肝癌患者行TACE后癌因性疲乏轨迹变化及预测因素研究OA
Trajectory changes and predictive factors of cancer-related fatigue in patients with liver cancer after TACE
目的 探讨肝癌患者行经动脉化疗栓塞术(TACE)后癌因性疲乏(CRF)轨迹的变化,分析轨迹变化的预测因素.方法 采用便利抽样法选取2021年12月至2024年11月在该院行TACE治疗的肝癌患者198例,采用多维疲乏简化量表(MFI-10)评估患者基线、术后1周、术后1个月、术后3个月的CRF水平,通过增长混合模型分析轨迹类别最优数量并命名,使用医院电子病例系统收集患者的临床资料,通过单因素分析及多因素logisitic回归分析轨迹变化的独立影响因素.结果 198例肝癌患者行TACE后CRF可分为4个潜在类别模型:低疲乏缓解型52例(26.26%)、高疲乏缓解型52例(26.26%)、中疲乏缓解型58例(29.29%)、高疲乏持续型36例(18.18%).单因素分析及多因素logistic回归分析结果显示,年龄、家庭人均月收入、汉密尔顿抑郁量表评分、广泛焦虑量表评分、匹兹堡睡眠质量指数量表评分、社会支持评定量表评分均是肝癌患者行TACE后CRF轨迹变化的独立影响因素(P<0.05).结论 肝癌患者行TACE后CRF轨迹存在一定的异质性,且受年龄、抑郁焦虑因素的影响,医护人员可根据各影响因素预测CRF轨迹变化而进行有效的干预措施.
Objective To investigate the trajectory changes of cancer-related fatigue(CRF)in patients with liver cancer after transarterial chemoembolization(TACE)and to analyze the predictive factors of these trajectory changes.Methods Using convenience sampling,198 patients with liver cancer who underwent TA-CE at the hospital from December 2021 to November 2024 were enrolled.The Multidimensional Fatigue In-ventory(MFI-10)was used to assess patients'CRF levels at baseline,1 week,1 month,and 3 months post-TACE.Growth mixture modeling was employed to determine the optimal number of trajectory classes and to name them.Clinical data were collected from the hospital's electronic medical record system.Univariate analy-sis and multivariate logistic regression were used to identify independent factors influencing trajectory chan-ges.Results Four latent class model of CRF trajectories were identified in the 198 patients with liver cancer after TACE:low-fatigue remission type(52 cases,26.26%),high-fatigue remission type(52 cases,26.26%),moderate-fatigue remission type(58 cases,29.29%),and high-fatigue persistent type(36 cases,18.18%).Uni-variate analysis and multivariate logistic regression showed that age,monthly per capita household income,Hamilton Depression Rating Scale score,Generalized Anxiety Disorder scale score,Pittsburgh Sleep Quality Index score,and Social Support Rating Scale score were all independent factors influencing the CRF trajectory changes in patients with liver cancer after TACE(P<0.05).Conclusion The CRF trajectories in patients with liver cancer after TACE exhibit certain heterogeneity and are influenced by factors such as age,depres-sion,and anxiety.Medical staff can predict CRF trajectory changes based on these influencing factors and im-plement effective interventions accordingly.
戴玲香;蔡丽丽;黄菁;邓美晨;刘晓芹;邹丰英
吉安市中心人民医院,江西 吉安 343000吉安市中心人民医院,江西 吉安 343000吉安市中心人民医院,江西 吉安 343000吉安市中心人民医院,江西 吉安 343000吉安市中心人民医院,江西 吉安 343000吉安市中心人民医院,江西 吉安 343000
医药卫生
肝癌经动脉化疗栓塞术癌因性疲乏预测因素增长混合模型
Liver cancerTransarterial chemoembolizationCancer-related fatiguePredictive factorsGrowth mixture model
《现代医药卫生》 2026 (6)
1215-1220,6
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