Advanced Search
LI Liang, CHEN Renjie, YU Zuhua. Treatment Strategies and Prognostic Factors in Patients with Stage T3 and T4 Laryngeal Carcinoma[J]. Cancer Research on Prevention and Treatment, 2023, 50(3): 258-263. DOI: 10.3971/j.issn.1000-8578.2023.22.0725
Citation: LI Liang, CHEN Renjie, YU Zuhua. Treatment Strategies and Prognostic Factors in Patients with Stage T3 and T4 Laryngeal Carcinoma[J]. Cancer Research on Prevention and Treatment, 2023, 50(3): 258-263. DOI: 10.3971/j.issn.1000-8578.2023.22.0725

Treatment Strategies and Prognostic Factors in Patients with Stage T3 and T4 Laryngeal Carcinoma

More Information
  • Corresponding author:

    CHEN Renjie,E-mail: nyefyebh@163.com

  • Received Date: June 26, 2022
  • Revised Date: September 14, 2022
  • Available Online: January 12, 2024
  • Objective 

    To investigate the selection of treatment strategies and prognostic factors for patients with stage T3 and T4 laryngeal carcinoma.

    Methods 

    A total of 132 patients with stage T3 and T4 laryngeal cancer admitted to our hospital from March 2010 to March 2019 were retrospectively selected as research objects. According to the different treatment strategies, the patients were divided into simple surgery group (group A, 57 cases), simple chemoradiotherapy group (group B, 32 cases), and surgery combined with chemoradiotherapy group (group C, 43 cases). The general data and clinicopathological features of the three groups were compared, and a survival curve was drawn by the Kaplan–Meier method. The 3-year survival rates of the three groups were compared. Then, the same 132 patients were divided into survival and death groups. The clinical data of the two groups were compared, and the prognostic factors were analyzed by multivariate logistic regression. A back propagation (BP) neural network model was constructed, and its differentiation and accuracy were evaluated.

    Results 

    The proportions and 3 year survival rates of patients with poor differentiation, lymphatic vascular invasion, and involvement of lymph nodes outside the capsule in group C were significantly higher than those in groups A and B (P < 0.05). The 3 year survival rate of 132 patients was 68.94%(41/132). Poor differentiation, N2-N3 stage, lymphatic vascular invasion, and involvement of lymph nodes outside the capsule were risk factors for death (P < 0.05), whereas surgery combined with radiotherapy and chemotherapy were protective factors (P < 0.05). The BP neural network model exhibited good discrimination and high accuracy.

    Conclusion 

    Surgery combined with radiotherapy and chemotherapy can significantly improve survival rate in patients with poor differentiation, lymphatic vascular invasion, and involvement of lymph nodes outside the capsule. Close attention should be paid to patients with stage N2-N3 in the formulation of reasonable treatment strategies.

  • Competing interests: The authors declare that they have no competing interests.

