列线图
医学
比例危险模型
阶段(地层学)
腺癌
病态的
肿瘤科
多元分析
内科学
多元统计
生存分析
放射科
癌症
统计
古生物学
生物
数学
作者
Wuhao Huang,Hua Zhang,Zhiwei Zhang,Bin Zhang,Xiaoyan Sun,Yansong Huo,Yingnan Feng,Pengfei Tian,Huilan Mo,Changli Wang
摘要
We aimed to develop a prognostic nomogram based on a new classification of combined micropapillary and solid components in pathological stage IA invasive lung adenocarcinoma (LUAD).According to the total proportion of solid and micropapillary components (TPSM), the X-tile software was applied to classify patients into the following three groups: TPSM-low (TPSM-L), TPSM-middle (TPSM-M), and TPSM-high (TPSM-H). The postoperative survival was compared among the three groups. The multivariate Cox regression analysis was performed to identify independent prognostic factors for survival. According to these factors, a nomogram model was developed to provide a personalized prognostic evaluation.A total of 595 patients with pathological stage IA invasive LUAD were included in our study. The 5-year disease-free survival and overall survival rates in patients with TPSM-H and TPSM-M were significantly lower than those with TPSM-L. The multivariate Cox regression analysis revealed that the TPSM classification was an independent prognostic factor for survival. According to TPSM classification, we developed a nomogram model which had good calibration and reliable discrimination ability to evaluate survival.The nomogram based on the combination of micropapillary and solid components has good prognostic value in predicting postoperative recurrence and survival of patients with pathological stage IA invasive LUAD.
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