宫颈癌TNM分期与预后相关性分析

Correlation Analysis between TNM Staging and Prognosis of Cervical Cancer

摘要: 目的：基于SEER数据库的宫颈癌患者影响因素分析，分析影响宫颈癌预后的相关因素，为宫颈癌患者预后恢复及治疗提供科学参考依据。方法：利用SEER数据库初步筛查宫颈癌相关数据，从中下载所有符合研究的宫颈癌患者的不同病理分型的数据，选用第八期T，N，M分期对数据的T，N，M分期进行整理，标准化，筛选，筛选条件为患者第八期T，N，M分期明确，有符合要求的观察结局，如死亡或存活。通过筛查出的患者的不同病理分型的数据，运用SPSS26.0统计软件进行统计描述，采用Kaplan-Meier法。描绘生存曲线并估计患者的生存率，死亡率。生存时间分布的组间比较采用Log-Rank检验，对分析结果中P < 0.05有统计学意义的变量进行多因素COX分析，所有统计检验均为双侧检验，取α = 0.05，以P < 0.05认为具有统计学差异。结果：(1) Kaplan-Meier单因素分析：T分期、N分期、M分期的不同病理分期对患者的生存期有影响，具有统计学意义(P < 0.05)，能不同程度地影响患者的生存期。(2) COX多因素分析：T分期、N分期、M分期是影响患者生存期的独立预后因素。结论：不同宫颈癌患者不同的T，N，M病理分期能不同程度地影响宫颈癌患者的预后，它们对于宫颈癌患者的死亡率，存活率有着明显的影响，能为宫颈癌的治疗方案的发展和完善提供相关的依据。

Abstract: Objective: Study on the prognostic risk model of cervical cancer patients based on SEER database, analyze the relevant factors affecting the prognosis of cervical cancer, and provide scientific reference for the prognosis recovery and treatment of cervical cancer patients. Methods: The SEER database was used to preliminarily screen the data related to cervical cancer, download the data of different pathological types of cervical cancer patients in line with the study, and select the eighth stage T, N, M to sort out, standardize and screen the T, N and M stages of the data. The screening conditions were that the eighth stage T, N and M stages of patients were clear, and there were satisfactory observed outcomes, such as death or survival. Through the data of different pathological types of patients screened, spss26 0 statistical software for statistical description, using Kaplan Meier method. Draw the survival curve and estimate the survival rate and mortality of patients. The inter group comparison of survival time distribution adopts log rank test to conduct multi factor Cox analysis on the variables with statistical significance of P < 0.05 in the analysis results. According to the results of multi factor analysis, establish a risk assessment model, evaluate the established model, calculate its accuracy, sensitivity, specificity and evaluate the effectiveness of the model. All statistical tests are bilateral tests, taking α = 0.05, P < 0.05. Result: (1) Kaplan Meier univariate analysis: different pathological stages of T stage, N stage and M stage have an impact on the survival of patients, which is statistically significant (P < 0.05), and can affect the survival of patients to varying degrees. (2) Cox multivariate analysis: T stage, N stage and M stage were independent prognostic factors affecting the survival time of patients. Conclusion: Different T, N and M pathological stages of different cervical cancer patients can affect the prognosis of cervical cancer patients to varying degrees. They have a significant impact on the mortality and survival rate of cervical cancer patients, and can provide relevant basis for the development and improvement of the treatment scheme of cervical cancer.