解放军医学杂志2024，Vol.49Issue(9)：1004-1010,7.DOI:10.11855/j.issn.0577-7402.1574.2024.0327
高能量代谢肺癌患者临床特征分析及其预测模型建立
Clinical characterization and prediction modeling of lung cancer patients with high energy metabolism
摘要
Abstract
Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.关键词
肺癌/高能量代谢/预测模型/人体成分/生活质量Key words
lung cancer/high energy metabolism/risk prediction model/body composition/quality of life分类
医药卫生引用本文复制引用
任江珊,王康,仇海乐,刘宸安,樊羽羽,于德刚,贾军梅,孙萍,平梅,张琼琼,刘燕燕,赵和平,陈妍,戎冬文..高能量代谢肺癌患者临床特征分析及其预测模型建立[J].解放军医学杂志,2024,49(9):1004-1010,7.基金项目
This work was supported by the Clinical Research Special Program of Wu Jieping Medical Foundation(320.6750.2022-17-27) 吴阶平医学基金会临床科研专项资助基金(320.6750.2022-17-27) （320.6750.2022-17-27）
