Kamigaichi Atsushi, Tsutani Yasuhiro, Mimae Takahiro, Miyata Yoshihiro, Shimada Yoshihisa, Ito Hiroyuki, Nakayama Haruhiko, Ikeda Norihiko, Okada Morihito
Department of Surgical Oncology, Hiroshima University, Hiroshima, Japan.
Department of Surgery, Tokyo Medical University, Tokyo, Japan.
Clin Lung Cancer. 2021 Mar;22(2):120-126.e3. doi: 10.1016/j.cllc.2020.12.010. Epub 2020 Dec 27.
Despite the recent development of radiologic mediastinal staging modality, unexpected mediastinal lymph node metastasis still occurs. Preoperative accurate nodal staging is important to determine the optimal treatment. Therefore, this study aimed to identify predictors of unexpected N2 disease in non-small-cell lung cancer (NSCLC).
Data from a multicenter database of 2802 patients with clinical T1-2N0-1M0 NSCLC who underwent anatomical segmentectomy or lobectomy were retrospectively analyzed. Unexpected N2 disease was defined as pathologic N2 disease with clinical N0 or N1. The predictive criteria of unexpected N2 disease were established on the basis of the multivariable analysis results of a derivation cohort of 2019 patients, and the criteria were further tested in a validation cohort of 783 patients.
In multivariable analyses, maximum standardized uptake value (SUV) of the primary tumor on 18-fluoro-2-deoxyglucose positron emission tomography/computed tomography (odds ratio, 1.072; 95% confidence interval, 1.018-1.129; P = .008) and clinical N1 (vs. clinical N0) disease (odds ratio, 5.40; 95% confidence interval, 1.829-15.94; P = .002) were independent predictors of unexpected N2 disease. The predictive criteria of unexpected N2 disease was defined as tumors with SUV of ≥ 3.1, determined by receiver operating characteristic curves, and clinical N1 disease. This criterion showed diagnostic accuracy of 90.6% (sensitivity 32.0%, specificity 94.5%) in the derivation cohort and 91.3% (sensitivity 32.6%, specificity 94.7%) in the validation cohort.
The predictive criteria of unexpected N2 disease (tumors with SUV of ≥ 3.1 and clinical N1) can be used to select candidates for preoperative invasive mediastinal staging in patients with clinical T1-2N0-1M0 NSCLC.
尽管近年来放射学纵隔分期方法有所发展，但仍会出现意外的纵隔淋巴结转移。术前准确的淋巴结分期对于确定最佳治疗方案很重要。因此，本研究旨在确定非小细胞肺癌（NSCLC）中意外N2期疾病的预测因素。
回顾性分析了来自多中心数据库的2802例临床T1-2N0-1M0 NSCLC患者的数据，这些患者接受了解剖性肺段切除术或肺叶切除术。意外N2期疾病定义为临床N0或N1的病理N2期疾病。基于2019例患者的推导队列的多变量分析结果建立意外N2期疾病的预测标准，并在783例患者的验证队列中进一步检验该标准。
在多变量分析中，18-氟-2-脱氧葡萄糖正电子发射断层扫描/计算机断层扫描（18F-FDG PET/CT）上原发肿瘤的最大标准化摄取值（SUV）（比值比，1.072；95%置信区间，1.018-1.129；P = .008）和临床N1（与临床N0相比）疾病（比值比，5.40；95%置信区间，1.829-15.94；P = .002）是意外N2期疾病的独立预测因素。根据受试者工作特征曲线确定，意外N2期疾病的预测标准定义为SUV≥3.1的肿瘤和临床N1疾病。该标准在推导队列中的诊断准确率为90.6%（敏感性32.0%，特异性94.5%），在验证队列中的诊断准确率为91.3%（敏感性32.6%，特异性94.7%）。
意外N2期疾病的预测标准（SUV≥3.1的肿瘤和临床N1）可用于选择临床T1-2N0-1M0 NSCLC患者进行术前侵入性纵隔分期的候选者。
