盲肠癌患者预后的竞争风险分析：基于人群的研究。
Competitive Risk Analysis of Prognosis in Patients With Cecum Cancer: A Population-Based Study.
机构信息
Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
出版信息
Cancer Control. 2021 Jan-Dec;28:1073274821989316. doi: 10.1177/1073274821989316.
BACKGROUND
The presence of competing risks means that the results obtained using the classic Cox proportional-hazards model for the factors affecting the prognosis of patients diagnosed with cecum cancer (CC) may be biased.
OBJECTIVE
The purpose of this study was to establish a competitive risk model for patients diagnosed with CC to evaluate the relevant factors affecting the prognosis of patients, and to compare the results with the classical COX proportional risk model.
METHODS
We extracted data on patients diagnosed with CC registered between 2004 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database. The univariate analysis utilized the cumulative incidence function and Gray's test, while a multivariate analysis was performed using the Fine-Gray, cause-specific (CS), and Cox proportional-hazards models.
RESULTS
The 54463 eligible patients diagnosed with CC included 24387 who died: 12087 from CC and 12300 from other causes. The multivariate Fine-Gray analysis indicated that significant factors affecting the prognosis of patients diagnosed with CC include: age, race, AJCC stage, differentiation grade, tumor size, surgery, radiotherapy, chemotherapy and regional lymph nodes metastasis. Due to the presence of competitive risk events, COX model results could not provide accurate estimates of effects and false-negative results occurred. In addition, COX model misestimated the direction of association between regional lymph node metastasis and cumulative risk of death in patients diagnosed with CC. Competitive risk models tend to be more advantageous when analyzing clinical survival data with multiple endpoints.
CONCLUSIONS
The present study can help clinicians to make better clinical decisions and provide patients diagnosed with CC with better support.
背景
竞争风险的存在意味着，使用经典的 Cox 比例风险模型来分析影响盲肠癌（CC）患者预后的因素所得到的结果可能存在偏差。
目的
本研究旨在建立一个用于评估影响 CC 患者预后的相关因素的竞争风险模型，并与经典 COX 比例风险模型的结果进行比较。
方法
我们从监测、流行病学和最终结果（SEER）数据库中提取了 2004 年至 2016 年期间确诊的 CC 患者的数据。采用累积发生率函数和 Gray 检验进行单因素分析，采用 Fine-Gray、原因特异性（CS）和 Cox 比例风险模型进行多因素分析。
结果
符合条件的 54463 例 CC 患者中，有 24387 例死亡：12087 例死于 CC，12300 例死于其他原因。多因素 Fine-Gray 分析表明，影响 CC 患者预后的显著因素包括：年龄、种族、AJCC 分期、分化程度、肿瘤大小、手术、放疗、化疗和区域淋巴结转移。由于存在竞争风险事件，COX 模型的结果无法提供对效应的准确估计，并且出现了假阴性结果。此外，COX 模型错误地估计了区域淋巴结转移与 CC 患者死亡累积风险之间的关联方向。竞争风险模型在分析具有多个终点的临床生存数据时往往更具优势。
结论
本研究可以帮助临床医生做出更好的临床决策，并为 CC 患者提供更好的支持。
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