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Sleep/Wake Patterns of Individuals With Advanced Cancer Measured by Ambulatory Polysomnography

Kathy P. Parker, Donald L. Bliwise, Maria Ribeiro, Sanjay R. Jain, Catherine I. Vena, Mary Kay Kohles-Baker, Andre Rogatko, Zhiheng Xu, Wayne B. Harris

From the Nell Hodgson Woodruff School of Nursing; Department of Neurology; Winship Cancer Institute, Emory University; Veterans Affairs Medical Center, Atlanta, GA; and the Beth Israel Deaconess Medical Center, Harvard University, Boston, MA

Corresponding author: Kathy P. Parker, PhD, RN, AAN, Nell Hodgson Woodruff School of Nursing, Emory University, 1520 Clifton Road, Atlanta, GA 30322-4207; e-mail: kpark04{at}emory.edu

	ABSTRACT

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Purpose Sleep/wake disturbances are prevalent in patients with advanced cancer, but 24-hour polysomnography (PSG) examinations of these patterns have not been undertaken. The purpose of this study was to describe these sleep/wake patterns using continuous PSG and to explore relationships with selected demographic and clinical variables.

Patients and Methods The sample included patients with advanced cancer (solid tumors); those with neurologic disorders or psychosis, substance abuse, or brain metastasis were excluded. The final sample included 114 participants with a mean age of 51.1 years (± 9.1 years). Participants underwent continuous, ambulatory PSG for 42 hours in their home environments. Standard PSG measures were calculated. Analysis included data from 2 nights and the intervening day. Descriptive statistics were used to summarize sleep/wake parameters of the average of the 2 nights and the intervening day. Nonparametric analyses were used to detect differences and relationships among the variables.

Results Compared with normative data, participants had reduced quantity and quality of nocturnal sleep and episodes of sleep scattered throughout the day. Increased daytime sleep was negatively associated with several key parameters of nocturnal sleep quantity and quality. Women, whites, and those who were married/partnered and had more education had better nocturnal sleep. Cancer type and selected medications may be risk factors for disturbed sleep and waking.

Conclusion Participants experienced severe difficulty with "state maintenance", or the ability to maintain both the sleep and waking states. Research designed to identify the etiology of these problems is needed to develop effective interventions.

	INTRODUCTION

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Sleep/wake disturbances are common in cancer patients.^1-3 Studies examining subjective reports reveal a pattern of difficulty getting to sleep, early morning awakenings, prolonged nocturnal waking periods, and unrefreshing sleep.^4-7 Daytime sleepiness is also prevalent.^4-6 Studies using actigraphy, a measure that estimates sleep parameters, have provided important insights into the nature of these complaints.^8,9 Ancoli-Israel et al¹⁰ demonstrated that women with breast cancer had disturbed sleep and those with delayed circadian rhythms had more daytime dysfunction and fatigue. Berger et al⁸ found that fatigue was associated with a greater number of nighttime awakenings, was greater during chemotherapy and negatively correlated with activity.^8,11 Although limited in scope and sample size, polysomnography (PSG) evaluations of nocturnal sleep reveal altered sleep architecture.^12-14 Daytime sleep/wake patterns have never been examined using PSG.

Adequate sleep quality and daytime alertness are necessary for health and well-being,^15-23 and patients with cancer report increased distress in association with these problems.^1,6,24-26 Sleep/wake disturbances may also enhance other symptoms such as pain, depression, and fatigue.^27-30 Minimal information is available regarding these problems using PSG (the gold standard of measurement), information that is needed to explore the etiology of these problems and guide the development of interventions. Thus, the purpose of this hypothesis-generating analysis was to describe the sleep/wake patterns of patients with advanced cancer using continuous ambulatory PSG. Relationships among nocturnal and daytime sleep measures, and differences based on demographic and clinical variables were also examined.

