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李亮, 陈仁杰, 俞祖华. T3、T4期喉癌患者治疗策略选择及预后影响因素[J]. 肿瘤防治研究, 2023, 50(3): 258-263. DOI: 10.3971/j.issn.1000-8578.2023.22.0725
引用本文: 李亮, 陈仁杰, 俞祖华. T3、T4期喉癌患者治疗策略选择及预后影响因素[J]. 肿瘤防治研究, 2023, 50(3): 258-263. DOI: 10.3971/j.issn.1000-8578.2023.22.0725
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

T3、T4期喉癌患者治疗策略选择及预后影响因素

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

  • 摘要:
    目的 探讨T3、T4期喉癌患者治疗策略的选择及预后影响因素。
    方法 回顾性选择2010年3月— 2019年3月我院收治的132例T3、T4期喉癌患者作为研究对象,根据治疗策略的不同将患者分为单纯手术组(A组57例)、单纯放化疗组(B组32例)和手术联合放化疗组(C组43例)。比较三组的一般资料及临床病理特征;Kaplan-Meier法绘制生存曲线,比较三组患者的3年生存率;并将132例患者分为存活组和死亡组,比较两组患者的临床资料;多因素Logistic回归分析影响患者预后的因素,并构建反向传播(BP)神经网络模型,评价模型的区分度和准确性。
    结果 C组肿瘤低分化、淋巴血管侵犯、淋巴结包膜外侵犯患者比例及3年生存率明显高于A组和B组(P < 0.05);132例患者3年生存率为68.94%(41/132);肿瘤低分化、N2~N3期、淋巴血管侵犯、淋巴结包膜外侵犯是导致患者死亡的危险因素(P < 0.05),手术联合放化疗是保护因素(P < 0.05);BP神经网络模型预测的区分度较好,准确性较高。
    结论 肿瘤低分化、淋巴血管侵犯、淋巴结包膜外侵犯的患者采用手术联合放化疗可显著提高生存率,临床上对于N2~N3期患者也应给予密切关注,制定合理治疗策略。

     

    Abstract:
    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.

     

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