  • [1]
    Lauwerends LJ, Galema HA, Hardillo JAU, et al. Current Intraoperative Imaging Techniques to Improve Surgical Resection of Laryngeal Cancer: A Systematic Review[J]. Cancers (Basel), 2021, 13(8): 1895. doi: 10.3390/cancers13081895
    [2]
    Vander Poorten V, Meulemans J, Van Lierde C, et al. Current indications for adjuvant treatment following transoral laser microsurgery of early intermediate laryngeal cancer[J]. Curr Opin Otolaryngol Head Neck Surg, 2021, 29(2): 79-85. doi: 10.1097/MOO.0000000000000702
    [3]
    Hsin LJ, Chuang HH, Lin MY, et al. Laryngeal Helicobacter pylori Infection and Laryngeal Cancer-Case Series and a Systematic Review[J]. Microorganisms, 2021, 9(6): 1129. doi: 10.3390/microorganisms9061129
    [4]
    Massa ST, Mazul AL, Puram SV, et al. Association of demographic and geospatial factors with treatment selection for laryngeal cancer[J]. JAMA Otolaryngol Head Neck Surg, 2021, 147(7): 590-598. doi: 10.1001/jamaoto.2021.0453
    [5]
    Campo F, Zocchi J, Ralli M, et al. Laser microsurgery versus radiotherapy versus open partial laryngectomy for T2 laryngeal carcinoma: a systematic review of oncological outcomes[J]. Ear Nose Throat J, 2021, 100(1_suppl): 51S-58S. doi: 10.1177/0145561320928198
    [6]
    Vilaseca I, Aviles-Jurado FX, Valduvieco I, et al. Transoral laser microsurgery in locally advanced laryngeal cancer: Prognostic i mpact of anterior versus posterior compartments[J]. Head Neck, 2021, 43(12): 3832-3842. doi: 10.1002/hed.26878
    [7]
    de Andrade NMM, Dedivitis RA, Ramos DM, et al. Tumor volume as a prognostic factor of locally advanced laryngeal cancer[J]. Eur Arch Otorhinolaryngol, 2021, 278(5): 1627-1635. doi: 10.1007/s00405-020-06438-1
    [8]
    Zhang H, Zou Y, Tian F, et al. Dual-energy CT may predict postoperative recurrence in early-stage glottic laryngeal cancer: a novel nomogram and risk stratification system[J]. Eur Radiol, 2022, 32(3): 1921-1930. doi: 10.1007/s00330-021-08265-2
    [9]
    Bradley PJ, Piazza C, Paderno A. A roadmap of six different pathways to improve survival in laryngeal cancer patients[J]. Curr Opin Otolaryngol Head Neck Surg, 2021, 29(2): 65-78. doi: 10.1097/MOO.0000000000000684
    [10]
    Atasever Akkas E, Yucel B. Prognostic value of systemic ımmune ınflammation ındex in patients with laryngeal cancer[J]. Eur Arch Otorhinolaryngol, 2021, 278(6): 1945-1955. doi: 10.1007/s00405-021-06798-2
    [11]
    陶文林, 李燃, 李会磊, 等. C-反应蛋白、纤维蛋白原、血小板/淋巴细胞比值与喉癌术后患者生存预后的关系[J]. 标记免疫分析与临床, 2020, 27(3): 387-392. https://www.cnki.com.cn/Article/CJFDTOTAL-BJMY202003007.htm

    Tao WL, Li R, Li HL, et al. The relationship between c-reactive protein, fibrinogen, platelet/lymphocyte ratio and survival prognosis in patients with postoperative laryngeal caccer[J]. Biao Ji Mian Yi Fen Xi Yu Lin Chuang, 2020, 27(3): 387-392. https://www.cnki.com.cn/Article/CJFDTOTAL-BJMY202003007.htm
    [12]
    邹庆云, 刘映岐, 查旭东, 等. 174例喉癌患者手术预后及影响因素分析[J]. 中国耳鼻咽喉颅底外科杂志, 2020, 26(4): 421-425. https://www.cnki.com.cn/Article/CJFDTOTAL-ZEBY202004015.htm

    Zou QY, Liu YQ, Zha XD, et al. Analysis of surgical prognosis and influencing factors of 174 laryngeal carcinoma patients[J]. Zhongguo Er Bi Yan Hou Lu Di Wai Ke Za Zhi, 2020, 26(4): 421-425. https://www.cnki.com.cn/Article/CJFDTOTAL-ZEBY202004015.htm
    [13]
    陶磊, 周梁, 张明, 等. T3~T4期下咽鳞状细胞癌患者术后预后相关风险因素及辅助治疗方案选择[J]. 临床耳鼻咽喉头颈外科杂志, 2021, 35(5): 400-404, 409. https://www.cnki.com.cn/Article/CJFDTOTAL-LCEH202105005.htm

    Tao L, Zhou L, Zhang M, et al. Prognostic risk factors and adjuvant treatment options in patients with stage T3-T4 hypopharyngeal squamous cell carcinoma[J]. Lin Chuang Er Bi Yan Hou Tou Jing Wai Ke Za Zhi, 2021, 35(5): 400-404, 409. https://www.cnki.com.cn/Article/CJFDTOTAL-LCEH202105005.htm
  • Related Articles

