): HR = 0.43 (P = 0.006), suggesting that chemotherapy is also an important factor in improving survival. (iii) Tumor Grade: Patients with poorly differentiated tumors (Grade III-IV) had a lower survival rate compared to those with well-differentiated tumors (Grade I-II), but the result did not reach statistical significance. (iv) Age: Patients over 60 years had a higher risk of mortality (HR \u0026gt; 1), suggesting that older age may be a potential negative factor for survival. (v) Sex: Male patients had a slightly higher risk of death compared to females, but this difference was not statistically significant.\u003c/p\u003e\n\u003cp\u003eModel Evaluation:\u003cbr\u003e\u0026nbsp;Analysis of Akaike Information Criterion corrected (AICc) (Figure 4) showed that the best-fitting Cox regression model had an AICc = 899.37, with the top four models having similar AICc values, indicating the importance of radiotherapy (RT) in survival prediction. Multiple high-ranking models included the radiotherapy variable, further supporting its role as an important factor influencing survival.\u003c/p\u003e\n\u003cp\u003eClinical Implications of the Findings:\u003cbr\u003e\u0026nbsp;The results of this study suggest that the combined use of radiotherapy and chemotherapy can improve survival rates in tongue cancer patients with pulmonary metastasis. Additionally, tumor differentiation, age, and sex may influence individual survival outcomes. Radiotherapy was included in several of the optimal survival prediction models, further supporting its role as a key component of treatment for tongue cancer with pulmonary metastasis. However, the independent role of radiotherapy still requires further prospective studies to verify and optimize personalized treatment strategies, ultimately improving patients’ long-term survival rates.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe comparison of matched cohorts in the SEER database showed that TCPM who received radiotherapy had significantly longer survival compared to those who did not undergo radiotherapy. Additionally, chemotherapy, age, and tumor differentiation were identified as important prognostic factors. The study suggests that radiotherapy is most effective in patients under 60 years old, those who received chemotherapy, and those with well-differentiated tumors. However, for patients with poorer prognoses, radiotherapy still provides survival benefits and should be considered in a variety of clinical situations. This may be related to the specific tumor microenvironment of tongue cancer and the rich lymphatic system surrounding it(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Comparison with Previous SEER Analyses\u003c/h2\u003e \u003cp\u003eCurrently, there is limited specific data on the use of radiotherapy for tongue cancer with pulmonary metastasis, making direct comparisons with previous studies difficult(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Most existing studies group head and neck squamous cell carcinoma (HNSCC) as a whole, and cases of tongue cancer are seldom analyzed separately. The distance from the tumor to the midline is a crucial factor in tongue cancer, and it may influence the response to radiotherapy(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This issue should be given special attention in future research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Limitations of SEER Analysis\u003c/h2\u003e \u003cp\u003eThe analysis of the SEER database has limitations, particularly the low resolution of data, especially in the incomplete recording of key clinical variables. For example, the database does not provide detailed information on the specific site and dose variations of radiotherapy, nor does it include data on the neutrophil-to-lymphocyte ratio (NLR), which are critical for clinical treatment and prognosis assessment(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Furthermore, the database does not include specific chemotherapy regimens, limiting the ability to further analyze the prognostic role of chemotherapy. Although immunotherapy is an emerging research focus, the SEER database does not separate it as a category, which is another limitation of this study(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Despite these constraints, the large sample size in our SEER analysis enhances the representativeness of the study, though there are still gaps in clinical detail.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Future Applications of Radiotherapy\u003c/h2\u003e \u003cp\u003eOur study demonstrates that the combined use of chemotherapy and radiotherapy significantly improves survival in tongue cancer patients with pulmonary metastasis, and radiotherapy has been confirmed as an effective survival predictor in multiple models. (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e)However, the independent effect of radiotherapy still requires further prospective studies to verify its value in personalized treatment and to improve the long-term survival of these patients. Furthermore, in the future, if immunotherapy can be combined with radiotherapy, it may harness the abscopal effect of radiotherapy, synergizing with immunotherapy to target and eliminate distant metastatic tumors(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This approach holds promise not only for enhancing treatment efficacy but also for potentially reducing additional side effects(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e "},{"header":"5. Conclusion","content":"\u003cp\u003eThis study indicates that radiotherapy may play a significant role in improving overall survival (OS) for tongue cancer patients with pulmonary metastasis, especially when combined with chemotherapy. The analysis revealed that patients receiving radiotherapy had a significantly longer median survival compared to those who did not receive radiotherapy. Moreover, several prognostic factors, including age, tumor differentiation, and chemotherapy, were identified as significant contributors to survival outcomes.