Gu WeiGuo, Hu MingBin, Wang WeiJia, Shi Chao, Mei JinHong
Department of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People's Republic of China.
First Clinical Medical College, Nanchang University, Nanchang, Jiangxi, People's Republic of China.
Ther Clin Risk Manag. 2020 Dec 10;16:1213-1225. doi: 10.2147/TCRM.S272748. eCollection 2020.
Distant metastasis in early T1-2 (diameter≤5 cm) stage lung adenocarcinoma (ET-LUAD) patients largely affect treatment strategies in clinical practice. However, the associated mechanism remains unclear and related studies is less. This study aimed to establish and validate a novel nomogram to predict the risk of distant metastasis in ET-LUAD.
A total of 258 patients diagnosed with ET-LUAD and not receiving any treatment were recruited into this study. The patients were randomly divided into a training cohort and validation cohort in a ratio of 1:2. Univariate and multivariate logistic regression analysis was used to select the most significant predictive risk factors associated with distant metastasis in the training cohort. The established nomogram was validated by the consistency index (C-index), calibration curve, and decision curve analysis (DCA).
There were 124 patients with confirmed distant metastasis and 134 patients with non-distant metastases ET-LUAD were enrolled in the study. Multivariate logistic hazards regression analysis identified independent risk factors associated with distant metastasis to include platelet-to-lymphocyte ratios (PLR), lactate dehydrogenase (LDH), neural-specific enolase (NSE), carcinoembryonic antigen (CEA) and cytokeratin 19 fragments (Cyfra211), which were included in the establishment of the nomogram. The nomogram achieved a high consistency (C-index=0.792), good calibration, and high clinical application value in the validation cohort.
The established nomogram can be used to predict distant metastasis in high-risk ET-LUAD nonmetastasis patients and can also be used by doctors to guide preventive and individualized treatment for ET-LUAD patients.
早期T1-2（直径≤5 cm）期肺腺癌（ET-LUAD）患者的远处转移在很大程度上影响临床实践中的治疗策略。然而，其相关机制仍不清楚，相关研究较少。本研究旨在建立并验证一种预测ET-LUAD远处转移风险的新型列线图。
本研究共纳入258例诊断为ET-LUAD且未接受任何治疗的患者。患者按1:2的比例随机分为训练队列和验证队列。采用单因素和多因素逻辑回归分析在训练队列中选择与远处转移相关的最显著预测风险因素。通过一致性指数（C指数）、校准曲线和决策曲线分析（DCA）对建立的列线图进行验证。
本研究纳入了124例确诊有远处转移的患者和134例无远处转移的ET-LUAD患者。多因素逻辑风险回归分析确定与远处转移相关的独立风险因素包括血小板与淋巴细胞比值（PLR）、乳酸脱氢酶（LDH）、神经元特异性烯醇化酶（NSE）、癌胚抗原（CEA）和细胞角蛋白19片段（Cyfra211），这些因素被纳入列线图的建立。该列线图在验证队列中具有较高的一致性（C指数=0.792）、良好的校准和较高的临床应用价值。
建立的列线图可用于预测高危ET-LUAD无转移患者的远处转移，也可供医生用于指导ET-LUAD患者的预防性和个体化治疗。
