Morbidity And Relevant Factors Of Severe Fatigue Among Patients With Tumor During Treatment Abstract

[Objective]This study aimed to investigate the incidence and influencing factors of severe fatigue,and explore the relationship among severe fatigue, anxiety, depression and the quality of life,whose result could provide an evidence to improve the life quality of patients with severefatigue.[Methods]Totally667patients with tumor enrolled in this study came from the First AffiliatedHospital of Fujian Medical University,Fujian Medical University ConsonancyHospital,FuZhou General Hospital of Nanjing Military Region and Fujian ProvincialHospital from October2011to October2012. Demographic data and clinical informationwere collected by trained interviewers with self-constructed questionnaires. Multidimensionalfatigue scale,core quality of life scale from the European organization for research andtreatment of cancer and Hospital Anxiety and Depression Scale were used to investgate thepatients.Besides, we investigated the fatigue status of a random sample of healthy peoplefrom Houxian community, Gudong community, Rujiang village of Mawei Town, andShanqian village of Ganzhe Town. We used percentile method to calculate the top5%ofquantile of MFI-20fatigue score as a cut-off point to divide tumor patients if there was asevere fatigue. Univariate analysis of the relationship between Fatigue and quality of life wasrealized by Independent-samples non-parametric test,and the influencing factors of severefatigue were analyzed by unconditional logistic regression; structural equation model wasused to study the the correlations among severe fatigue, anxiety, depression, and survivalquality. [Results]1. Univariate analysis showed that there was a significant difference among theincidence of severe fatigue in different age groups, tumor sites, stages of cancer.2. Multivariate logistic regression analysis demonstrated that age, social support, diseasestage, side-effects rate, hemoglobin, and tumor location were correlated with severe fatigue.3. Regarding gender, age, disease stage and treatment as a stratification factor，there wasa correlation among severe fatigue anxiety, depression, and survival quality accroding to ourresult：in both male and female subgroup，severe fatigue was related to survival quality；However，Only In patients at the age of41～50and51~60，severe fatigue was associatedwith anxiety and depression； Only the patients in I phase,Results revealed some definitecorrelation between survival quality and severe fatigue， but in the rest stages,which wasstatistically significant,severe fatigue was related with survival quality, anxiety anddepression; Moreover,the Incidence of severe fatigue was higher in the patients with anxietyor pression than that in no anxiety or pression group;And the difference of survival qualitywas significant between the groups with or without severe fatigue.4. According to the Linear structural equation analysis， psychological fatigueinfluenced both physical and role function； mental fatigue also had an effect on rolefunction, social function and emotional function；physically fatigue，anxiety and depressioncould influence cognitive function while depression could also have impact on socialfunction；there was a significant positive linear correlation between each dimension of fatigueas well as between anxiety and depression.we obtained a similar result among each dimensionof fatigue，anxiety and depression.[Conclusion]1. The incidence of severe fatigue tends to rise among the patients during a radiation orchemotherapy on tumor.2. Anxiety and depression had an impact on the incidence of severe fatigue of patientsduring radiation therapy and chemotherapy.3. There are correlations among severe fatigue, anxiety, depression, and survivalquality.Therefore, it is necessary to strengthen social support instead of ignoring the negative psychological factors just like fatigue, anxiety and depression. At the same time,more attentions should be paid to the role, emotional, cognitive and social function of patientswith tumor, which in fact improves the quality of life of patients.4.The linear structural equation model has many advantages compared with traditionalstatistical methods in the analysis of latent variables， and should be properly used withprofessional.