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Abstract: Context: Despite the recognized distressing symptom of fatigue in children with cancer, little information is available to assist in the selection of an instrument to be used to measure fatigue. Objectives: The objectives of this study were to 1) describe the instruments that have been used to measure cancer-related fatigue in children and adolescents and 2) summarize the psychometric properties of the most commonly used instruments used to measure fatigue in children and adolescents with cancer. Methods: Five major electronic databases were systematically searched for studies using a fatigue measurement scale in a population of children or adolescents with cancer. Fatigue scales used in those studies were included in the review. Results: From a total of 1753 articles, 25 were included. We identified two main fatigue measurement instruments used in a pediatric oncology population: 1) the Fatigue Scale-Child/Fatigue Scale-Adolescent and the proxy report versions for parents and staff and 2) the PedsQL™ Multidimensional Fatigue Scale. These two scales show similar attributes with reasonably good internal consistency and responsiveness. Conclusion: Either the Fatigue Scale or PedsQL Multidimensional Fatigue Scale can be incorporated into clinical research. Future research should focus on identifying specific fatigue measures more suited to different purposes such as comparative trials or identification of high-risk groups. [Copyright &y& Elsevier]

Background: Dexamethasone contributes to high cure rates in paediatric acute lymphoblastic leukaemia (ALL) but significantly and adversely alters sleep and fatigue. Herein we explored three mechanisms (pharmacokinetics, serum albumin and pharmacogenetics) through which dexamethasone may cause debilitating fatigue and disrupted sleep. Methods: We enrolled 100 patients on a 10-d study: 5-d of no dexamethasone (OFF DEX) followed by 5-d of dexamethasone (ON DEX) during continuation chemotherapy. Sleep variables were collected with continuous actigraphy on days 1 through 5, both OFF DEX and ON DEX. On days 2 and 5 of each 5-d period, parents and patients 7years of age and older completed a sleep diary and Fatigue Scale questionnaire. Blood was collected at 0 (pre-dexamethasone), 1, 2, 4 and 8h after the first oral dexamethasone dose for pharmacokinetic analysis. Serum albumin concentration was retrospectively analysed in stored samples. Patient DNA was genotyped for 99 polymorphic loci in candidate genes associated with glucocorticoid metabolism. Results: Dexamethasone clearance was significantly greater in younger patients than in older ones and in lower risk patients. In multiple regression models, risk group was significantly related to pharmacokinetic parameters. We found that polymorphisms in three genes (AHSG, IL6, POLDIP3) were significantly associated with sleep measures but not with fatigue. Conclusion: Risk group had the most significant relationship with disrupted sleep in patients while on dexamethasone. Serum albumin levels had neither a direct relationship with sleep or fatigue variables nor an indirect relationship through systemic exposure to dexamethasone. We identified candidate genes that may help explain the adverse events of disrupted sleep in paediatric patients receiving dexamethasone. [Copyright &y& Elsevier]

Fatigue is one of the most debilitating conditions associated with cancer and anticancer therapy. The lack of reliable and valid self-report instruments has prevented accurate assessment of fatigue in pediatric oncology patients. The purpose of this study was to identify the most sensitive and specific score, that is, the "cut score," on the Fatigue Scale-Child (FS-C) to identify those children with high cancer-related fatigue in need of clinical intervention. We first used Rasch methods to identify the items on the FS-C that distinguished children with high cancer-related fatigue from other children; our findings indicated that the FS-C needed to be reduced from 14 items to 10 items. We then assessed the 10-item FS-C for its psychometric properties and applied the receiver operating characteristics curve analysis to the FS-C responses from 221 children (aged 7-12 years) receiving anticancer treatment. The cut score identified with 75% sensitivity and 73.5% specificity was 12; 73 (33%) patients scored 12 or higher. Findings from this validated instrument provide a needed guide for clinicians to interpret fatigue scores and provide clinical interventions for this debilitating condition to their pediatric patients with cancer. [ABSTRACT FROM AUTHOR]

Abstract: Fatigue is one of the most debilitating conditions associated with cancer and anticancer therapy. The lack of reliable and valid self-report instruments has prevented accurate assessment of fatigue in pediatric oncology patients. The purpose of this study was to identify the most sensitive and specific score, that is, the “cut score,” on the Fatigue Scale-Child (FS-C) to identify those children with high cancer-related fatigue in need of clinical intervention. We first used Rasch methods to identify the items on the FS-C that distinguished children with high cancer-related fatigue from other children; our findings indicated that the FS-C needed to be reduced from 14 items to 10 items. We then assessed the 10-item FS-C for its psychometric properties and applied the receiver operating characteristics curve analysis to the FS-C responses from 221 children (aged 7–12 years) receiving anticancer treatment. The cut score identified with 75% sensitivity and 73.5% specificity was 12; 73 (33%) patients scored 12 or higher. Findings from this validated instrument provide a needed guide for clinicians to interpret fatigue scores and provide clinical interventions for this debilitating condition to their pediatric patients with cancer. [Copyright &y& Elsevier]