摘要
目的分析老年肺腺癌患者的临床特征并构建能够用于预测肺腺癌患者生存情况的预测模型。方法回顾性分析在SEER数据库收集的年龄60岁及以上,在2013年至2018年期间被诊断为肺腺癌的患者临床数据。采用Cox回归分析影响老年肺腺癌患者预后的独立因素,并构建列线图模型。通过C指数和校准曲线对列线图的判别和校准能力进行评估。根据预测模型计算每例患者的总风险得分,并按照总风险得分的四分位数对患者进行分层。采用Kaplan-Meier法和Log rank检验对各风险组的生存差异进行评价。结果38852例肺腺癌患者中男性17200例,女性21652例。不同年龄、性别、婚姻状况、组织学分级、TNM分期、肿瘤大小、骨转移、脑转移、肝转移、是否接受手术治疗、是否接受放疗、是否接受化疗的肺腺癌患者的生存率有显著差异(均P<0.001)。建模组的C指数为0.815(95%CI:0.811~0.819),验证组的C指数为0.810(95%CI:0.804~0.816)。预测模型在建模数据集中预测1年、3年和5年生存率的曲线下面积较高,分别为0.746、0.768和0.775,在验证数据集中分别为0.747、0.770和0.777。以此模型构建的风险分层模型能够很好地区分不同风险的患者(P<0.001)。结论年龄、性别、婚姻状况、组织学分级、TNM分期、肿瘤大小、骨转移、脑转移、肝转移、手术治疗、放疗、化疗是老年肺腺癌患者生存预后的独立影响因素。本研究构建的风险预测模型可筛选不同生存风险的患者,对预测老年肺腺癌患者的治疗响应,实现精准医疗具有重要的意义。
Objective This study aims to analyze the clinical characteristics of elderly patients with lung adenocarcinoma and to construct a predictive model for assessing their survival.Methods We conducted a retrospective analysis of clinical data sourced from the SEER database for patients aged 60 years or older who were diagnosed with lung adenocarcinoma between 2013 and 2018.Cox regression analysis was employed to identify independent prognostic factors affecting the survival of elderly lung adenocarcinoma patients,leading to the development of a nomogram model.The discriminative ability and calibration of the nomogram were assessed using the C-index and calibration curve.Each patient's total risk score was calculated based on the predictive model,and patients were stratified according to the quartiles of their total risk scores.The Kaplan-Meier method and Log-rank test were utilized to evaluate survival differences among the identified risk groups.Results Among 38,852 lung adenocarcinoma patients,17,200 were males and 21,652 were females.Significant differences in survival rates were observed among lung adenocarcinoma patients based on age,gender,marital status,histological grade,TNM stage,tumor size,and the presence of bone,brain,or liver metastases,as well as the type of treatment received,including surgical treatment,radiation therapy,and chemotherapy(all P<0.001).The C-index of the training model was 0.815(95%CI:0.811-0.819),while the validation model yielded a C-index of 0.810(95%CI:0.804-0.816).The prediction model demonstrated higher Area Under Curve(AUC)values of 0.746,0.768,and 0.775 for 1-year,3-year,and 5-year survival in the modeling dataset,respectively,and 0.747,0.770,and 0.777 in the validation dataset.Furthermore,the risk stratification model effectively distinguished patients at varying levels of risk(P<0.001).Conclusions Age,gender,marital status,histological grade,TNM stage,tumor size,and the presence of bone,brain,and liver metastases,along with treatment modalities such as surgery,radiotherapy,and
作者
赵爽
杨晗
赵海娟
苗苗
王情情
王雅茹
殷钰莹
姚慧卿
刘飞
王欣
Zhao Shuang;Yang Han;Zhao Haijuan;Miao Miao;Wang Qingqing;Wang Yaru;Yin Yuying;Yao Huiqing;Liu fei;Wang Xin(Clinical Trial Research Center,Beijing Hospital,National Center of Gerontology,Institute of Geriatric Medicine,Chinese Academ y of Medical Sciences,Beijing 100730,China)
出处
《中华老年医学杂志》
CAS
CSCD
北大核心
2024年第11期1402-1408,共7页
Chinese Journal of Geriatrics
基金
中央高水平医院临床科研业务费(BJ-2023-208)
首都卫生科研发展专项(2022-2Z-4055)。
关键词
肺肿瘤
腺癌
列线图
预后
Lung neoplasms
Adenocarcinoma
Nomograms
Prognosis
