基于免疫评分构建肺腺癌患者的预后预测诺模图

Construction of a prognostic nomogram for lung adenocarcinoma patients based on immune scores

目的探讨免疫评分与预后的关系,并建立临床诺模图预测肺腺癌患者的生存。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库获取337例肺腺癌患者的临床病理特征和免疫评分,采用多因素COX比例风险回归模型分析肺腺癌患者总生存期的独立预测因素,根据多变量分析结果建立诺模图,采用一致性指数和校准曲线测定预测准确度和判别能力。结果根据免疫评分将患者分为3个亚组。与免疫评分低的患者相比,免疫评分高的患者总生存期显著改善(HR=0.56,95%CI:0.34~0.91,P=0.018);肿瘤TNM分期也是影响生存期的重要因素。预测总生存期的C指数为0.71(95%CI:0.665~0.755)。1年、3年和5年总生存期概率的校准曲线显示,诺模图预测值和实际观测值之间具有显著一致性。结论免疫评分高与肺腺癌患者更好的总生存期显著相关,肿瘤TNM分期显著影响患者的总生存期。此外,用于预测预后的诺模图可能有助于估计肺腺癌患者的生存期。

Objective To explore the relationship between immune scores and prognosis,and establish a clinical nomogram to predict the survival of patients with lung adenocarcinoma.Methods The clinicopathological features and immune scores of 337 patients with lung adenocarcinoma were obtained from The Cancer Genome Atlas(TCGA)database.Multivariate COX proportional hazards regression model was used to analyze the independent predictors of overall survival in patients with lung adenocarcinoma.Based on the results of the multivariate analysis,a nomogram was established.The consistency index(C-index)and calibration curve were used to measure the prediction accuracy and discrimination ability.Results The patients were divided into three subgroups according to the immune scores.Compared with patients with low immune scores,patients with high immune scores had significantly better overall survival(HR=0.56,95%CI:0.34-0.91,P=0.018).Additionally,the TNM stage of the tumor was also an important factor affecting survival.The C-index for predicting overall survival was 0.71(95%CI:0.665-0.755).Calibration curves for the probability of overall survival at 1,3,and 5 years demonstrated significant concordance between nomogram-predicted and observed values.Conclusion High immune score was significantly associated with better overall survival in patients with lung adenocarcinoma,and the TNM stage of the tumor also significantly influenced the overall survival.In addition,the nomogram developed for predicting prognosis may be helpful in estimating the survival of patient with lung adenocarcinoma.