\u003c/p\u003e\u003cp\u003eDespite these findings, the independent impact of radiotherapy remains uncertain and warrants further investigation in prospective studies to fully assess its efficacy in tongue cancer patients with pulmonary metastasis. Additionally, the lack of specific data regarding radiotherapy sites and dosage in large databases like SEER limits the ability to draw comprehensive conclusions on the optimal radiotherapy protocols. However, the inclusion of radiotherapy in multiple high-ranking survival prediction models supports its continued use as a key treatment modality. Future research should aim to optimize treatment strategies, considering radiotherapy as part of a multimodal approach to improve the long-term survival of these patients.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eConsent to Publish declaration\u003c/h2\u003e \u003cp\u003e \u003cb\u003enot applicable\u003c/b\u003e \u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYQ C( Yiquan Chen) and YCM(Yichun Man ) contributed equally as co-first authors. YQC and YCM performed the research, analyzed data, and drafted the main manuscript text. HJ W(Haijun Wu) acted as the corresponding author, leading the study design, critically revising the manuscript, and supervising the publication process. All authors reviewed, revised, and approved the final version of the manuscript.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDeclaration of conflict of interest: None.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations: not applicable.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFund Statement: Fund Statement Not Applicable.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number: not applicable.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWe acknowledge the Surveillance, Epidemiology, and End Results (SEER) Program for providing the data used in this study. Financial support is not applicable.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe datasets analyzed in this study are publicly available. Consent to publish is not required as per the data provider\u0026rsquo;s terms of use.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration: not applicable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003cbr\u003e\u0026nbsp;The datasets analyzed during the current study are publicly available from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute (\u003c/strong\u003e\u003cstrong\u003ehttps://seer.cancer.gov/\u003c/strong\u003e\u003cstrong\u003e). Access to SEER data requires submission of a research application. Processed data and supplementary tables/figures supporting the findings of this study are included in the manuscript and its supplementary information files.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlgudaibi LY, AlMeaigel S, AlQahtani N, Shaheen NA, Aboalela A. Oral and oropharyngeal cancer: Knowledge, attitude and practices among medical and dental practitioners. Cancer reports (Hoboken, N.J.) 4 (4): e1349, 2021.\u003c/li\u003e\n\u003cli\u003eAlmangush A, M\u0026auml;kitie AA, Triantafyllou A, de Bree R, Strojan P, Rinaldo A, Hernandez-Prera JC, Su\u0026aacute;rez C, Kowalski LP, Ferlito A, Leivo I. Staging and grading of oral squamous cell carcinoma: An update. Oral oncology 107: 104799, 2020.\u003c/li\u003e\n\u003cli\u003eAnsarin M, Bruschini R, Navach V, Giugliano G, Calabrese L, Chiesa F, Medina JE, Kowalski LP, Shah JP. Classification of GLOSSECTOMIES: Proposal for tongue cancer resections. Head \u0026amp; neck 41 (3): 821-827, 2019.\u003c/li\u003e\n\u003cli\u003eChakraborty PS, Das AK, Vatsyayan A, Rahman T, Das R, Medhi SK, Das K, Sharma JD. Metastatic involvement of level IIb nodal station in oral squamous cell carcinoma: A clinicopathological study. Natl J Maxillofac Surg 10 (1): 8-12, 2019.\u003c/li\u003e\n\u003cli\u003eChan B. Data Analysis Using R Programming. Adv Exp Med Biol 1082: 47-122, 2018.\u003c/li\u003e\n\u003cli\u003eCitrin DE. Recent Developments in Radiotherapy. The New England journal of medicine 377 (11): 1065-1075, 2017.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Cruz AK, Vaish R, Dhar H. Oral cancers: Current status. Oral Oncol 87: 64-69, 2018.\u003c/li\u003e\n\u003cli\u003eHageman E, Che P, Dahele M, Slotman BJ, Sminia P. Radiobiological Aspects of FLASH Radiotherapy. Biomolecules 12 (10), 2022.\u003c/li\u003e\n\u003cli\u003eHayat MJ, Howlader N, Reichman ME, Edwards BK. Cancer statistics, trends, and multiple primary cancer analyses from the Surveillance, Epidemiology, and End Results (SEER) Program. The oncologist 12 (1): 20-37, 2007.\u003c/li\u003e\n\u003cli\u003eJohnson DE, Burtness B, Leemans CR, Lui V, Bauman JE, Grandis JR. Head and neck squamous cell carcinoma. Nat Rev Dis Primers 6 (1): 92, 2020.\u003c/li\u003e\n\u003cli\u003eKikuta S, Todoroki K, Seki N, Kusukawa J. Adenosquamous Carcinoma in the Midline Dorsum of the Tongue: A Rare Case Report. Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons 76 (10): 2131-2135, 2018.\u003c/li\u003e\n\u003cli\u003eLiu S, Wang W, Hu S, Jia B, Tuo B, Sun H, Wang Q, Liu Y, Sun Z. Radiotherapy remodels the tumor microenvironment for enhancing immunotherapeutic sensitivity. Cell Death Dis 14 (10): 679, 2023.\u003c/li\u003e\n\u003cli\u003eMoro JDS, Maroneze MC, Ardenghi TM, Barin LM, Danesi CC. Oral and oropharyngeal cancer: epidemiology and survival analysis. Einstein (Sao Paulo, Brazil) 16 (2): eAO4248, 2018.\u003c/li\u003e\n\u003cli\u003eNabors B, Portnow J, Hattangadi-Gluth J, Horbinski C. NCCN CNS tumor guidelines update for 2023. Neuro-oncology 25 (12): 2114-2116, 2023.