Construction and validation of a risk model for cancer-related fatigue in non-small cell lung cancer patients undergoing chemotherapy based on Nomogram model
10.3760/cma.j.cn115682-20220523-02457
- VernacularTitle:基于Nomogram模型的非小细胞肺癌化疗患者癌因性疲乏风险模型的构建与验证
- Author:
Aihua CONG
1
;
Ying XU
;
Yuping SHANG
Author Information
1. 南京医科大学附属泰州人民医院肿瘤科，泰州 225300
- Keywords:
Carcinoma, non-small-cell lung;
Cancer-related fatigue;
Risk factors;
Risk nomogram model
- From:
Chinese Journal of Modern Nursing
2023;29(10):1352-1360
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a risk nomogram model for cancer-related fatigue in non-small cell lung cancer patients undergoing chemotherapy, and to verify the application value of the model.Methods:From from January 2017 to December 2021, 520 non-small cell lung cancer patients undergoing chemotherapy admitted to Taizhou People's Hospital and the Second People's Hospital of Lianyungang were selected as the research objects using the convenient sampling method, 400 patients admitted from January 2017 to February 2020 were selected as the model group, and 120 patients admitted from April 2020 to December 2021 were selected as the verification group. Lasso analysis and Logistic regression analysis were used to explore the risk factors of cancer-related fatigue in non-small cell lung cancer patients undergoing chemotherapy. R 4.1.2 software was used to establish a risk nomogram model to predict the risk of cancer-related fatigue in non-small cell lung cancer patients undergoing chemotherapy, and to verify the application value of the model.Results:The incidence of cancer-related fatigue in the model group was 65.5% (262/400) . Logistic regression analysis showed that age≥60 years old, female, living alone, TNM stage (Ⅲ-Ⅳ stage) , poor sleep, depression, frequency of chemotherapy>2 times and percentage of forced expiratory volume in one second to the predicted value (FEV 1%) <70% were the risk factors of cancer-related fatigue in non-small cell lung cancer patients undergoing chemotherapy. The results of risk nomogram model showed that consistency index of the model group and the verification group were 0.846 (95% CI: 0.810-0.889) , 0.887 (95% CI: 0.857-0.917) respectively. The calibration curve showed that the actual and predict values of the model group and the validation group had a good fitting degree. The areas under receiver operating characteristic curve of the model group and the validation group were 0.845 and 0.866, respectively. The decision curve showed that the predictive graph of cancer-induced fatigue in non-small cell lung cancer patients undergoing chemotherapy had good clinical efficacy. Conclusions:Age≥60 years old, female, living alone, TNM stage (Ⅲ-Ⅳ) , poor sleep, depression, frequency of chemotherapy>2 times and FEV 1%<70% are the risk factors of cancer-related fatigue in non-small cell lung cancer patients undergoing chemotherapy, the risk nomogram model established based on the above risk factors is helpful to developing the screening and prevention measures of patients at high-risk of cancer-related fatigue.
