Sleep Disorders and Sleep Quality in Moroccan Adult Patients with Cancer during Treatment

Background: Sleep disruption is a common problem for patients with cancer. Several recent studies have reported an incidence of 30% to 50% in this group, compared to 15% in the general population, but it has received little attention from the oncology community compared with other symptoms accompanying cancer. Patients and methods: It is a cross-sectional study where we included a total of 284 patients with cancer during treatment. All patients were offered brief sleep questionnaires, judgment criteria were based on the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), and the Epworth Sleepiness Scale (ESS) to assess respectively sleep quality, insomnia, and sleepiness. We analyzed data by calculation of Cronbach’s alpha coefficient for the reliability of measurements, and by simple and multiple logistic regressions. Results: Internal consistency measurement of the ISI, ESC, PSQI subscales questionnaires found a Cronbach’s alpha coefficient of 0.895, 0.618 and 0.669, respectively. 52% of patients have no clinically significant insomnia, 12.5% have Subthreshold insomnia, 25% have clinical insomnia (moderate severity) and 10.5% have severe clinical insomnia. Patients with urologic, head and neck, and gastro-intestinal cancer had higher scores than patients with breast and gynecologic cancer. As for patients receiving surgery and chemotherapy, the ISI average score was respectively 14.3 ± 4.4 and 13.8 ± 4.9. it was statistically different (p<0.001) in post-hoc correction from the average scores of patients receiving radiotherapy (13.2 ± 3.8). In multivariate analysis, the strongest associated factors with insomnia were lowest SES (OR=3.849 [1,684-5,159]), head and neck cancer (OR=3.129 (1,985-5,129)), urologic cancer (OR=2.919 [1,985-5,295]), Surgery (OR=3.201 [1,993-8,157]), and Chemotherapy (OR=3.154 [2,869-7,818]). Regarding daytime sleepiness, 49.6% of patients were in normal range in healthy adults 32% have moderate sleepiness and 18.4% have severe sleepiness. Multivariate analysis of age, sex, marital status, SES, cancer type, and treatment type show that older patients more than 60 years, single patients, surgery and chemotherapy were the independent associated factors with somnolence and this was statistically significant. While married status was a protector factor. 28.2% of patients tested did not have impaired quality of sleep, 39.1% had moderate sleep quality, while 32.7% reported severe impaired sleep quality. According to the in PSQI score, independent factors associated with poor quality of sleep found in multivariate analysis were primarily younger patients (OR>8.8, p=0.001), followed by urologic cancer (OR>4, p=0.001), head and neck cancer (OR=1.979, p=0.006), and lowest level of SES (OR=4.119, p=0.001), regarding type of treatment there is no significant difference between different treatment. 74% of patients with sleep disturbances report that their sleep disorders decrease quality of life, 41% report fatigue, 53% experienced mental capacity degradation and 39% of patients report that affect Interpersonal relationship, and their humor in 42%. Conclusion: Patients with head and neck cancer and urological cancer, patients receiving chemotherapy and surgery should be investigated especially among younger ones, in order to detect those at risk of sleep disruption and offer them appropriate support. Citation: Echchikhi Y, El-Abbassi S, Touil A, Kacemi H, El-Majjaoui S, et al. (2017) Sleep Disorders and Sleep Quality in Moroccan Adult Patients with Cancer during Treatment. J Cancer Sci Ther 9: 637-643. doi:10.4172/1948-5956.1000486 J Cancer Sci Ther ISSN: 1948-5956 JCST, an open access journal Volume 9(9) 637-643 (2017) 638 Student’s t-test was used to compare the result score in different categories of age (less than 30 years, between 30 and 60 years, and more than 60 years) The relationship between all the above-mentioned independent variables and each dependent factor was analyzed by simple logistic regression. We fixed a significance threshold of 0.250 in univariate analysis to include variables in the multivariate model where multiple logistic regression was performed. The error risk was set at 0.05 to assess result statistical significance.