\u003c/li\u003e\n\u003cli\u003ePfister DG, Spencer S, Adelstein D, Adkins D, Anzai Y, Brizel DM, Bruce JY, Busse PM, Caudell JJ, Cmelak AJ, Colevas AD, Eisele DW, Fenton M, Foote RL, Galloway T, Gillison ML, Haddad RI, Hicks WL, Hitchcock YJ, Jimeno A, Leizman D, Maghami E, Mell LK, Mittal BB, Pinto HA, Ridge JA, Rocco JW, Rodriguez CP, Shah JP, Weber RS, Weinstein G, Witek M, Worden F, Yom SS, Zhen W, Burns JL, Darlow SD. Head and Neck Cancers, Version 2.2020, NCCN Clinical Practice Guidelines in Oncology. Journal of the National Comprehensive Cancer Network : JNCCN 18 (7): 873-898, 2020.\u003c/li\u003e\n\u003cli\u003eRao YJ, Goodman JF, Haroun F, Bauman JE. Integrating Immunotherapy into Multimodal Treatment of Head and Neck Cancer. Cancers (Basel) 15 (3), 2023.\u003c/li\u003e\n\u003cli\u003eSchober P, Mascha EJ, Vetter TR. Statistics From A (Agreement) to Z (z Score): A Guide to Interpreting Common Measures of Association, Agreement, Diagnostic Accuracy, Effect Size, Heterogeneity, and Reliability in Medical Research. Anesthesia and analgesia 133 (6): 1633-1641, 2021.\u003c/li\u003e\n\u003cli\u003eShaul ME, Fridlender ZG. Tumour-associated neutrophils in patients with cancer. Nat Rev Clin Oncol 16 (10): 601-620, 2019.\u003c/li\u003e\n\u003cli\u003eShiboski CH, Schmidt BL, Jordan RCK. Tongue and tonsil carcinoma: increasing trends in the U.S. population ages 20-44 years. Cancer 103 (9): 1843-9, 2005.\u003c/li\u003e\n\u003cli\u003eSiegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA: a cancer journal for clinicians 71 (1): 7-33, 2021.\u003c/li\u003e\n\u003cli\u003eTao W, Li-Juan Z, Kan L, Jing-Yuan L, Xiang-Qi L, Yu-Jie L. The Microenvironment of Tongue Cancer. Adv Exp Med Biol 1296: 49-78, 2020.\u003c/li\u003e\n\u003cli\u003eVorwerk H, Hess CF. Guidelines for delineation of lymphatic clinical target volumes for high conformal radiotherapy: head and neck region. Radiat Oncol 6: 97, 2011.\u003c/li\u003e\n\u003cli\u003eXia WY, Shen YJ, Zhang CC, Qian LQ, Wang H, Wang K, Jin HZ, Zhu XR, Ding ZP, Zhang Q, Yu W, Feng W, Fu XL. Combination of radiotherapy and PD-L1 blockade induces abscopal responses in EGFR-mutated lung cancer through activating CD8(+) T cells. Transl Oncol 48: 102074, 2024.\u003c/li\u003e\n\u003cli\u003eYamagata K, Onizawa K, Otsuka Y, Yoshida H. Treatment for lung metastasis from head and neck squamous cell carcinoma: a preliminary study of docetaxel. Oral Maxillofac Surg 12 (1): 13-8, 2008.\u003c/li\u003e\n\u003cli\u003eYu D, Guo R, Zhu L. The risk and prognostic factors for lung metastases in oral squamous cell carcinoma: A population-based analysis of the SEER database. Journal of stomatology, oral and maxillofacial surgery 125 (3): 101713, 2024.\u003c/li\u003e\n\u003cli\u003eZhang Z, Liu X, Chen D, Yu J. Radiotherapy combined with immunotherapy: the dawn of cancer treatment. Signal Transduct Target Ther 7 (1): 258, 2022.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1Clinical Characteristics of Tongue Cancer Patients with Pulmonary Metastasis.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(N=67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(N=135)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(N=68)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 0.44781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAge19_30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAge30_60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e15 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e29 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e14 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAge60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e50 (74.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e103 (76.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e53 (77.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 2.9638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e19 (28.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e29 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e10 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e48 (71.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e106 (78.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e58 (85.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 2.7391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e6 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e8 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e16 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e8 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e58 (86.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e113 (83.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e55 (80.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital.status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 1.5848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e12 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e22 (16.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e10 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e30 (44.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e67 (49.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e37 (54.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e15 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e29 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e14 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e5 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e9 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 3.7339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGrade II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e13 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e25 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e12 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGrade III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e16 (23.