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• W2146228908 abstract "Free AccessWake After Sleep OnsetVagal Regulation, Cortisol, and Sleep Disruption in Women with Metastatic Breast Cancer Oxana Palesh, Ph.D., Jamie M. Zeitzer, Ph.D., Ansgar Conrad, Dipl.-Psych., Janine Giese-Davis, Ph.D., Karen M. Mustian, Ph.D., Varinia Popek, Karen Nga, David Spiegel, M.D. Oxana Palesh, Ph.D. Address correspondence to: Oxana Palesh, Ph.D., Research Assistant Professor of Radiation Oncology, University of Rochester Medical Center, James P. Wilmot Cancer Center, 601 Elmwood Avenue, Box 704, Rochester, NY 14642(585) 273-3998(585) 461-5601 E-mail Address: [email protected] University of Rochester, Wilmot Cancer Center, Rochester, NY Search for more papers by this author , Jamie M. Zeitzer, Ph.D. Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA Search for more papers by this author , Ansgar Conrad, Dipl.-Psych. Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA Search for more papers by this author , Janine Giese-Davis, Ph.D. Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA Search for more papers by this author , Karen M. Mustian, Ph.D. University of Rochester, Wilmot Cancer Center, Rochester, NY Search for more papers by this author , Varinia Popek University of Greifswald, Department of Psychology, Greifswald, Germany Search for more papers by this author , Karen Nga Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA Search for more papers by this author , David Spiegel, M.D. Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA Search for more papers by this author Published Online:October 15, 2008https://doi.org/10.5664/jcsm.27280Cited by:54SectionsAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail ToolsAdd to favoritesDownload CitationsTrack Citations AboutABSTRACTStudy Objectives:To determine the relationship between hypothalamic pituitary axis (HPA) dysregulation, vagal functioning, and sleep problems in women with metastatic breast cancer.Design:Sleep was assessed by means of questionnaires and wrist actigraphy for 3 consecutive nights. The ambulatory, diurnal variation in salivary cortisol levels was measured at 5 time points over 2 days. Vagal regulation was assessed via respiratory sinus arrhythmia (RSATF) during the Trier Social Stress Task.Participants:Ninety-nine women (54.6 ± 9.62 years) with metastatic breast cancer.Results:Longer nocturnal wake episodes (r = 0.21, p = 0.04, N = 91) were associated with a flatter diurnal cortisol slope. Sleep disruption was also associated with diminished RSATF. Higher RSA baseline scores were significantly correlated with higher sleep efficiency (r = 0.39, p = 0.001, N = 68) and correspondingly lower levels of interrupted sleep (waking after sleep onset, WASO; r = −0.38, p = 0.002, N = 68), lower average length of nocturnal wake episodes (r = −0.43, p < 0.001, N = 68), and a lower self-reported number of hours of sleep during a typical night (r = −0.27, p = 0.02, N = 72). Higher RSA AUC was significantly related to higher sleep efficiency (r = 0.45, p < 0.001, N = 64), and a correspondingly lower number of wake episodes (r = −0.27, p = 0.04, N = 64), lower WASO (r = −0.40, p = 0.001, N = 64), and with lower average length of nocturnal wake episodes (r = −0.41, p = 0.001, N = 64). While demographics, disease severity, and psychological variables all explained some portion of the development of sleep disruption, 4 of the 6 sleep parameters examined (sleep efficiency, WASO, mean number of waking episodes, average length of waking episode) were best explained by RSA.Conclusions:These data provide preliminary evidence for an association between disrupted nocturnal sleep and reduced RSA the subsequent day, confirming an association between disrupted nocturnal sleep and flattened diurnal cortisol rhythm in women with metastatic breast cancer. They suggest that the stress-buffering effects of sleep may be associated with improved parasympathetic tone and normalized cortisol patterns during the day.Citation:Palesh O; Zeitzer JM; Conrad A; Giese-Davis J; Mustian KM; Popek V; Nga K; Spiegel D. Vagal regulation, cortisol, and sleep disruption in women with metastatic breast cancer. J Clin Sleep Med 2008;4(5):441–449.INTRODUCTIONSleep disruption is 2 to 3 times more common in cancer patients than in the general population.1,2 In our previous studies of 97 women with metastatic breast cancer,3,4 nearly two-thirds (63%) reported symptoms of disrupted nocturnal sleep. Other studies have found a similar prevalence of disrupted sleep and insomnia in cancer patients5–11 and among breast cancer patients in particular.5,6Disrupted sleep and insomnia in particular are associated with several negative physical and psychiatric consequences in the general population, including fatigue, psychiatric illness (major depression in particular), physical complaints, substance abuse, reduced quality of life, and cognitive imparment.12–19,20 Some data also suggest that sleep loss and/or chronic insomnia may negatively influence cardiac function,21,22 immune function,23 and glucose regulation,24–26 thereby increasing early mortality.27–29 Little is known about insomnia and its consequences in cancer patients, but it would be reasonable to expect that the consequences of insomnia in this population would be similar to or worse than those in the general population. In cancer patients, sleep disturbance may exacerbate concurrent cancer and/or treatment-related symptoms such as