The study of potential contributors to fatigue, such as sleep disturbance, has been identified as a research priority in pediatric cancer. The primary objective of this descriptive study was to explore relationships between sleep habits, sleep disturbance, and fatigue for children receiving maintenance chemotherapy for acute lymphoblastic leukemia (ALL). This study also described sleep habits, sleep disturbance, and fatigue of parents of children and adolescents with ALL and determined if relationships existed between parent and child sleep disturbance and fatigue. Using a descriptive, cross-sectional design, children aged 4-18 years receiving maintenance chemotherapy for ALL and their parents completed questionnaires about their sleep and fatigue. Sleep disturbance was common in both children (87%) and parents (48%) and sleep disturbance scores were positively correlated with fatigue scores. From qualitative written responses to open-ended questions, 9 themes emerged related to sleep for children undergoing maintenance chemotherapy for ALL. Sleep differences noted since diagnosis included (1) sleep is disturbed, (2) sleep habits have changed, and (3) sleep is unchanged or improved. Things that got in the way of children sleeping well included (4) side effects of medication, especially dexamethasone; and (5) medication schedules. Things that helped children get sleep at night were (6) sleeping with someone, (7) comforting activities or routine, (8) medications, and (9) food and drink. Sleep disturbance in children on ALL maintenance and their parents is common and likely contributes to increased fatigue and is a potential target for nursing interventions.

Background Dexamethasone contributes to high cure rates in pediatric 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-day study: 5 days of no dexamethasone (OFF DEX) followed by 5 days 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-day period, parents and patients 7 years of age and older completed a sleep diary and Fatigue Scale questionnaire. Blood was collected at 0 (pre-dexamethasone), 1, 2, 4, and 8 hours after the first oral dexamethasone dose for pharmacokinetic analysis. Serum albumin concentration was retrospectively analyzed 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 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 pediatric patients receiving dexamethasone.

This study identified the lack of an appropriate symptom screening tool for use by pediatric cancer patients. A preliminary version of SSPedi was developed. Subsequent work will ensure that it is understandable by children and evaluate its psychometric properties.

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, i.e., 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 (ROC) 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.

Fatigue is one of the most common and distressing symptoms experienced by adolescents during and after treatment for cancer. The lack of reliable and valid instruments has prevented an accurate assessment of the trajectory of fatigue among adolescent oncology patients. The purposes of this study were to identify the items on the Fatigue Scale-Adolescent (FS-A) that distinguished adolescents with high fatigue and to identify the most sensitive and specific score ("cut score") in order to identify those in need of a fatigue intervention. Rasch methods were used to identify FS-A items that distinguished adolescents with high cancer-related fatigue, and results indicated that the 14-item FS-A could be reduced to 13 items. The 13-item FS-A was assessed for its psychometric properties, with application of the receiver operating characteristics curve analysis to the responses from 75 adolescents. The internal consistency coefficient was .87, and a 4-factor confirmatory analysis achieved good fit coefficients. The identified cut score was 31, with 66.6% sensitivity and 82.6% specificity; 16 (21.33%) of the patients scored 31 or higher. The 13-item FS-A has acceptable psychometric properties and is able to identify adolescent oncology patients with high fatigue.