Cancer nursing · 2010
Trajectories of fatigue in patients with breast cancer before, during, and after radiation therapy.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Dhruva Anand, Dodd Marylin, Paul Steven M, Cooper Bruce A, Lee Kathryn, West Claudia, Aouizerat Bradley E, Swift Patrick S, Wara William, Miaskowski Christine
Аннотация
BACKGROUND: Fatigue is a significant problem associated with radiation therapy (RT).
OBJECTIVE: This study examined how evening and morning fatigue changed from the time of simulation to 4 months after the completion of RT and investigated whether specific demographic and disease characteristics and baseline severity of symptoms predicted the initial levels of fatigue and characteristics of the trajectories of fatigue.
METHODS: Seventy-three women with breast cancer completed questionnaires that assessed sleep disturbance, depression, anxiety, and pain prior to the initiation of RT and the Lee Fatigue Scale, over 6 months. Descriptive statistics and hierarchical linear modeling were used for data analysis.
RESULTS: Large amounts of interindividual variability were found in the trajectories of fatigue. Evening fatigue at baseline was negatively influenced by having children at home and depression. The trajectory of evening fatigue was worse for women who were employed. Morning fatigue at baseline was influenced by younger age, lower body mass index, and the degree of sleep disturbance and trait anxiety. Trajectories of morning fatigue were worse for patients with a higher disease stage and more medical comorbidities.
CONCLUSION: Interindividual and diurnal variability in fatigue found in women with breast cancer is similar to that found in men with prostate cancer. However, the predictors of interindividual variability in fatigue between these 2 cohorts were different.
IMPLICATIONS FOR PRACTICE: Diurnal variability and different predictors for morning and evening fatigue suggest different underlying mechanisms. The various predictors of fatigue need to be considered in the design of future intervention studies.
OBJECTIVE: This study examined how evening and morning fatigue changed from the time of simulation to 4 months after the completion of RT and investigated whether specific demographic and disease characteristics and baseline severity of symptoms predicted the initial levels of fatigue and characteristics of the trajectories of fatigue.
METHODS: Seventy-three women with breast cancer completed questionnaires that assessed sleep disturbance, depression, anxiety, and pain prior to the initiation of RT and the Lee Fatigue Scale, over 6 months. Descriptive statistics and hierarchical linear modeling were used for data analysis.
RESULTS: Large amounts of interindividual variability were found in the trajectories of fatigue. Evening fatigue at baseline was negatively influenced by having children at home and depression. The trajectory of evening fatigue was worse for women who were employed. Morning fatigue at baseline was influenced by younger age, lower body mass index, and the degree of sleep disturbance and trait anxiety. Trajectories of morning fatigue were worse for patients with a higher disease stage and more medical comorbidities.
CONCLUSION: Interindividual and diurnal variability in fatigue found in women with breast cancer is similar to that found in men with prostate cancer. However, the predictors of interindividual variability in fatigue between these 2 cohorts were different.
IMPLICATIONS FOR PRACTICE: Diurnal variability and different predictors for morning and evening fatigue suggest different underlying mechanisms. The various predictors of fatigue need to be considered in the design of future intervention studies.
Предметные рубрики MeSH
Age DistributionAnalysis of VarianceAnxietyBody Mass IndexBreast NeoplasmsCircadian RhythmDepressionFatigueFemaleHumansLinear ModelsLongitudinal StudiesMiddle AgedNursing Methodology ResearchPainPredictive Value of TestsRadiotherapy, AdjuvantRisk FactorsSan FranciscoSeverity of Illness IndexSleep Wake DisordersSurveys and Questionnaires