A predictive nomogram for lymph node metastasis in part-solid invasive lung adenocarcinoma: A complement to the IASLC novel grading system - Gao, Zhaoming; Wang, Xiaofei; Zuo, Tao; Zhang, Mengzhe; Zhang, Zhenfa (Frontiers in Oncology, 2022)
Background: IASLC proposed a novel grading system for invasive lung adenocarcinoma, but lymphatic invasion was not evaluated. Meanwhile, the scope of lymph node dissection in part-solid invasive lung adenocarcinoma (PSILA) is still controversial. Therefore, this study aims to explore preoperative risk factors for lymph node metastasis in PSILA, to provide reference for intraoperative dissection of lymph nodes. Methods: From 2018 to 2020, clinical data of patients (stage cN0) consecutively diagnosed as PSILA were retrospectively analyzed and classified according to the novel grading system. Logistic regression was conducted to screen the clinicopathological factors of lymph node metastasis in PSILA. Results: A large cohort of 960 patients with PSILA who underwent lobectomy or sub-lobectomy was enrolled. By Logistic regression analyses, solid part size, bronchial cut-off sign, spiculation and CA199 were eventually identified as independent risk factors for lymph node metastasis, based on which a nomogram was built to preoperatively predict the risk of lymph node metastasis (AUC=0.858; Concordance index = 0.857; Best cut-off: 0.027). This suggests that intraoperative systematic lymph node dissection is recommended when the predicted risk value exceeds 0.027. Reproducibility of the novel grading system were verified. Conclusions: The novel IASLC grading system was applicative in real world. The nomogram for preoperative prediction of lymph node metastasis may provide reference for the lymph node dissection strategy during PSILA surgeries.