fatigue, mood disturbance, and gastrointestinal distress and may lead to reduced quality of life (QOL) and to the development of psychiatric illness and reduced overall health.3,30–33The pathophysiology of sleep disruption is not well understood,34 and the precise physiological pathway for the development of sleep disruption and its relationship with cancer are largely unknown. In the non-cancer population, evidence shows that people with insomnia have an elevated response to stress in general,35,36 and psychiatric disorders linked to sleep disruption and/or hyperarousal, such as major depression, posttraumatic stress disorder, and generalized anxiety disorder, are all known to be associated with hypothalamic-pituitary-adrenal axis (HPA) dysregulation.20,37 Past research has linked insomnia to activation of the stress-response system (notably the HPA axis with its activation measured by an increased production of cortisol38), but whether HPA activation causes insomnia or whether insomnia produces HPA activation is unknown.39Besides HPA dysregulation, sleep disruption has been linked to other physiologic markers including changes in metabolism, muscle tone, and heart rate. Changes in heart rate, specifically respiratory sinus arrhythmia (RSA), can be used as a proxy measurement of general parasympathetic tone.40 Respiratory sinus arrhythmia (RSA) is an indicator of the delicate balance between the normal slowing of heart rate during expiration and the speeding up of heart rate during inspiration. Heart rate and consequently RSA is signaled by centers in the medulla oblongata, specifically the nucleus ambiguus, which directly affects the parasympathetic responses of the nervous system on the heart through the vagus nerve. The vagus nerve slows heart rate during expiration by decreasing the rate of sinoatrial node firing and activating the nucleus ambiguus; however, during inspiration the nucleus accumbens is inhibited and the vagus nerve is not stimulated, allowing heart rate to rise. Given this, RSA is an important marker of parasympathetic tone, and impaired or dysregulated RSA has been implicated in stress-related disorders.RSA is a measurement of the covariation of heart rate with respiration. Heart rate increases during inspiration, when intrathoracic pressure and blood flow to the heart decrease, and decreases during expiration, when pressure and blood flow increase. Diminished RSA has been associated with both worse medical (i.e., cardiac)41 and psychiatric (i.e., depression)42 health. Some preliminary studies suggest that RSA is at least associated and might even be predictive of insomnia in healthy subjects. Irwin and colleagues43 found that RSA correlates with electroencephalographic delta sleep and morning reports of sleep quality, sleepiness, and fatigue in subjects with alcohol dependence. This association between RSA and sleep disruption is illustrated by the findings of El-Sheikh and Buckhalt,44 who reported that children with less vagal regulation during a reaction-time task had poorer self-reported and actigraphy-measured sleep.Evidence suggests that lower RSA and higher cortisol levels are associated with sleep disruption. Examination of endocrine and autonomic activity in cancer patients with insomnia has the potential to shed light not only on cancer-specific insomnia but also on the additive or multiplicative interaction of cancer physiology and insomnia. Thus, measurement of cortisol levels, along with assessment of vagal tone, might help explain the causes of existing sleep disturbances in women with metastatic breast cancer and suggest possible targets for therapeutic intervention.METHODSParticipantsThe inclusion criteria for the study required the presence of metastatic breast cancer or recurrent breast cancer, age ≥ 45 years, score < 70% on the Karnofsky rating, residency in the Greater San Francisco Bay area, and a proficiency in English.A total of 111 participants were eligible and consented to participate in the study out of a pool of 221 women screened. Women were recruited through oncologists at Stanford University Medical Center and in the Bay Area by means of newspaper advertisements and word-of-mouth from subjects and patients. Twenty-five women were not eligible. Eighty-three women were eligible but declined participation; another 2 died before the study began. Of the remaining 111 participants, 5 were too busy to participate, one declined participation, one felt too ill, one had an accident, and 4 were excluded after reporting steroid medications in their baseline medication logs, leaving 99 participants who completed demographic and self-report measures. Out of these patients, 2 provided inadequate biological or saliva samples. Seven participants did not complete actigraphy data, and 31 participants did not participate in the Trier Social Stress Test (TSST) testing or did not provide analyzable data for calculation of the RSA.Participants were excluded from the study if they had active cancers within the past 10 years other than breast cancer, basal cell or squamous cell carcinomas of the skin, or in situ cancer of the cervix. They were also excluded if they had positive supraclavicular lymph nodes as the only metastatic lesion at the time of initial diagnosis. We also excluded patients who had a concurrent medical condition likely to influence short term survival, or who used a corticosteroid within the preceding month Those with a history of major psychiatric disorder