-
Correlation between frailty and body composition in elderly patients with gastric cancer
- GUO Xin, MENG Jun, ZHENG Shiliang, DONG Xiuhong
-
Journal of Shandong University (Health Sciences). 2024, 62(4):
40-47.
doi:10.6040/j.issn.1671-7554.0.2024.0036
-
Abstract
(
235 )
PDF (1166KB)
(
67
)
Save
-
References |
Related Articles |
Metrics
Objective To investigate the correlation between frailty and body composition among elderly patients with gastric cancer, so as to evaluate the efficacy of body composition metrics in forecasting frailty among this demographic. Methods Ninety-six elderly patients with gastric cancer underwent pathological diagnosis at the Affiliated Hospital of Weifang Medical University between September 2021 and August 2023. Utilizing the Fried frailty phenotype(FP), these patients were categorized into either the frailty group or the non-frailty group. Demographic data including age, sex, smoking history, alcohol consumption history, cancer location, cancer stage, body mass index(BMI), body fat content, and body fat percentage were collected for both groups of patients. The fat-free mass index(FFMI), muscle mass index(MMI), upper limb muscle mass index(ULMMI), and lower limb muscle mass index(LLMMI)were computed using the collected data. Univariate Logistic regression analysis was conducted to examine the relationship between these indices and frailty among elderly cancer patients. Subsequently, multivariate Logistic regression analysis was employed to determine if these indices served as independent factors influencing frailty in elderly cancer patients. Additionally, a ROC curve was constructed to assess the predictive capability of these indices for frailty in elderly patients with gastric cancer. Results (1)A total of 96 elderly patients with gastric cancer were included. The incidence of frailty in elderly patients with gastric cancer was 39.58 %. (2)The age and clinical stage of gastric cancer in the frailty group were higher than those of the non-fraity group(all P<0.05 ). (3)Body fat content and body fat percentage in the frailty group were higher than those in the non-frailty group, and FFMI, MMI, and LLMMI were significantly lower than those in the non-frailty group(all P<0.05). (4)Comparison of general data between the two groups revealed that age and clinical stages 3 and 4 of the tumor were associated with the occurrence of frailty in elderly patients with gastric cancer compared to clinical stage 1. Regarding the comparison of body composition between the two groups, FFMI, MMI, and LLMM were inversely correlated with frailty in elderly patients with gastric cancer, while body fat content and body fat percentage showed a positive correlation with frailty in this demographic. (5)After adjusting for age and cancer clinical stage, FFMI, MMI, LLMMI, body fat content, and body fat percentage emerged as independent predictors of frailty in elderly patients with gastric cancer. (6)The ROC curve analysis revealed that the AUC values for FFMI, MMI, LLMMI, body fat content, and body fat percentage were 0.701, 0.645, 0.655, 0.607, and 0.632, respectively. The combined AUC for all these indicators was calculated to be 0.833. Conclusion The detection rate of frailty among elderly patients with gastric cancer is notably high. The amalgamation of independent components within the human body composition holds significant predictive value in diagnosing frailty in this demographic. This approach aids in identifying high-risk groups vulnerable to frailty, thereby offering a theoretical foundation for prioritizing attention to frailty among elderly patients with gastric cancer.