Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia

BackgroundTo explore the risk factors associated with falls in elderly lung cancer patients with sarcopenia, construct a predictive model, and validate its performance.MethodsThis cross-sectional study involved 316 lung cancer patients with sarcopenia who were hospitalized in the oncology, thoracic...

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Main Authors: Qing Wang, Xiao Han, Jun Zhang, Mengying Hu, Jiaojiao Xu, Qiongqiong Ai, Hequn Wei, Jiao Yu, Haiping Ma
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Oncology
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Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1533368/full
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author Qing Wang
Qing Wang
Xiao Han
Jun Zhang
Jun Zhang
Mengying Hu
Mengying Hu
Jiaojiao Xu
Qiongqiong Ai
Hequn Wei
Jiao Yu
Haiping Ma
author_facet Qing Wang
Qing Wang
Xiao Han
Jun Zhang
Jun Zhang
Mengying Hu
Mengying Hu
Jiaojiao Xu
Qiongqiong Ai
Hequn Wei
Jiao Yu
Haiping Ma
author_sort Qing Wang
collection DOAJ
description BackgroundTo explore the risk factors associated with falls in elderly lung cancer patients with sarcopenia, construct a predictive model, and validate its performance.MethodsThis cross-sectional study involved 316 lung cancer patients with sarcopenia who were hospitalized in the oncology, thoracic surgery, and respiratory medicine departments of a tertiary hospital in Jiangxi Province between January 2023 and December 2023. Data were collected through questionnaires and physical measurements. A logistic regression predictive model was developed on the basis of independent risk factors.ResultsThe incidence of falls among elderly lung cancer patients with sarcopenia was 19.94%. Multivariate logistic regression analysis identified multiple metastases, nocturia (≥3 times per night), sleep disorders, frailty, and malnutrition as independent risk factors for falls. The Hosmer - Lemeshow test indicated good model fit (X2 = 5.353, P=0.719), with an overall predictive accuracy of 83.7%. The area under the ROC curve (AUC) was 0.832, and the Youden index reached a maximum of 0.577, corresponding to a sensitivity of 74.7%, specificity of 83.0%, and an optimal cut-off value of 0.221.ConclusionThe risk prediction model for falls in elderly lung cancer patients with sarcopenia, which is based on independent predictors, demonstrated good predictive performance. This model facilitates the timely identification of high-risk patients, providing scientific evidence to support the development of precise clinical management strategies.
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spelling doaj-art-98cc7720e4d5400c8e6762e6179b4ee32025-08-20T03:21:39ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-06-011510.3389/fonc.2025.15333681533368Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopeniaQing Wang0Qing Wang1Xiao Han2Jun Zhang3Jun Zhang4Mengying Hu5Mengying Hu6Jiaojiao Xu7Qiongqiong Ai8Hequn Wei9Jiao Yu10Haiping Ma11The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaSchool of Nursing, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaThe Affiliated Stomatological Hospital of Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaSchool of Nursing, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaSchool of Nursing, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaThe Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, ChinaBackgroundTo explore the risk factors associated with falls in elderly lung cancer patients with sarcopenia, construct a predictive model, and validate its performance.MethodsThis cross-sectional study involved 316 lung cancer patients with sarcopenia who were hospitalized in the oncology, thoracic surgery, and respiratory medicine departments of a tertiary hospital in Jiangxi Province between January 2023 and December 2023. Data were collected through questionnaires and physical measurements. A logistic regression predictive model was developed on the basis of independent risk factors.ResultsThe incidence of falls among elderly lung cancer patients with sarcopenia was 19.94%. Multivariate logistic regression analysis identified multiple metastases, nocturia (≥3 times per night), sleep disorders, frailty, and malnutrition as independent risk factors for falls. The Hosmer - Lemeshow test indicated good model fit (X2 = 5.353, P=0.719), with an overall predictive accuracy of 83.7%. The area under the ROC curve (AUC) was 0.832, and the Youden index reached a maximum of 0.577, corresponding to a sensitivity of 74.7%, specificity of 83.0%, and an optimal cut-off value of 0.221.ConclusionThe risk prediction model for falls in elderly lung cancer patients with sarcopenia, which is based on independent predictors, demonstrated good predictive performance. This model facilitates the timely identification of high-risk patients, providing scientific evidence to support the development of precise clinical management strategies.https://www.frontiersin.org/articles/10.3389/fonc.2025.1533368/fullelderlylung cancersarcopeniafallspredictive model
spellingShingle Qing Wang
Qing Wang
Xiao Han
Jun Zhang
Jun Zhang
Mengying Hu
Mengying Hu
Jiaojiao Xu
Qiongqiong Ai
Hequn Wei
Jiao Yu
Haiping Ma
Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
Frontiers in Oncology
elderly
lung cancer
sarcopenia
falls
predictive model
title Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
title_full Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
title_fullStr Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
title_full_unstemmed Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
title_short Construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
title_sort construction of a risk prediction model for falls in elderly lung cancer patients with sarcopenia
topic elderly
lung cancer
sarcopenia
falls
predictive model
url https://www.frontiersin.org/articles/10.3389/fonc.2025.1533368/full
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