	PATIENTS AND METHODS

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Sample
Patients with advanced solid tumor malignancy (stages III and IV) were screened from medical oncology clinics within a large university health care system. Individuals were excluded for a wide variety of reasons including: early-stage disease, age younger than 30 or older than 75 years, Karnofsky performance score (KPS) of less than 50 (inability to perform most activities of daily living), inability to read and write, known brain metastasis or other neurologic disorders, history of substance abuse predating the cancer, history of previously diagnosed sleep apnea, recent hospital discharge, and inability to schedule in-home PSG until at least 5 days subsequent to the most recent chemotherapy and/or radiotherapy or 1 week after hospitalization. No attempt was made to systematically track a primary basis for exclusion among those 1,500 patients screened. Five participants declined for reasons such as the time commitment, work scheduling difficulties, inconvenience associated with equipment placement, and conflicts with vacations. The final sample included 114 participants.

Design
The institutional review board approved the study. Demographic and clinical data, medications, and laboratory information were obtained from screening medical records. The project manager, a registered nurse, completed the KPS. Potential participants underwent an interview to determine interest in participation and confirm eligibility. Within a 1- to 2-week period after consent, all participants underwent continuous ambulatory PSG over a 42-hour period of time in their home setting and completed a diary on which they recorded nocturnal bedtime (lights out) and morning wake time (lights on).

Ambulatory PSG
Recordings were made using an Embla A10 Recorder (Embla Systems, Broomfield, CO) initialized by Somnologica Science software. The electrodes were connected to an Embla SX Proxy that was strapped to a participant's chest. The Embla Recorder was stored in a small backpack worn or carried by the participant. Participants were able to perform usual activities (exception bathing or showering). The data were stored on a 768-MB flash card and imported into the Somnologica Science software. The quality of the recordings was excellent.

A standard sleep montage of electroencephalography (C3/A2-C4/A1 and O2/C3-O1/C4), monopolar left and right electrooculography (EOG) referenced to the opposite mastoid, and surface mentalis electromyography was used. Sleep stages were manually scored by the same certified PSG technician following standard criteria.³¹ Nocturnal PSG sleep measures calculated included total sleep time (TST, minutes); sleep efficiency (TST/nocturnal sleep period x 100; %); the percentage of TST spent in stages 1, 2, 3, and 4 (3 and 4 are referred to as slow-wave sleep [SWS]), and rapid eye movement (REM) sleep; latency to the first 60 seconds of continuous sleep (sleep latency, minutes), and the latency to the first epoch of REM sleep (REM latency, minutes). A brief arousal index (changes in electroencephalography frequency lasting 3 to 14 seconds; events/per hour of sleep)³² and an index of awakenings lasting at least 60 seconds (events/per hour of the nocturnal recording period) were also calculated. Daytime PSG sleep variables included total sleep time, percentage of time spent in sleep stages, and an index of awakenings lasting at least 60 seconds (a proxy variable estimating the number of times per hour participants had at least one epoch of sleep). To decrease participant burden, respiratory/limb movement data were not collected.

Participants were connected to the PSG recorder before 6:00 PM their first night and the recording ended between 12:00 and 2:00 PM the day after the second night (based on participant wake-up time, convenience, and scheduling). With the exception of one participant (battery failure after 29 hours), all recordings included at least 42 hours of continuous PSG. A home visit was made by the project manager in the morning and afternoon of each day to ensure integrity of the equipment. The recordings yielded two nocturnal sleep periods (as measured from reported "lights out" to "lights on") and one daytime period (as measured from reported "lights on" to "lights off").

Data Analysis
Descriptive statistics were used to summarize data. There were no significant differences between nocturnal PSG variables for the first and second nights, so the data were averaged. Nonparametric analyses were used because most variables did not meet the assumptions necessary for use of parametric procedures. The Mann-Whitney U test was used to detect two group differences, and the Kruskal-Wallis test was used when more than two groups were compared (followed by post hoc comparisons and Bonferroni correction of the significance level). The Spearman rho (r_s) correlation procedure was used to detect significant relationships between variables. A histogram showing the patterns of sleep, sleep stages, and waking on an hourly basis across the 42-hour period was also generated. SPSS (SPSS Inc, Chicago, IL) and SAS (SAS Institute, Cary, NC) statistical packages were used. The level of significance was set at = .05.

