文章摘要
郭 彬,刘 姣,赵丽军,石小毛,何 梦.原发性肝癌患者术后癌因性疲乏的影响因素及其预测模型构建[J].,2024,(9):1707-1711
原发性肝癌患者术后癌因性疲乏的影响因素及其预测模型构建
Influencing Factors of Postoperative Cancer-Related Fatigue in Patients with Primary Liver Cancer and the Construction of its Prediction Model
投稿时间:2023-11-24  修订日期:2023-12-20
DOI:10.13241/j.cnki.pmb.2024.09.021
中文关键词: 原发性肝癌  癌因性疲乏  影响因素  预测模型
英文关键词: Primary liver cancer  Cancer-related fatigue  Influencing factors  Prediction model
基金项目:湖南省科技计划项目(2015SK2048)
作者单位E-mail
郭 彬 湖南省人民医院(湖南师范大学附属第一医院)肝病内科 湖南 长沙 410000 guo6514wk@126.com 
刘 姣 湖南省人民医院(湖南师范大学附属第一医院)肝病内科 湖南 长沙 410000  
赵丽军 湖南省人民医院(湖南师范大学附属第一医院)肝病内科 湖南 长沙 410000  
石小毛 湖南省人民医院(湖南师范大学附属第一医院)肝病内科 湖南 长沙 410000  
何 梦 湖南省人民医院(湖南师范大学附属第一医院)肝病内科 湖南 长沙 410000  
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中文摘要:
      摘要 目的:分析原发性肝癌患者术后癌因性疲乏(CRF)的影响因素并构建预测模型。方法:选取2020年1月~2023年1月湖南师范大学附属第一医院收治接受手术治疗的200例原发性肝癌患者,根据术后3个月是否存在CRF将患者分为CRF组(124例)和非CRF组(76例)。单因素和多因素Logistic回归分析影响原发性肝癌患者术后CRF的因素并构建其预测模型。通过受试者工作特征(ROC)曲线分析预测模型对原发性肝癌患者术后CRF的预测价值。结果:单因素分析显示,CRF组病程长于非CRF组,Child-Pugh分级B级、美国东部肿瘤协作组功能状态(ECOG)评分1~2分、辅助化疗、医疗付费方式自费、抑郁/焦虑比例高于非CRF组,文化程度高中及以上、家庭月收入>3000元、高度社会支持度比例低于非CRF组(P<0.05)。多因素Logistic回归分析显示,病程延长、Child-Pugh分级B级、ECOG评分1~2分、辅助化疗、医疗付费方式自费、抑郁/焦虑为影响原发性肝癌患者术后CRF的独立危险因素,家庭月收入>3000元、高度社会支持为独立保护因素(P<0.05)。原发性肝癌患者术后CRF的预测模型方程:Logit(P)=P/1-P=-1.252+0.409×病程+0.839×Child-Pugh分级+1.378×ECOG评分+1.055×辅助化疗+1.476×医疗付费方式-0.793×家庭月收入+0.883×抑郁/焦虑-1.260×社会支持度。霍斯默-莱梅肖检验P>0.05。ROC曲线分析显示,模型预测原发性肝癌患者术后CRF的曲线下面积为0.910,敏感度为87.10%,特异度为85.53%。结论:病程、Child-Pugh分级、ECOG评分、辅助化疗、医疗付费方式、抑郁/焦虑、家庭月收入、社会支持度为影响原发性肝癌患者术后CRF的因素,基于此构建的预测模型对原发性肝癌患者术后CRF的预测价值较高,可能有助于临床早期发现和干预原发性肝癌患者术后CRF,以改善患者预后。
英文摘要:
      ABSTRACT Objective: To analyze the influencing factors of postoperative cancer-related fatigue (CRF) in patients with primary liver cancer and to construct a prediction model. Methods: 200 primary liver cancer patients who underwent surgical treatment in the First Affiliated Hospital of Hunan Normal University from January 2020 to January 2023 were selected, patients were divided into CRF group (124 cases) and non-CRF group (76 cases) according to the presence or absence of CRF at 3 months after surgical. The factors affecting postoperative CRF in primary liver cancer patients were analyzed by univariate and multivariate logistic regression analysis and to construct its prediction model. The predictive value of the prediction model for postoperative CRF in primary liver cancer patients was analyzed by receiver operating characteristic (ROC) curve. Results: Univariate analysis showed that, the course of disease in CRF group was longer than that in non-CRF group, the Child-Pugh grade B, the Eastern Cooperative Oncology Group (ECOG) score of 1~2 points, adjuvant chemotherapy, medical payment at their own expense and the proportion of depression/anxiety were higher than those in non-CRF group, and the proportion of high school education and above, family monthly income >3 000 yuan and high social support were lower than those in non-CRF group(P<0.05). Multivariate Logistic regression analysis showed that, prolonged course of disease, Child-Pugh grade B, ECOG score of 1~2 points, adjuvant chemotherapy, medical payment at their own expense, depression/anxiety were independent risk factors for postoperative CRF in primary liver cancer patients, family monthly income >3000 yuan and high social support were independent protective factors(P<0.05). The prediction model equation of postoperative CRF in primary liver cancer patients: Logit (P)=P/1-P=-1.252+0.409×course of disease+0.839×Child-Pugh classification+1.378×ECOG score+1.055×adjuvant chemotherapy+1.476×medical payment method-0.793×family monthly income+0.883×depression/anxiety-1.260×social support. Hosmer-Lemeshaw test P>0.05. ROC curve analysis showed that, the area under the curve of the model for predicting postoperative CRF in primary liver cancer patients was 0.910, the sensitivity was 87.10%, and the specificity was 85.53%. Conclusion: The course of disease, Child-Pugh classification, ECOG score, adjuvant chemotherapy, medical payment method, depression/anxiety, family monthly income and social support are the factors affecting postoperative CRF in primary liver cancer patients, the predictive model base on this has a high predictive value for postoperative CRF in primary liver cancer patients, which may be helpful for early clinical detection and intervention of postoperative CRF in primary liver cancer patients to improve the prognosis of patients.
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