Construction and verification of frailty risk prediction model in elderly lung cancer patients

1Xu Mengmeng,1Wang Xiaolan,2Chen Roudi

Electronic Journal of Metabolism and Nutrition of Cancer ›› 2024, Vol. 11 ›› Issue (6) : 840-846.

PDF(1526 KB)
PDF(1526 KB)
Electronic Journal of Metabolism and Nutrition of Cancer ›› 2024, Vol. 11 ›› Issue (6) : 840-846.

Construction and verification of frailty risk prediction model in elderly lung cancer patients

  • 1Xu Mengmeng,1Wang Xiaolan,2Chen Roudi
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Abstract

Objective To investigate the occurrence and influencing factors of frailty in elderly lung cancer patients establish a frailty prediction model and verify it. Method In this study 500 patients with lung cancer admitted to our hospital during the period from January 2022 to March 2024 were selected as research objects. The frailty status and influencing factors were analyzed statistically. Regression analysis was used to construct frailty risk prediction model and the model was displayed and verified by column graph. Result In the modeling group of this study 350 elderly lung cancer patients aged 61-79 years old with an average age of 68. 22 ± 7. 25 years old including 121 females 34. 57% and 229 males 65. 43% participated. Among 350 elderly patients with lung cancer 123 had frailty 35. 14% . Univariate analysis showed that age Charson comorbidity index nutritional status duration of disease body mass index BMI hemoglobin D - dimer albumin depression and cancer fatigue were the independent risk factors for fadility in elderly lung cancer patients P < 0. 05 . Result of multi - factor analysis Age Charson comorbidity index duration of disease D-dimer depression and cancer fatigue were the risk factors for frailty in elderly lung cancer patients P < 0. 05 hemoglobin albumin BMI nutritional status were the protective factors for frailty in elderly lung cancer patients P < 0. 05 . In the verification group AUC was 0. 842 95%CI = 0. 802-0. 886 sensitivity was 83. 5% and specificity was 73. 8%. Conclusion This study established a risk prediction model for frailty in elderly lung cancer patients. Frailty in elderly lung cancer patients is affected by age Charson comorbidity index nutritional status duration of disease D-dimer albumin depression and cancerous fatigue. In the future trajectory studies should be carried out to optimize the prediction model and establish a dynamic nomogram model to provide a reliable tool for clinical nurses to dynamically predict the frailty of elderly patients with lung cancer with a view to reducing frailty.

Key words

Lung cancer / Frailty / A nomogram / Nutritional risk / Prediction model / Senior patients / Risk factor / Risk prediction

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1Xu Mengmeng,1Wang Xiaolan,2Chen Roudi. Construction and verification of frailty risk prediction model in elderly lung cancer patients[J]. Electronic Journal of Metabolism and Nutrition of Cancer. 2024, 11(6): 840-846
PDF(1526 KB)

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