	RESULTS

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Demographic and Clinical Features of the Sample
Demographic and clinical features of the sample appear in Tables 1 and 2. The mean age of the sample was 55.2 years (± 9.1 years) with approximately equal sex distribution. Approximately 60% of the participants were nonwhite (African American/other) while 40% were white. A majority of the participants had breast, lung, colorectal, and head and neck cancer. Other cancer types included ovarian, prostate, liver, pancreatic, thyroid, and renal. The mean KPS was 76.3 (± 11.0). Laboratory parameters of the sample were within normal limits, demonstrating an absence of metabolic disorders that could affect sleep parameters. The medications for which participants had prescriptions and reported taking appear in Table 3; only those taken by at least 10% of the sample (n = 11) were included.

View this table: [in this window] [in a new window]   Table 3. Medications for Which Participants Had an Active Prescription Reported by 10% of the Sample (n 11)

View larger version (41K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 1. Graph of polysomnographic measures of sleep stages and wakefulness in 1-hour bins. During the nights, participants were awake 25% of the time. Most sleep was stage 1 and 2 non–rapid eye movement (NREM). During the daytime, sleep ranged from 5% to 15% per hour with REM intrusion. MT, movement time; REM, rapid-eye-movement sleep; S3, NREM slow-wave sleep; S2, NREM sleep; S1, NREM stage 1 sleep; wake, waking.

Nocturnal and Daytime Sleep/Waking Measures and Demographic Variables
Because sleep-related demographic differences have been previously described in the normal population and healthy insomniacs, analyses were conducted to determine whether nocturnal PSG sleep measures differed by the demographic features (Table 5). Although sleep was disturbed in the entire sample, compared with men, women had a higher sleep efficiency, less %stage 1, and more %REM and %SWS. Women also had a lower brief arousals index. In summary, the overall quality of nocturnal sleep was better in women than in men.

During the day, whites had significantly less %REM sleep than did nonwhites. Those participants with more than a high school education had less %REM sleep compared with those with less education. The Kruskal-Wallis test revealed a significant difference in daytime %REM sleep according to marital status. Multiple comparisons demonstrated that the only significant difference among groups was that married/partnered participants had less %REM sleep during the day than did single participants.

Nocturnal and Daytime Sleep/Waking Measures and Clinical Variables
Because sleep-related differences have been reported,^6,14 analyses were conducted to determine whether PSG measures differed by cancer type (Table 5). The Kruskal-Wallis test revealed selected significant differences among cancer groups. After multiple comparisons were conducted, it was noted that participants with lung cancer had more nocturnal %stage 1 and a higher index of awakenings lasting at least 60 seconds. There were no significant differences in daytime PSG parameters and cancer type.

Analyses were also conducted to identify possible effects of medications on PSG measures (Table 5). Those participants taking opioids had increased nocturnal %stage 2, whereas those taking serotonin reuptake inhibitors (SSRIs) had increased total sleep time and an increased REM latency. Participants taking antineoplastics had increased sleep efficiency and %SWS and decreased daytime %REM. Beta blockers significantly decreased nocturnal sleep efficiency and total sleep times and increased daytime %REM sleep, whereas benzodiazepines increased nocturnal total sleep time and decreased daytime %REM sleep.

	DISCUSSION

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Most studies conducted with cancer patients have employed either subjective reports^4,26 and/or activity/rest measures (actigraphy)^8,10,11,37 to assess sleep and waking. This is the first study to our knowledge to examine sleep/wake patterns in patients with advanced cancer via continuous PSG, but in-home ambulatory PSG has been used successfully in several field studies and yielded good quality recordings, albeit for shorter periods of time (overnight).^38,39 We confirmed previous reports, using actigraphy, that participants had reduced quantity and quality of nocturnal sleep.^8,10,11,37 We also documented the amount and type of the nocturnal and daytime sleep obtained and poor daytime wake continuity. A major finding was that participants experienced difficulty with state maintenance, the ability to maintain both the sleep and waking states. The key features of such dysregulation likely involve homeostatic and circadian process alterations (described in the Two-Process Model of Sleep Regulation^40,41). Although our study was designed neither to examine nor to test the actions and interactions between these processes, the data obtained afforded the opportunity to discuss the results within a widely accepted conceptual context for understanding sleep.

