目的 探讨淋巴结阳性率(LNR)对预测非小细胞肺癌(NSCLC)患者预后的临床价值。方法回顾性分析301例行完全性切除术的N1、N2期NSCLC患者的临床资料。其中,男198例,女103例;年龄31—78岁,中位年龄59岁。分析临床病理特征与LNR的相关性,单因素Kaplan—Meier生存分析和多因素Cox比例风险回归分析LNR对术后生存时间的影响;结合现有N分期对有淋巴结转移的患者进行预后危险组别的划分。结果高LNR组与低LNR组在年龄、吸烟状况、病理类型、临床分期、N分期、隆突下淋巴结是否转移和淋巴结阳性个数、清扫个数及阳性淋巴结站数存在明显差异(P〈0.05);LNR是独立预后因素,LNR的高低明显影响总生存期(OS)和无病生存期(DFS)(P〈0.001),LNR越高,死亡(HR=2.507,P〈0.001)和复发转移(HR=1.872,P=0.008)的风险性越大;在同一N分期中,LNR高、低亚组间比较OS与DFS差异亦有统计学意义。随危险组别的增高,5年总生存率(32.8%、20.7%、6.9%)及中位生存时间(MST)(57、30、16个月)、5年无病生存率(28.1%、16.3%、5.5%)及中位无病生存时间(DMST)(38、19、10个月)均逐渐降低(均P〈0.001)。结论LNR能更准确判断NSCLC预后、指导术后治疗,有助于完善NSCLC的TNM分期体系。
Objective To investigate the relationship between the metastatic lymph node ratio (LNR) and the prognosis of non-small cell lung cancer (NSCLC). Methods A total of 301 patients with NI and N2 NSCLC undergoing curative pulmonectomy were analyzed retrospectively. There were 103 females and 198 males with a median age of 59 years (range: 31 -78). The correlations between LNR and clinicopathological data were analyzed by x2 test. The effects of LNR on overall survival (OS) and disease free survival (DFS) of patients were analyzed by the methods of univariate Kaplan-Meier and muhivatiate Cox proportional hazard model. The risk groups were classified by LNR on the basis of N staging. Results LNR correlated with age, smoking status, pathological type, clinical stage and N stage ( P 〈 0. 05 ). And it also correlated with positive lymph nodes, resected lymph nodes and the number of positive lymph node station (P 〈0. 001 ). Kaplan-Meier survival analysis revealed that LNR influenced significantly the lengths of OS (P 〈 0. 001 ) and DFS (P 〈 0. 001 ). Cox proportional hazard model showed a high LNR was an independent poor prognostic factor for OS ( HR = 2. 507, 95% CI 1. 612 - 3. 900, P 〈 0. 001 ) and DFS (HR = 1. 872, 95% CI 1. 182 - 2. 964, P = 0. 008) ; and at the same N stage, the low-LNR group was better in OS and DFS than the high-LNR group. After stratification into high-, medium- and low-risk groups, the high-(LNR: 〉18%, N-status: N2), intermediate-(LNR: 〉18%, N-status: N1; LNR: 〈18%, N- status: N2) and low-risk factors (LNR: 〈 18%, N-status: N1 ) could efficiently predict the outcomes. The 5-year survival rate (32. 8% vs 20. 7% vs 6. 9% ), median survival time (MST) (57 vs 30 vs 16 months), 5-year disease-free survival rate (28. 1% vs 16. 3% vs 5.5% ) and disease-free survival time (38 vs 19 vs 10 months) decreased progressively with the rising risk groups ( P 〈 0. 001 ). Conclusion LNR may be used