Zang Ruo-Chuan, Qiu Bin, Gao Shu-Geng, He Jie
Department of Thoracic Surgery, Peking Union Medical College, Cancer Hospital and Chinese Academy of Medical Sciences, Beijing 100021, China.
Chin Med J (Engl). 2017 Feb 20;130(4):398-403. doi: 10.4103/0366-6999.199838.
Lymph node status of patients with early-stage nonsmall cell lung cancer has an influence on the choice of surgery. To assess the lymph node status more correspondingly and accurately, we evaluated the relationship between the preoperative clinical variables and lymph node status and developed one model for predicting lymph node involvement.
We collected clinical and dissected lymph node information of 474 patients with clinical stage T1aN0-2M0 nonsmall cell lung cancer (NSCLC). Logistic regression analysis of clinical characteristics was used to estimate independent predictors of lymph node metastasis. The prediction model was validated by another group.
Eighty-two patients were diagnosed with positive lymph nodes (17.3%), and four independent predictors of lymph node disease were identified: larger consolidation size (odds ratio [OR] = 2.356, 95% confidence interval [CI]: 1.517-3.658, P < 0.001,), central tumor location (OR = 2.810, 95% CI: 1.545-5.109, P = 0.001), abnormal status of tumor marker (OR = 3.190, 95% CI: 1.797-5.661, P < 0.001), and clinical N1-N2 stage (OR = 6.518, 95% CI: 3.242-11.697, P < 0.001). The model showed good calibration (Hosmer-Lemeshow goodness-of-fit, P < 0.766) with an area under the receiver operating characteristics curve (AUC) of 0.842 (95% [CI]: 0.797-0.886). For the validation group, the AUC was 0.810 (95% CI: 0.731-0.889).
The model can assess the lymph node status of patients with clinical stage T1aN0-2M0 NSCLC, enable surgeons perform an individualized prediction preoperatively, and assist the clinical decision-making procedure.
早期非小细胞肺癌患者的淋巴结状态对手术方式的选择有影响。为了更准确地评估淋巴结状态，我们评估了术前临床变量与淋巴结状态之间的关系，并建立了一个预测淋巴结受累的模型。
我们收集了474例临床分期为T1aN0 - 2M0的非小细胞肺癌（NSCLC）患者的临床及解剖淋巴结信息。采用临床特征的逻辑回归分析来估计淋巴结转移的独立预测因素。该预测模型由另一组进行验证。
82例患者被诊断为淋巴结阳性（17.3%），确定了四个淋巴结疾病的独立预测因素：实变区更大（比值比[OR]=2.356，95%置信区间[CI]：1.517 - 3.658，P<0.001）、肿瘤位于中央（OR = 2.810，95% CI：1.545 - 5.109，P = 0.001）、肿瘤标志物异常（OR = 3.190，95% CI：1.797 - 5.661，P<0.001）以及临床N1 - N2期（OR = 6.518，95% CI：3.242 - 11.697，P<0.001）。该模型显示出良好的校准度（Hosmer - Lemeshow拟合优度，P<0.766），受试者工作特征曲线（AUC）下面积为0.842（95%[CI]：0.797 - 0.886）。对于验证组，AUC为0.810（95% CI：0.731 - 0.889）。
该模型可以评估临床分期为T1aN0 - 2M0的NSCLC患者的淋巴结状态，使外科医生能够在术前进行个体化预测，并辅助临床决策过程。
