Shao Jun, Wang Chengdi, Li Jingwei, Song Lujia, Li Linhui, Tian Panwen, Li Weimin
Department of Respiratory and Critical Care Medicine, West China Medical School/West China Hospital, Sichuan University, Chengdu, China.
West China School of Public Health, Sichuan University, Chengdu, China.
Ann Transl Med. 2020 Sep;8(18):1137. doi: 10.21037/atm-20-5505.
Diagnosis of multiple lung nodules has become convenient and frequent due to the improvement of computed tomography (CT) scans. However, to distinguish intrapulmonary metastasis (IPM) from multiple primary lung cancer (MPLC) remains challenging. Herein, for the accurate optimization of therapeutic options, we propose a comprehensive algorithm for multiple lung carcinomas based on a multidisciplinary approach, and investigate the prognosis of patients who underwent surgical resection.
Patients with multiple lung carcinomas who were treated at West China Hospital of Sichuan University from April, 2009 to December, 2017, were retrospectively identified. A comprehensive algorithm combining histologic assessment, molecular analysis, and imaging information was used to classify nodules as IPM or MPLC. The Kaplan-Meier method was used to estimate survival rates, and the relevant factors were evaluated using the log-rank test or Cox proportional hazards model.
The study included 576 patients with 1,295 lung tumors in total. Significant differences were observed between the clinical features of 171 patients with IPM and 405 patients with MPLC. The final classification consistency was 0.65 and 0.72 compared with the criteria of Martini and Melamed (MM) and the American College of Chest Physicians (ACCP), respectively. Patients with independent primary tumors had better overall survival (OS) than patients with intra-pulmonary metastasis (HR =3.99, 95% CI: 2.86-5.57; P<0.001). Nodal involvement and radiotherapy were independent prognostic factors.
The comprehensive algorithm was a relevant tool for classifying multifocal lung tumors as MPLC or IPM, and could help doctors with precise decision-making in routine clinical practice. Patients with multiple lesions without lymph node metastasis or without radiotherapy tended to have a better prognosis.
由于计算机断层扫描（CT）技术的进步，多发性肺结节的诊断变得更加便捷和常见。然而，区分肺内转移（IPM）和多发性原发性肺癌（MPLC）仍然具有挑战性。在此，为了准确优化治疗方案，我们提出了一种基于多学科方法的多发性肺癌综合算法，并对接受手术切除的患者的预后进行了研究。
回顾性纳入2009年4月至2017年12月在四川大学华西医院接受治疗的多发性肺癌患者。采用组织学评估、分子分析和影像信息相结合的综合算法，将结节分类为IPM或MPLC。采用Kaplan-Meier法估计生存率，并使用对数秩检验或Cox比例风险模型评估相关因素。
该研究共纳入576例患者，总计1295个肺肿瘤。171例IPM患者和405例MPLC患者的临床特征存在显著差异。与Martini和Melamed（MM）标准及美国胸科医师学会（ACCP）标准相比，最终分类一致性分别为0.65和0.72。独立原发性肿瘤患者的总生存期（OS）优于肺内转移患者（HR =3.99，95%CI：2.86-5.57；P<0.001）。淋巴结受累和放疗是独立的预后因素。
综合算法是将多灶性肺肿瘤分类为MPLC或IPM的相关工具，有助于医生在日常临床实践中做出精确决策。无淋巴结转移或未接受放疗的多发病灶患者预后往往较好。
