Department of Thoracic Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, Zhejiang Province, China.
Department of surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 east qing chun road, Hangzhou, 310016, Zhejiang Province, China.
J Cardiothorac Surg. 2021 Jan 19;16(1):13. doi: 10.1186/s13019-020-01390-x.
Lymph node ratio (LNR) has been suggested to be an effective prognostic tool for stratifying non-small cell lung cancer (NSCLC) cases. In this study, we sought to determine cancer-specific survival (CCS) of NSCLC cases from the SEER registry and used the X-tile method to optimize CCS-based LNR cut-off points for prognostic stratification of node-positive NSCLC.
CSS and other clinicopathologic variables were retrieved from the SEER registry. Kaplan-Meier methods were used to calculate CSS. The optimal cut-off points for LNR classification were determined by the X-tile approach. Multivariate Cox regression analysis was performed to identify independent risks of CSS.
Totally 11,341 lung cancer patients were included. Their median CSS was 22 months (range 0,143). The median LNR was 0.22 (Q1,Q3: 0.11, 0.50). X-tile analysis showed that the optimal LNR cut-off points were 0.28 and 0.81, dividing the cohort into low (LNR1 ≤ 0.28; n = 6580, 58%), middle (0.28 < LNR2 < 0.81; n = 3025, 26.7%), and high (LNR3 > 0.81; n = 1736, 15.3%) subsets. Kaplan-Meier analysis showed that patients with a low LNR had a significantly higher CCS versus patients with middle or high LNR (P < 0.001). Multivariate competing risks regression analysis revealed that LNR was an independent and significant adverse predictor of CSS (LNR2 vs. LNR1: SHR: 1.56, 95%CI: 1.47,1.67, P < 0.001; LNR3 vs. LNR1: SHR: 2.54, 95%CI: 2.30,2.80, P < 0.001).
LNR is an independent prognostic factor of node-positive NSCLC and its optimal cut-off values established using the robust x-tile method effectively define subpopulations of node-positive NSCLC cases, which is important in guiding selection of treatment strategies clinically.
淋巴结比率（LNR）已被证明是一种有效的非小细胞肺癌（NSCLC）分层预后工具。本研究旨在通过 SEER 数据库确定 NSCLC 患者的癌症特异性生存率（CSS），并使用 X-tile 方法确定基于 CSS 的 LNR 截断点，以对淋巴结阳性 NSCLC 进行预后分层。
从 SEER 数据库中检索 CSS 和其他临床病理变量。Kaplan-Meier 方法用于计算 CSS。通过 X-tile 方法确定 LNR 分类的最佳截断点。多因素 Cox 回归分析用于确定 CSS 的独立风险因素。
共纳入 11341 例肺癌患者。中位 CSS 为 22 个月（范围 0，143）。中位 LNR 为 0.22（Q1，Q3：0.11，0.50）。X-tile 分析显示，最佳 LNR 截断点为 0.28 和 0.81，将队列分为低（LNR1≤0.28；n=6580，58%）、中（0.28<LNR2<0.81；n=3025，26.7%）和高（LNR3>0.81；n=1736，15.3%）亚组。Kaplan-Meier 分析显示，低 LNR 患者的 CSS 明显高于中或高 LNR 患者（P<0.001）。多因素竞争风险回归分析显示，LNR 是 CSS 的独立且显著的不良预测因子（LNR2 与 LNR1：SHR：1.56，95%CI：1.47，1.67，P<0.001；LNR3 与 LNR1：SHR：2.54，95%CI：2.30，2.80，P<0.001）。
LNR 是淋巴结阳性 NSCLC 的独立预后因素，使用稳健的 X-tile 方法确定的最佳截断值可有效定义淋巴结阳性 NSCLC 病例的亚群，这对指导临床治疗策略的选择具有重要意义。
