Assessing the Sleep-wake Pattern in Cancer Patients for Predicting a Short Sleep Onset Latency.

Objective: We investigated the sleep parameters and clinical factors related to short sleep onset latency (SL) in cancer patients. Methods: We retrospectively reviewed the medical records of 235 cancer patients. Patient Health Questionnaire-9, State and Trait Anxiety Inventory (State subcategory), Insomnia Severity Index (ISI), Cancer-related Dysfunctional Beliefs about Sleep, and Fear of Progression scale scores and sleep related parameters including sleeping pill ingestion time, bedtime, sleep onset time, and wake-up time were collected. We also calculated the duration from sleeping pill ingestion to bedtime, sleep onset time, and wake-up time; duration from wake-up time to bedtime and sleep onset time; and time spent in bed over a 24 hours period. Results: Among patients not taking sleeping pills (n = 145), early wake-up time (adjusted odds ratio [OR]: 0.39, 95% confidence interval [CI] 0.19-0.78), early sleep onset time (OR: 0.50, 95% CI 0.27-0.93), and low ISI score (OR: 0.82, 95% CI 0.71-0.93) were identified as expecting variables for SL ≤ 30 minutes. Longer duration from wake-up time to bedtime (OR: 2.49, 95% CI 1.48-4.18) predicted SL ≤ 30 minutes. Among those taking sleeping pills (n = 90), early sleep onset time (OR: 0.54, 95% CI 0.39-0.76) and short duration from pill ingestion to sleep onset time (OR: 0.05, 95% CI 0.02-0.16) predicted SL ≤ 30 minutes. Conclusion: Cancer patients who fell asleep quickly spent less time in bed during the day. Thus, before cancer patients with insomnia are prescribed sleeping pills, their sleep parameters should be examined to improve their SL.

Depression, Rather Than Cancer-Related Fatigue or Insomnia, Decreased the Quality of Life of Cancer Patients.

PURPOSE: Cancer-related fatigue is a common and distressing symptom that occurs during cancer treatment. This study aimed to find factors that are related to cancer-related fatigue, and its effect on patients' quality of life. MATERIALS AND METHODS: This study included 159 patients who completed questionnaires and interviews during their initial examination at the sleep clinic for cancer patients, Asan Medical Center, between December 2018 and January 2020. Their medical reports were reviewed retrospectively. Questionnaire data about depression, anxiety, insomnia, fear of disease progression, and dysfunctional beliefs about sleep, pain, and quality of life, were reviewed. Additionally, patient sleep structure data were analyzed. RESULTS: Factors such as depression (p < 0.001), anxiety (p < 0.001), fear of cancer progression (p < 0.001), fatigue (p=0.027), and time in bed during 24 hours (p=0.037) were significant expecting variables for low quality of life from logistic regression analysis. In pathway analysis, depression (p < 0.001), not cancer-related fatigue (p=0.537), act as a direct risk factor on quality of life. And also, depression was an overall risk factor for insomnia, fatigue, and daily activity of cancer patients. CONCLUSION: Cancer-related fatigue did not show significant effect on patient's quality of life in this study. However, the result of pathway analysis highlights the importance of assessing depression in the process of cancer treatment and providing appropriate interventions.

Development of Dysfunctional Beliefs and Attitude about Sleep Scale for Cancer Patients.

Study objectives: This study aimed to develop a scale utilizing the original Dysfunctional Beliefs and Attitudes about Sleep (DBAS) scale that measured maladaptive cognitions associated with sleep that is especially sensitive to cancer patients. In addition to the original scale, we added two additional items that reflected cancer-specific dysfunctional beliefs about sleep. Methods: Participants consisted of 337 cancer patients (mean age 54.0 ± 11.8 years, 32.0% men). All participants completed the DBAS-16, two cancer specific items, and the Insomnia Severity Index. Item-to-total-score correlations, internal consistency, item selection, and factor structure were examined. Results: The DBAS-16 was found to be reliable, and internal consistency was also adequate when adding two cancer-specific questions (Cronbach's alpha = 0.89). A total of 14 items were selected, and a four-factor model was selected using exploratory factor analysis (Tucker-Lewis index = 0.86, root mean square error of approximation = 0.08). The four factors were (a) sleep expectations, (b) worry about insomnia, (c) perceived consequences of insomnia and medication, and (d) two cancer-related items. The modified 14 items of the Cancer-related DBAS (C-DBAS-14) well differentiated cancer patients with and without insomnia. Conclusions: The C-DBAS-14 is a promising measure that has adequate internal consistency. It is also sensitive to sleep-related cognitions in cancer patients and can discriminate patients with cancer who are experiencing insomnia from those who are good sleepers. The enhanced utility of the shortened 14-item scale tailored specifically to cancer patients may be useful in both clinical practice and research settings.Abbreviations: CBT: cognitive behavioral therapy; C-DBAS-14: Cancer-Related Dysfunctional Beliefs and Attitude about Sleep; C-DBS: Cancer-Related Dysfunctional Beliefs about Sleep; DBAS-16: Dysfunctional Beliefs and Attitudes about Sleep; ISI: Insomnia Severity Index.