Risk Factors and Predictors of Sleep Disturbances in Breast Cancer Women With Docetaxel Treatment

Sunday, 22 July 2018

Ya-Ning Chan, MS1
Ya-Jung Wang, PhD, RN1
You-Wun Jheng, MS, RN2
(1)School of Nursing, National Yang-Ming University, Taipei, Taiwan
(2)Taichung Veterans General Hospital, Taichung, Taiwan


Sleep disturbance is a prevalent problem with varied occurrence rate from 20% to 70% in breast cancer population (Fiorentino & Ancoli-Israel, 2006). Sleep disturbance not only is identified as a cluster symptom with fatigue and depression (Ho, Rohan, Parent, Tager, & McKinley, 2015), but significantly associates with decreased health-related quality of life (Liu et al., 2013). Therefore, in order to enable clinical staff facilitating early awareness of breast cancer women with poor sleep quality, the purposes of this study were to identify the prevalence, risk factors and predictors of poor sleep quality in breast cancer women.


Secondary data were from a cross-sectional research focusing on 140 breast cancer women undergoing at least one cycle of taxane in a teaching hospital in northern Taiwan. Women who have been diagnosed over five years (n=7), treated with various chemotherapy regimens (n=7) and with regimens including platinum (n=16) or paclitaxel (n=12) were excluded. A total of 98 breast cancer women with docetaxel treatment were included. The demographic and clinical characteristics were collected using the information sheet developed by research investigators. Furthermore, anxiety and depression were assessed using Hospital Anxiety and Depression Scale (HADS); chemotherapy-induced peripheral neuropathy was assessed using Patient Neurotoxicity Questionnaire (PNQ); neuropathic pain was assessed using Identification Pain Questionnaire (ID pain); functional status was assessed using peripheral neuropathy scale (PNS) and Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality. All questionnaires were Traditional Chinese version. Besides, both descriptive (mean, standard deviation, frequency, percentage) and inferential (chi-squared test, independent sample t test, binary logistic regression) statistics were performed using SPSS 20.0 software.


The results indicated that most participants were younger than 55 years old (62.3%), newly diagnosed (98%), in early cancer stage (70.4%), with lymph nodes involvement (55.1%) and undergoing chemotherapy (61.3%). In terms of sleep, more than 60% of participants suffering from poor sleep quality (PSQI cut off point of 5). Demographic characteristics showed no significant association with the prevalence of sleep disturbances. However, patients with chronic illness (OR=2.753, p=0.041), with anxiety (OR=7.714, p=0.009), with neuropathic pain (OR=11.261, p=0.022), with sensory neuropathy (OR=2.529, p=0.032), with motor neuropathy (OR=3.781, p=0.002), with worse functional status (OR=1.154, p<0.001) and undergoing chemotherapy (OR=2.593, p=0.027) had a higher risk to develop poor sleep quality. On the contrary, targeted therapy (OR=0.351, p=0.015) was identified as the protective factor of sleep quality. Furthermore, the predictors of poor sleep quality were also identified, including anxiety (OR=7.331, p=0.019), worse functional status (OR=1.160, p=0.001) and with targeted therapy (OR=0.269, p=0.009).


The prevalence of poor sleep quality was relatively high comparing with literature review article in breast cancer population (Fiorentino & Ancoli-Israel, 2006). Unlike clinical characteristics, demographic characteristics had no contribution to develop sleep disturbances. Similarly, studies also indicated that anxiety, depression, neuropathic pain (Fontes, Severo, Gonçalves, Pereira, & Lunet, 2017) , undergoing chemotherapy and undergoing radiotherapy significantly associated with sleep disturbances (Costa et al., 2014) in breast cancer women. However, the above-mentioned results from other research studies weren’t entirely consistent with our study. Therefore, future research with efficient sample size and longitudinal design are suggested to not only confirm the preliminary findings but gain a better understanding of risk factors and predictors of poor sleep quality among different treatment status. In conclusion, clinical staff should be aware of the sleep problem derived from patients’ physical and psychological illness, as well as their treatment status in order to prevent further life quality decreasing.