    [1]QIN Wenhua, FENG Xin, WANG Zengzhou, CHU Shangnan, WANG Hong, WU Shiyu, CHEN Cheng, HUAN Fukui, LIANG Bin, ZHANG Tao. Setup Error and Its Influencing Factors in Radiotherapy for Spinal Metastasis[J]. Cancer Research on Prevention and Treatment, 2025, 52(5): 400-404. DOI: 10.3971/j.issn.1000-8578.2025.24.1084
    [2]ZHOU Jieli, WU Linjuan, ZHANG Pengtian, Peng Yanxia, HAN Dong. Prediction of pN Staging of Papillary Thyroid Carcinoma Using Ultrasonography Radiomics and Deep Neural Networks[J]. Cancer Research on Prevention and Treatment, 2025, 52(2): 151-155. DOI: 10.3971/j.issn.1000-8578.2025.24.0617
    [3]NIU Quan, BI Xiaogang. Risk Factors and Prognosis of Patients with Para-Aortic Lymph Node Metastasis of Advanced Esophagogastric Junction Malignancy[J]. Cancer Research on Prevention and Treatment, 2024, 51(11): 918-925. DOI: 10.3971/j.issn.1000-8578.2024.24.0272
    [4]WU Yang, LI Tian, SHI Tingting, ZHU Lingling, ZHANG Yani, GUO Peipei, ZHANG Runbing, WANG Shunna, GAO Chun, YU Xiaohui, ZHANG Jiucong. Influencing Factors of Overall Survival of Elderly Patients with Hepatocellular Carcinoma and Construction of Prediction Model of Prognosis Nomogram: A Population-Based Study[J]. Cancer Research on Prevention and Treatment, 2024, 51(9): 756-763. DOI: 10.3971/j.issn.1000-8578.2024.24.0009
    [5]LIU Lingtao, LIU Yuwen, HUANG Jinquan, ZHANG Chu, CHEN Xingzhi. A Bibliometric Study of Oncology Imaging Diagnosis Based on Convolutional Neural Networks[J]. Cancer Research on Prevention and Treatment, 2023, 50(5): 512-517. DOI: 10.3971/j.issn.1000-8578.2023.22.1123
    [6]HAN Dong, ZHANG Xirong, JIA Yongjun, REN Ge, LYU Ruihua, SHI Linna, HE Taiping. A Neural Network Model Based on Enhanced CT for Distinguishing ISUP Grade of Clear Cell Renal Cell Carcinoma[J]. Cancer Research on Prevention and Treatment, 2021, 48(1): 55-59. DOI: 10.3971/j.issn.1000-8578.2021.20.0440
    [7]WEI Xueyan, LI Ying, HU Desheng. Nutritional Status and Its Influencing Factors of Nasopharyngeal Carcinoma Patients During Chemoradiotherapy[J]. Cancer Research on Prevention and Treatment, 2020, 47(7): 524-530. DOI: 10.3971/j.issn.1000-8578.2020.20.0280
    [8]Cai Hongning, Zhang Lei, Zhang Dunlan, Gao Han, Luo Jun. Application of Artificial Neural Networks in Prediction of Prognosis of Cervical Cancer[J]. Cancer Research on Prevention and Treatment, 2012, 39(09): 1117-1119. DOI: 10.3971/j.issn.1000-8578.2012.09.015
    [9]HUANG Jin-qiu, PENG Min-hao, ZOU Quan-qing, YANG Ding-hua, CHEN Bin, XIAO Kai-yin. Cox Model Analysis of Prognostic Factors after Radical Hepatectomy for Primary Hepatocellular Carcinoma[J]. Cancer Research on Prevention and Treatment, 2009, 36(02): 137-139. DOI: 10.3971/j.issn.1000-8578.2009.02.015
    [10]WANG Xin, NIE Shao-fa. Study on Factors Influencing Survial in Patients with Colorectal Cancer after Resection by COX Proportional Hazard Model[J]. Cancer Research on Prevention and Treatment, 2006, 33(04): 286-287. DOI: 10.3971/j.issn.1000-8578.3372
  • Cited by

    Periodical cited type(4)

    1. 刘川,马玮,王志海,李彦仕,潘敏,曾泉,胡国华. pT3N0期喉鳞癌的临床治疗策略. 临床耳鼻咽喉头颈外科杂志. 2025(01): 61-65 .
    2. 彭丽娜,武川军,要兆旭,赵倩,韩海平. 沉默miR-373对喉癌细胞增殖、凋亡能力的影响及作用机制研究. 中国耳鼻咽喉头颈外科. 2024(06): 346-350 .
    3. 张寒,张胜利,祖媛媛. 声门上型喉癌手术患者预后的预测模型构建. 国际医药卫生导报. 2024(11): 1796-1801 .
    4. 郭珊珊,杨文婧,许丽萍,陶倩,王欢,王书谦. 喉癌治疗后复发的影响因素分析及预测模型构建. 山东医药. 2023(33): 27-31 .

    Other cited types(0)

Catalog

    Figures(4)  /  Tables(2)

    Article views (1689) PDF downloads (1114) Cited by(4)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return