A dynamic online nomogram for predicting the heterogeneity trajectories of frailty among elderly gastric cancer survivors

被引:4
|
作者
Miao, Xueyi [1 ]
Guo, Yinning [1 ]
Ding, Lingyu [2 ]
Xu, Xinyi [3 ]
Zhao, Kang [1 ]
Zhu, Hanfei [1 ]
Chen, Li [2 ]
Chen, Yimeng [1 ]
Zhu, Shuqin [1 ,4 ]
Xu, Qin [1 ,4 ]
机构
[1] Nanjing Med Univ, Sch Nursing, Nanjing 211166, Peoples R China
[2] Nanjing Med Univ, Dept Gastrointestinal Surg, Affiliated Hosp 1, Nanjing 210000, Peoples R China
[3] Queensland Univ Technol, Fac Hlth, Brisbane, Australia
[4] Nanjing Med Univ, Sch Nursing, 101 Longmian Ave, Nanjing, Peoples R China
基金
中国国家自然科学基金;
关键词
Older people; Gastric cancer; Frailty trajectory; Heterogeneity; Prediction; MINI-NUTRITIONAL ASSESSMENT; PROGNOSTIC NOMOGRAMS; DEPRESSION; MORTALITY;
D O I
10.1016/j.ijnurstu.2024.104716
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Background: Frailty is very common among older people with gastric cancer and seriously affects their prognosis. The development of frailty is continuous and dynamic, increasing the difficulty and burden of care. Objectives: The aims of this study were to delineate the developmental trajectory of frailty in older people with gastric cancer 1 year after surgery, identify heterogeneous frailty trajectories, and further explore their predictors to construct a nomogram for prediction. Design: We conducted a prospective longitudinal observation study. Clinical evaluation and data collection were performed at discharge, and at 1, 3, 6, and 12 months. Setting and participants: This study was conducted in a tertiary hospital and 381 gastric cancer patients over 60 years who underwent radical gastrectomy completed the 1-year follow-up. Methods: A growth mixture model (GMM) was used to delineate the frailty trajectories, and identify heterogeneous trajectories. A regression model was performed to determine their predictors and further construct a nomogram based on the predictors. Bootstrap with 1000 resamples was used for internal validation of nomogram, a receiver operating characteristic (ROC) curve to evaluate discrimination, calibration curves to evaluate calibration and decision curve analysis (DCA) to evaluate the clinical value. Results: GMM identified three classes of frailty trajectories: "frailty improving", "frailty persisting" and "frailty deteriorating". The latter two were referred to as heterogeneous frailty trajectories. Regression analysis showed 8 independent predictors of heterogeneous frailty trajectories and a nomogram was constructed based on these predictors. The area under ROC curve (AUC) of the nomogram was 0.731 (95 % CI = 0.679-0.781), the calibration curves demonstrated that probabilities predicted by the nomogram agreed well with the actual observation with a mean absolute error of 0.025, and the DCA of nomogram indicated that the net benefits were higher than that of the other eight single factors. Conclusions: Older gastric cancer patients have heterogeneous frailty trajectories of poor prognosis during oneyear postoperative survival. Therefore, early assessment to predict the occurrence of heterogeneous frailty trajectories is essential to improve the outcomes of elderly gastric cancer patients. Scientific and effective frailty interventions should be further explored in the future to improve the prognosis of older gastric cancer patients. Contribution of the paper statements: This study constructed a static and dynamic online nomogram with good discrimination and calibration, which can help to screen high-risk patients, implement preoperative risk stratifi- cation easily and promote the rational allocation of medical resources greatly. Registration: ClinicalTrials.gov (Number: NCT05982899). Tweetable abstract: Our findings identified three frailty trajectories and constructed a nomogram to implement preoperative risk stratification and improve patient outcomes. (c) 2024 Elsevier Ltd. All rights reserved.
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页数:9
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