The homeostatic process, a key indicator of which is SWS, is determined by the amount of prior sleep and waking and reflects the need for sleep that builds across the day. SWS, which occurs in greatest amounts in the first third of the night, is thought to dissipate sleep need. Participants experienced an almost total absence of SWS. Numerous factors could explain this observation such as the age of the participants (%SWS normally decreases with age⁴²), medications such a benzodiazepines,⁴² opioids,^43,44 and those for pain³⁰ and depression and anxiety.^1,3 These factors may have contributed to sleep fragmentation, preventing sleep cycle progression and the attainment of SWS. The lack of SWS may have prevented the dissipation of sleep need and increased daytime sleep tendency.

The circadian process, markers of which are the rhythms of body temperature (which is coupled with the timing and amount of REM sleep), melatonin, and cortisol production, determines periods of high and low sleep propensity. Normally, short episodes of REM occur early in the night and increase in length as the night progresses and body temperature decreases.^42,45 Although %REM was slightly decreased, we observed this pattern. We also noted that REM occurred during the day, especially in the midafternoon (Fig 1). This rarely occurs in healthy individuals and, when it does, is often associated with sleep deprivation⁴⁶ and sleep disorders such as narcolepsy⁴⁷ and sleep apnea.⁴⁸ Several studies have noted that patients with cancer have blunted or erratic circadian patterns as measured by actigraphy^10,49 and other key markers of the circadian system such as cortisol^50-52 and melatonin^52,53 secretion. Our findings support these reports.

Homeostatic and circadian processes interact to regulate sleep and waking. As the homeostatic drive for sleep increases, the circadian process decreases sleep propensity and increases the ability to stay awake during the day. Throughout the course of the night, when the homeostatic drive for sleep dissipates, the circadian process increases sleep propensity permitting a longer, more consolidated nocturnal sleep period.^41,54 Two major findings suggest that the interaction between these two processes is altered in patients with advanced cancer. First, participants had reduced nocturnal total sleep time and sleep efficiency, being awake approximately 25% of the time during the night and asleep for up to 20% during the day. Second, increased daytime sleep was negatively associated with several markers of nocturnal sleep quality. The poor nocturnal sleep continuity and increased daytime sleep suggest that the homeostatic need for sleep was not dissipated at night and/or the circadian ability to decrease sleep propensity during the day and increase sleep propensity at night was blunted.

Several demographic variables related to sleep disturbances in the general population showed similar relationships in this sample. Although all participants slept poorly, women slept better than men.⁵⁵ Whites had more nocturnal sleep time, a higher sleep efficiency, and less daytime %REM sleep than did nonwhites. Race has been associated with poor sleep,⁵⁶ possibly because of race-related depression and anxiety⁵⁷ or an increased prevalence of sleep apnea.⁵⁸ Participants who were married or living with someone and had more education experienced less sleep/wake disturbance.⁵⁹ These factors may play a role in determining lifestyle and/or psychological health that can affect sleep and waking.

Our results suggest that patients with lung cancer may be at greater risk that those with breast cancer. However, all participants with breast cancer were women, whereas the lung cancer group was composed of both sexes. Because women slept better than the men in this sample, sex may have had a confounding effect.

The nocturnal sleep of the sample was characterized by decreased total sleep time and %SWS, a minor decrease in %REM sleep, and increased %stage 2 and REM latency. Daytime sleep was notable for an increased number of brief sleep episodes and an abnormal distribution of REM sleep. Medications may contribute to these observations. Opioids tend to suppress %SWS and %REM and increase %stage 2.^43,44,60 Participants taking SSRIs had relatively large increases in nocturnal total sleep time, an observation in sharp contrast to several other reports.^60,61 Improvement of underlying depression, which can increase nocturnal total sleep time, may be one explanation. The well-characterized lengthening of the REM latency with SSRI use was observed,^60,61 and may have resulted in daytime REM sleep rebound. Participants taking antineoplastic agents had more nocturnal total sleep time, increased nocturnal sleep efficiency, and decreased daytime REM sleep. Increased cytokine production in response to treatment (or the cancer itself) can increase nocturnal sleep time,⁶² and possibly resulted in decreased daytime REM intrusion. Beta blockers had the classically described effects on sleep (decreased in nocturnal total sleep time and sleep efficiency).^60,63,64 Similarly, benzodiazepines increased nocturnal total sleep time and decreased %REM, as previously reported.⁶⁰