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e26 (19.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e10 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e37 (55.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e79 (58.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e42 (61.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGrade I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e4 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGrade IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 3.0271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBlank(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e35 (52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e74 (54.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e39 (57.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e11 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e15 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e8 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eT4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e10 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eT4b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eTX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e9 (13.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e18 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e9 (13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 6.4677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep = 0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBlank(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e35 (52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e74 (54.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e39 (57.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e8 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e5 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN2b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e12 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e19 (14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN2c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e14 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN2NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e7 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e4 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eN2a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026chi;2 = 12.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNo/Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e37 (55.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e53 (39.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e16 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e30 (44.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e82 (60.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e52 (76.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 is available in the Supplementary Files section.\u003c/p\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":"Tongue cancer, pulmonary metastasis, radiotherapy, overall survival, SEER database, survival analysis, Cox regression","lastPublishedDoi":"10.21203/rs.3.rs-6350109/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6350109/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTongue cancer is a common head - neck malignancy, and lung is the most frequent site of its distant metastasis. Chemotherapy is widely used for tongue cancer with pulmonary metastasis, yet the effectiveness of radiotherapy as a local treatment lacks clear recommendation in clinical guidelines. The core objective of this study is to delve into whether, for patients with early - stage metastatic tongue cancer, the combined treatment approach of adding radiotherapy to chemotherapy can effectively extend their effective survival period.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBased on the SEER database, we analyzed tongue cancer patients with pulmonary metastasis diagnosed from January 1, 2010, to December 31, 2021. Inclusion criteria were tongue cancer (M1 stage) with pulmonary metastasis. Kaplan - Meier survival curves and Cox regression models evaluated radiotherapy's effect on OS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 135 patients, 68 received radiotherapy (RT group) and 67 did not (Non - RT group). Kaplan - Meier analysis showed the RT group had a significantly longer median OS ((P\u0026thinsp;=\u0026thinsp;0.0063)). Multivariate Cox regression indicated radiotherapy significantly reduced the death risk (HR\u0026thinsp;=\u0026thinsp;0.57, (P\u0026thinsp;=\u0026thinsp;0.007)).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRadiotherapy may positively impact the OS of tongue cancer patients with pulmonary metastasis, especially when combined with chemotherapy. Although it's an effective survival predictor in some models, further prospective studies are needed to verify its independent effect for personalized treatment. It may be effective to consider radiotherapy as a complementary treatment measure while exercising chemotherapy.\u003c/p\u003e","manuscriptTitle":"Survival analysis of patients with early distant metastasis of tongue cancer undergoing radiotherapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:59:38","doi":"10.21203/rs.3.rs-6350109/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":"11b1411e-4096-408b-a0bc-a3c2021f399d","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-24T11:08:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 06:59:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6350109","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6350109","identity":"rs-6350109","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}