空洞性肺癌发生相关因素及无进展生存分析

Analysis of correlation factors for occurrence and progression-free survival of cavitating lung cancer in 947 cases

目的探讨空洞性肺癌发生的相关因素及其与无进展生存时间（PFS）的关系。方法收集947例肺癌患者的临床资料，其中治疗前有空洞51例，治疗后有空洞23例，无空洞873例。采用Logistic多因素分析方法分析空洞性肺癌发生的相关因素，采用Cox多因素分析方法分析影响患者PFS的独立因素，采用Kaplan-Meier法和Logrank检验进行生存分析。结果在全组肺癌患者中治疗前空洞的发生率为5．4％，治疗后空洞的发生率为2．6％。多因素Logistic回归分析显示，治疗前肺癌患者的年龄、糖尿病史、饮酒史、病理类型、肿瘤位置、肿瘤直径和远处转移与空洞的发生均有关（均P〈0．05）。多因素Logistic回归分析显示，治疗后肺癌患者的性别、病理类型和肿瘤直径与空洞的发生均有关（均P〈0．05）。治疗前有空洞的患者中位PFS（7．3个月）长于治疗前无空洞的患者（5．2个月），差异有统计学意义（P=0．002）。而治疗后有、无空洞患者的中位PFS（分别为5．1和5．3个月）差异无统计学意义（P=0．060）。Cox多因素分析结果显示，在治疗前有空洞的患者中，细胞角蛋白21—1片段水平与患者的PFS有关（P〈0．05）；在治疗后有空洞的患者中，吸烟史与患者的PFS有关（P〈0．05）。结论治疗前有空洞和治疗后有空洞的肺癌患者具有不同的临床病理特征和PFS。治疗前有空洞患者的PFS长于无空洞患者，治疗后有空洞患者的PFS短于无空洞患者。

Objective This study was designed to investigate the correlation factors for occurrence and progression-free survival of patients with cavitating lung cancer. Methods We collected the clinical data of 947 lung cancer patients. Tumor cavitation was observed in 51 patients at baseline and in 23 patients after treatment, while was not discovered in other 873 patients. Multifactor logistic regression was performed to analyze the correlation factors for occurrence. The independent predictors of PFS were analyzed with Cox proportional regression. Survival curves were constructed with the Kaplan-Meier product limit method and compared using the log-rank test. Results In the 947 cases, the proportion of cases with baseline cavitation was 5.4% and the incidence of cavitation after treatment was 2.6%. Multivariate logistic regression analysis revealed that the occurrence of baseline cavitation is related to age, history of diabetes, history of drinking, pathologic types, tumor location, tumor diameter and distant metastasis （ P 〈 0.05 ）. Multifaetor logistic regression analysis revealed that the occurrence of post-therapeutic cavitation is related to sex, pathologic types and tumor diameter （P〈0.05）.The median PFS of patients with baseline cavitation （7.3 months） was significantly longer than the cases without it （ 5.2 months ） （ P = 0.002）. While there was no significant difference between the median PFS of patients with post-therapeutic cavitation and patients without it （5.1 months vs. 5.3 months, P= 0.060 ）. Cox proportional regression analysis revealed that cyfra21-1 is related to PFS of patients with baseline cavitaion （ P〈0.05 ） and smoking history is related to PFS of patients with post- therapeutic eavitaion （P 〈 0. 05 ）. Conclusions Patients with baseline and post-therapeutic cavitation present different clinical features and progression-free survivals. The PFS of patients with baseline cavitation is longer than that of the cases without it. On the contrary, PFS of patients with post-therapeutic cavitation is shorter than the patients without it.