Development of a Prognostic Nomogram for Patients with Lung Adenocarcinoma in the Stages I, II, and III Based on Immune Scores

基于免疫评分的I、II、III期肺腺癌患者预后列线图的构建

阅读:1

Abstract

BACKGROUND: Immunotherapy has significantly changed the treatment prospects of non-small cell lung cancer (NSCLC). However, there is no report based on immune score to predict the overall survival (OS) of lung adenocarcinoma (LUAD) in the stages I, II, and III. Therefore, this study aimed to investigate the immune score and the prognosis-related factors of LUAD and construct a nomogram to predict the prognosis. METHODS: A total of 390 cases with lung adenocarcinoma in the stages I, II, and III were included in the study. The clinicopathological characteristics and immune scores of LUAD patients were downloaded from the TCGA database. Cox proportional hazards regression model was used to estimate hazard ratio (HR) and 95% confidence interval (CI). A Nomogram was composed of the Cox model and internally validated using 1000 bootstrap. The concordance index (c-index) and the calibration curves were used to evaluate the model. The decision curve analysis (DCA) was performed to evaluate the clinical practical value of the model. RESULTS: According to the immune score, the patients were divided into low-, medium-, and high-score groups. This study showed that compared with patients with low and medium immune scores, only patients with high immune scores had significantly improved OS (HR and 95% confidence interval (CI): 0.489 [0.324-0.737]). The C-index for OS prediction was 0.691 (95% CI, 0.646-0.736). The calibration curves for nomogram-predicted probabilities of 3- and 5-year survival have good ability for the calibration and discrimination. CONCLUSION: The high immune score was significantly correlated with better OS of patients with LUAD in the stages I, II, and III. Moreover, the nomogram of predicting prognosis may help assess the survival of LUAD patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。