BackgroundA systematic literature review was conducted to (a) identify the most frequently used health-related quality of life (HRQOL) models and (b) critique those models.MethodsOnline search engines were queried using pre-determined inclusion and exclusion criteria. We reviewed titles, abstracts, and then full-text articles for their relevance to this review. Then the most commonly used models were identified, reviewed in tables, and critiqued using published criteria.ResultsOf 1,602 titles identified, 100 articles from 21 countries met the inclusion criteria. The most frequently used HRQOL models were: Wilson and Cleary (16%), Ferrans and colleagues (4%), or World Health Organization (WHO) (5%). Ferrans and colleagues’ model was a revision of Wilson and Cleary’s model and appeared to have the greatest potential to guide future HRQOL research and practice.ConclusionsRecommendations are for researchers to use one of the three common HRQOL models unless there are compelling and clearly delineated reasons for creating new models. Disease-specific models can be derived from one of the three commonly used HRQOL models. We recommend Ferrans and colleagues’ model because they added individual and environmental characteristics to the popular Wilson and Cleary model to better explain HRQOL. Using a common HRQOL model across studies will promote a coherent body of evidence that will more quickly advance the science in the area of HRQOL.

Although sleep is vital to all human functioning and poor sleep is a known problem in cancer, it is unclear whether the overall prevalence of the various types of sleep disorders in cancer is known. The purpose of this systematic literature review was to evaluate if the prevalence of sleep disorders could be ascertained from the current body of literature regarding sleep in cancer. This was a critical and systematic review of peer-reviewed, English-language, original articles published from 1980 through 15 October 2013, identified using electronic search engines, a set of key words, and prespecified inclusion and exclusion criteria. Information from 254 full-text, English-language articles was abstracted onto a paper checklist by one reviewer, with a second reviewer randomly verifying 50% (k = 99%). All abstracted data were entered into an electronic database, verified for accuracy, and analyzed using descriptive statistics and frequencies in SPSS (v.20) (North Castle, NY). Studies of sleep and cancer focus on specific types of symptoms of poor sleep, and there are no published prevalence studies that focus on underlying sleep disorders. Challenging the current paradigm of the way sleep is studied in cancer could produce better clinical screening tools for use in oncology clinics leading to better triaging of patients with sleep complaints to sleep specialists, and overall improvement in sleep quality.

Current evidence shows that sleep-wake disturbances are a persistent problem linked to poor quality of life in women surviving breast cancer. Information regarding correlates of sleep-wake disturbances in long-term survivors is sparse. The purpose of this study was to refine knowledge regarding prevalence, severity, and correlates of sleep-wake disturbances in long-term breast cancer survivors (BCS) compared to age-matched women without breast cancer (WWC). The cross-sectional convenience sample included 246 BCS and 246 WWC who completed a quality-of-life study and were matched within +/− 5 years of age. BCS were a mean of 5.6 years beyond completion of cancer treatment (range 5.6 to 10.0 years). Based on Pittsburgh Sleep Quality Index (PSQI) scores, BCS had significantly more prevalent sleep-wake disturbances (65%) compared to WWC (55%) (P < 0.05). BCS also had significantly higher PSQI global scores indicating poorer sleep quality compared to WWC (P < 0.05). Significant correlates of prevalence of poor sleep for BCS included hot flashes, poor physical functioning, depressive symptoms and distress, and for WWC, included hot flashes, poor physical functioning, and depressive symptoms. Significant correlates (P < 0.05) of severity of poor sleep for BCS included presence of non-cancer co-morbidities, hot flashes, depressive symptoms, and residual effects of cancer treatment. For WWC, these included hot flashes, poor physical functioning, depressive symptoms, and impact of a life event. Knowledge of prevalence, severity, and correlates of sleep-wake disturbances provides useful information to health care providers during clinical evaluations for treatment of sleep-wake disturbances in BCS.