The etiology of the state maintenance abnormalities is unclear but likely related to disrupted sleep regulatory processes.³ Numerous factors can adversely affect these processes, including demographics, lifestyle, environment, and psychological status.^1,3 Medications, specifically opioids and SSRIs, can alter both SWS and REM sleep, key markers of homeostatic and circadian regulation.^44,65,66 Pain and fatigue, changes in activity and hormone production, type of cancer, and cancer treatment may also be important.^1,3 Research is also needed to determine whether the state instability observed may be related to sleep disorders common in this age group, such as sleep apnea and periodic limb movement disorder.

The study is limited because the variables listed above were not controlled in the analyses, and only active participants were included (KPS 50). Nonetheless, the results provide the first comprehensive description of sleep/wake patterns of patients with advanced cancer using PSG to our knowledge, and highlight the importance of work designed to identify the etiology of these problems, especially related to those factors that negatively affect sleep regulatory processes. This information is necessary to develop effective interventions that consolidate both states and improve clinical outcomes.

	AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

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Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a "U" are those for which no compensation was received; those relationships marked with a "C" were compensated. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.

Employment or Leadership Position: None Consultant or Advisory Role: Kathy P. Parker, Sanofi-aventis (C); Donald L. Bliwise, Takeda (C), Neurocare (C), Stanford School of Sleep Medicine (C) Stock Ownership: None Honoraria: Kathy P. Parker, Sanofi-aventis; Donald L. Bliwise, Takeda, Sleep Medicine Education Initiative, Boehringer-Ingelhein; Sanjay R. Jain, Sanofi-aventis, Amgen Research Funding: Kathy P. Parker, National Institue of Nursing Research, Emory University Woodruff Fund Expert Testimony: None Other Remuneration: None

	AUTHOR CONTRIBUTIONS

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Conception and design: Kathy P. Parker, Donald L. Bliwise, Maria Ribeiro, Sanjay R. Jain, Catherine I. Vena, Mary Kay Kohles-Baker, Wayne B. Harris

Financial support: Kathy P. Parker

Administrative support: Mary Kay Kohles-Baker, Wayne B. Harris

Provision of study materials or patients: Kathy P. Parker, Maria Ribeiro, Sanjay R. Jain, Mary Kay Kohles-Baker, Wayne B. Harris

Collection and assembly of data: Kathy P. Parker

Data analysis and interpretation: Kathy P. Parker, Donald L. Bliwise, Andre Rogatko, Zhiheng Xu

Manuscript writing: Kathy P. Parker, Donald L. Bliwise, Mary Kay Kohles-Baker

Final approval of manuscript: Kathy P. Parker, Donald L. Bliwise, Maria Ribeiro, Sanjay R. Jain, Catherine I. Vena, Mary Kay Kohles-Baker, Andre Rogatko, Zhiheng Xu, Wayne B. Harris

	NOTES

 
Supported by Grants No. RO1 NR008124 and P20 NR07798 from the National Institute of Nursing Research.

Presented in part at the 9th Annual Research Conference of the Oncology Nursing Society, February 8-10, 2007, Hollywood, CA; the 42nd Annual Meeting of the American Society of Clinical Oncology, June 2-6, 2006, Atlanta, GA; 41st Annual Meeting of the American Society of Clinical Oncology, May 13-17, 2005, Orlando, FL; and the 19th Annual Meeting of the Associated Professional Sleep Societies, June 18-23, 2005, Denver, CO.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted April 19, 2007; accepted January 8, 2008.

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