Zhao Fei, Zhou Yue, Ge Peng-Fei, Huang Chen-Jun, Yu Yue, Li Jun, Sun Yun-Gang, Meng Yang-Chun, Xu Jian-Xia, Jiang Ting, Zhang Zhi-Xuan, Sun Jin-Peng, Wang Wei
Department of Thoracic Surgery, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
BMC Cancer. 2017 Apr 13;17(1):267. doi: 10.1186/s12885-017-3273-x.
There is little information on which pattern should be chosen to perform lymph node dissection for stage I non-small-cell lung cancer. This study aimed to develop a model for predicting lymph node metastasis using pathologic features of patients intraoperatively diagnosed as stage I non-small-cell lung cancer.
We collected pathology data from 284 patients intraoperatively diagnosed as stage I non-small-cell lung cancer who underwent lobectomy with complete lymph node dissection from 2013 through 2014, assessing various factors for an association with metastasis to lymph nodes (age, gender, pathology, tumour location, tumour differentiation, tumour size, pleural invasion, bronchus invasion, multicentric invasion and angiolymphatic invasion). After analysing these variables, we developed a multivariable logistic model to estimate risk of metastasis to lymph nodes.
Univariate logistic regression identified tumour size >2.65 cm (p < 0.001), tumour differentiation (p < 0.001), pleural invasion (p = 0.034) and bronchus invasion (p < 0.001) to be risk factors significantly associated with the presence of metastatic lymph nodes. On multivariable analysis, only tumour size >2.65 cm (p < 0.001), tumour differentiation (p = 0.006) and bronchus invasion (p = 0.017) were independent predictors for lymph node metastasis. We developed a model based on these three pathologic factors that determined that the risk of metastasis ranged from 3% to 44% for patients intraoperatively diagnosed as stage I non-small-cell lung cancer. By applying the model, we found that the values ŷ > 0.80, 0.43 < ŷ ≤ 0.80, ŷ ≤ 0.43 plus tumour size >2 cm and ŷ ≤0.43 plus tumour size ≤2 cm yielded positive lymph node metastasis predictive values of 44%, 18%, 14% and 0%, respectively.
A non-invasive prediction model including tumour size, tumour differentiation and bronchus invasion may be useful to give thoracic surgeons recommendations on lymph node dissection for patients intraoperatively diagnosed as Stage I non-small cell lung cancer.
对于I期非小细胞肺癌应选择何种模式进行淋巴结清扫，相关信息较少。本研究旨在利用术中诊断为I期非小细胞肺癌患者的病理特征，建立一个预测淋巴结转移的模型。
我们收集了2013年至2014年期间284例术中诊断为I期非小细胞肺癌并接受肺叶切除及完整淋巴结清扫患者的病理数据，评估与淋巴结转移相关的各种因素（年龄、性别、病理、肿瘤位置、肿瘤分化、肿瘤大小、胸膜侵犯、支气管侵犯、多中心侵犯和血管淋巴管侵犯）。分析这些变量后，我们建立了一个多变量逻辑模型来估计淋巴结转移风险。
单变量逻辑回归确定肿瘤大小>2.65 cm（p<0.001）、肿瘤分化（p<0.001）、胸膜侵犯（p=0.034）和支气管侵犯（p<0.001）是与转移性淋巴结存在显著相关的危险因素。多变量分析显示，只有肿瘤大小>2.65 cm（p<0.001）、肿瘤分化（p=0.006）和支气管侵犯（p=0.017）是淋巴结转移的独立预测因素。我们基于这三个病理因素建立了一个模型，该模型确定术中诊断为I期非小细胞肺癌患者的转移风险范围为3%至44%。通过应用该模型，我们发现ŷ>0.80、0.43<ŷ≤0.80、ŷ≤0.43加肿瘤大小>2 cm和ŷ≤0.43加肿瘤大小≤2 cm时，阳性淋巴结转移预测值分别为44%、18%、14%和0%。
一个包括肿瘤大小、肿瘤分化和支气管侵犯的非侵入性预测模型，可能有助于为胸外科医生对术中诊断为I期非小细胞肺癌的患者进行淋巴结清扫提供建议。
