Construction and Validation of A Nutritional Risk Prediction Model for Gastric Cancer Inpatients
10.3969/j.issn.1008-7125.2025.01.007
- VernacularTitle:胃癌住院患者营养风险预测模型的构建和验证
- Author:
Kehua WANG
1
;
Pingping SONG
1
;
Ling ZHANG
1
;
Lili ZHANG
1
;
Na WANG
1
Author Information
1. 秦皇岛市第一医院药学部(066000)
- Publication Type:Journal Article
- Keywords:
Stomach Neoplasms;
Nutritional Risk Prediction Models;
Nutritional Risk Screening 2002;
Risk Factors
- From:
Chinese Journal of Gastroenterology
2025;30(1):38-42
- CountryChina
- Language:Chinese
-
Abstract:
Background:Nutritional risk is highly prevalent among gastric cancer patients,yet accurate screening tools remain lacking.Aims:To construct and validate a nutritional risk prediction model for gastric cancer inpatients.Methods:From August 2023 to July 2024,a total of 295 gastric cancer inpatients admitted to the First Hospital of Qinhuangdao were enrolled,and divided into the model group(n=206)and validation group(n=89)at a ratio of 7∶3.Nutritional screening was performed in the model group using the nutritional risk screening 2002(NRS 2002)score.Univariate analysis and multivariate Logistic regression analysis were employed to identify the independent risk factors for nutritional risk,and a prediction model was constructed.The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the consistency between the model constructed and NRS 2002 score.The predictive performance was assessed using ROC curve and validated in the independent cohort.Risk stratification was performed based on the cut-off value derived from the ROC curve,and the nutritional risk in different subgroups of the model group and validation group was assessed.Results:Multivariate Logistic regression analysis indicated that age≥68 years,body mass index(BMI)≤22 kg/m2,anorexia,dysphagia and anemia were the independent risk factors for nutritional risk in gastric cancer patients in the model group(all P<0.05).The prediction model had good consistency with the NRS 2002 score(P=0.567).ROC curve showed that the area under the curve(AUC)of the prediction model for predicting nutritional risk were 0.840(95%CI:0.785-0.895,P<0.001)for the model group and 0.895(95%CI:0.831-0.958,P<0.001)for the validation group when the cut-off value was set at 9.5 points.The proportion of patients with nutritional risk in high-risk subgroup was significantly higher than that in low-risk subgroup in both model group and validation group(P<0.001).Conclusions:The prediction model based on age,BMI,anorexia,dysphagia and anemia can effectively identify nutritional risk in gastric cancer inpatients and may serve as a clinical reference tool.