No abstract

Study Objectives: To determine effects of yoga and aerobic exercise compared with usual activity on objective assessments of sleep in midlife women. Methods: Secondary analyses of a randomized controlled trial in the Menopause Strategies: Finding Lasting Answers for Symptoms and Health (MsFLASH) network conducted among 186 late transition and postmenopausal women aged 40-62 y with hot flashes. Women were randomized to 12 w of yoga, supervised aerobic exercise, or usual activity. The mean and coefficient of variation (CV) of change in actigraph sleep measures from each intervention group were compared to the usual activity group using linear regression models. Results: Baseline values of the primary sleep measures for the entire sample were mean total sleep time (TST) = 407.5 ± 56.7 min; mean wake after sleep onset (WASO) = 54.6 ± 21.8 min; mean CV for WASO = 37.7 ± 18.7 and mean CV for number of long awakenings > 5 min = 81.5 ± 46.9. Changes in the actigraphic sleep outcomes from baseline to weeks 11-12 were small, and none differed between groups. In an exploratory analysis, women with baseline Pittsburgh Sleep Quality Index higher than 8 had significantly reduced TST-CV following yoga compared with usual activity. Conclusions: This study adds to the currently scant literature on objective sleep outcomes from yoga and aerobic exercise interventions for this population. Although small effects on self-reported sleep quality were previously reported, the interventions had no statistically significant effects on actigraph measures, except for potentially improved sleep stability with yoga in women with poor self-reported sleep quality. Keywords: actigraphy, exercise, insomnia symptoms, menopause, variability, vasomotor symptoms, yoga Citation: Buchanan DT, Landis CA, Hohensee C, Guthrie KA, Otte JL, Paudel M, Anderson GL, Caan B, Freeman EW, Joffe H, LaCroix AZ, Newton KM, Reed SD, Ensrud KE. Effects of yoga and aerobic exercise on actigraphic sleep parameters in menopausal women with hot flashes.

Context Sleep is a significant problem in breast cancer survivors (BCS) and measured frequently using the Pittsburgh Sleep Quality Index (PSQI). Thus, it is important to evaluate its factor structure. The two-process model of sleep regulation was the theoretical framework for this study. Objectives To perform a confirmatory factor analysis of the PSQI in BCS and compare results between African-American and Caucasian BCS. Methods This was a secondary analysis of cross-sectional data using local and regional health care facilities and Eastern Cooperative Oncology Group referrals. The study included 1174 non-depressed BCS (90% Caucasian), with a mean age of 57 years and median PSQI global scores at the cut-off for poor sleep (median = 6.00, interquartile range = 4.00–9.00). Measurements included self-reported demographics, medical history, depression, and sleep. Results Acceptable fit was not reached for the traditional one-factor model that would be consistent with current PSQI scoring or for alternative models in published literature from other populations. A new two-factor model (i.e., sleep efficiency and perceived sleep quality) best fit the data but nested-model comparisons by race showed different relationships by race for 1) sleep quality–sleep latency, and 2) sleep efficiency–sleep quality. Conclusion Results were inconsistent with current PSQI scoring that assumes a single global factor and with previously published literature. Although a new two-factor model best fit the data, further quantitative and qualitative analyses are warranted to validate our results in other populations before revising PSQI scoring recommendations. Additional recommendations for research are described.

Objectives To evaluate the relationships among measures of hot flushes, perceived hot flush interference, sleep disturbance, and measures of quality of life while controlling for potential covariates (patient and treatment variables). Methods Breast cancer survivors (n = 395) due to receive aromatase inhibitor therapy provided demographic information, physiological hot flush data via sternal skin conductance monitoring, hot flush frequency via written diary and electronic event marker, hot flush severity and bother via written diary, and questionnaire data via the Hot Flash Related Daily Interference Scale, Pittsburgh Sleep Quality Index, the EuroQOL, Hospital Anxiety and Depression Scale and the Center for Epidemiologic Studies Depression Scale. Results Confirmatory factor analysis supported a two-factor model for hot flush symptoms (frequency and severity). Although there was strong convergence among self-reported hot flush measures, there was a high degree of unexplained variance associated with physiological measures. This suggests that self-report and physiological measures do not overlap substantially. The structural model showed that greater hot flush frequency and severity were directly related to greater perceived interference with daily life activities. Greater perceived interference, in turn, directly predicted greater sleep disruption, which predicted lower perceived health state and more symptoms of anxiety and depression. Conclusions Findings suggest hot flush interference may be the most appropriate single measure to include in clinical trials of vasomotor symptom therapies. Measuring and ameliorating patients' perceptions of hot flush interference with life activities and subjective sleep quality may be the most direct routes to improving quality of life.

In the prospective Exemestane and Letrozole Pharmacogenetics trial of adjuvant aromatase inhibitor (AI) therapy for early-stage breast cancer, worsening of multiple treatment-related symptoms during AI therapy predicted AI early discontinuation. If these findings are confirmed in independent trials, early detection of changes in PRO measures could be used clinically to target interventions in patients at high risk for early discontinuation.