for which patient was hospitalized or medicated were also excluded, although patients with mild depression or anxiety not requiring hospitalization or pharmacotherapy were allowed to enter the study.Demographic DataDemographic information and medical history obtained from a brief self-report measure are provided in Table 1. Thirty-nine patients (39.4%) took antidepressant medications in this study. The breakdown of types of antidepressant usage is reported by Spiegel et al.45 and is as follows: 18.2% on SSRIs, 11.1% on SNRIs, 2.0% on tricyclic antidepressants, 1.0% on bupropion, 1.0% on an SNRI/tricyclic combination, 2.0% on an SNRI and bupropion, 1.0% on an SSRI and tricyclic, 2.0% on an SSRI/bupropion combination, and 1.0% on hypericum. Nineteen patients (19.2%) took medication specifically prescribed for treating disrupted sleep during study baseline, and 14 patients were taking medication for sleep during test measurements. Of 19 patients taking medications at baseline, 6 patients were taking benzodiazepines, 6 were taking over-the-counter sleep aids or supplements, 5 were taking hypnotic sleep medications, and the remainder of patients were using antidepressant and prescription antihistamine medications for sleep.Table 1 Descriptive Statistics for Demographic and Medical Variables in Metastatic Breast Cancer Participants (N = 99)Demographic VariableStatisticsAge, mean ± SD (range)54.65 ± 9.62 (36–80)Education, No. (%) Trade or High School3 (3%) Some College33 (33.3%) Bachelor’s Degree20 (20.2%) Some Graduate School9 (9.1%) Advanced Degree34 (34.3%)Race, No. (%) Asian10 (10.1%) Black2 (2.0%) American Indian2 (2.0%) White84 (84.8%) Other/Unknown1 (1.0%)Ethnicity, No (%) Hispanic8 (8.1%)Marital Status, No (%) Married67 (67.7%) Never married7 (7.1%) Divorced/Separated19 (19.2%) Widowed6 (6.1%)Household Income, No (%), $ < 20,0005 (5.1%) 20,000–39,99918 (18.2%) 40,000–59,99911 (11.1%) 60,000–79,99916 (16.2%) 80,000–99,99912 (12.1%) > 100,00027 (27.3%) Don’t know/not reported10 (10.1%)ProceduresWomen in the study collected saliva for cortisol measurement for 2 days, completed questionnaires, wore actigraphs46 to monitor their sleep-wake cycles for 3 days, and participated in the TSST approximately 1–2 weeks after the cortisol baseline collections. The TSST, a standardized social and cognitive stress test, consisted of telling the participants that they would have 5 min to prepare a speech for a job interview and another 5 min to do mental math.47 Baseline measurements of resting RSA were taken prior to beginning of the stress task (See Giese-Davis63 for details of our TSST procedures).The initial autonomic data assessment at the baseline point started at a median time of 6.3 min (from instructions) to a median stop time of 15.5 min (from instructions). The median length of the TSSTs from instructions to 60 min post-assessment was 107 minutes. But RSA during the task (area under the curve or AUC) was only recorded from baseline to 10-min post-assessment. Thus the length of time that the RSA was recorded is 107-6.3-50 = 50.7 minutes.MeasuresDemographic and Medical VariablesWomen completed a brief, self-report measure assessing demographic characteristics, including age, marital status, family size, living circumstances, ethnicity, education, employment, and family income. They also answered questions about history of diagnosis of cancer. Disease and treatment information was extracted from medical records.Perceived Stress Scale (PSS)PSS48 is a measure evaluating perception of stress in the past month. For this project we implemented a version that included 10 items, e.g., “In the last month how often have you…felt difficulties were piling up so high that you could not overcome them?” The measure utilizes a 5-point Likert-type scale: 0 = “Never” to 4 = “Very Often.” A total score is computed by summing ten items.Beck Depression Inventory (BDI)The BDI49 is well-known and widely used measure of depression. BDI-II consists of 21 questions and a response scale ranging from 0 to 3. The BDI has established validity and reliability across multiple studies.The Pain-Rating ScaleThe Pain-rating scale50,51 is a 9-item measure used in our earlier studies of metastatic breast cancer patients. For the purposes of this study we used a question that inquired about ratings of current pain and suffering.The Structured Clinical Interview for DSM-IV (SCID)SCID52 is designed to establish a reliable and valid DSM-IV Axis I diagnosis. The SCID was used to assess whether patients met clinical criteria for a depression diagnosis. For the purposes of this study we created a variable that included those women who were diagnosed via SCID as having depression and those who were also taking antidepressant medications.CortisolFor 2 consecutive days, saliva was collected at waking, 30 min after waking, and at 12:00, 17:00, and 21:00 hours. Patients were given wrist timers to remind them to collect saliva at the required times, and saliva swabs (Sarstedt, Inc., Newton, NC) were collected in electronic bottles (provided by AARDEX Ltd Zug, Switzerland) that marked the times when the bottles were opened. Saliva samples were refrigerated after collection and stored at −70°C within 2 days of collection. Samples were assayed using a luminescence immunoassay (Immuno-Biological Laboratories Inc, Hamburg, Germany). Assay sensitivity was 0.015 μg/dL, and intra-assay variations on low, medium, and high controls were 2.78%, 10.45%, and 4.79% respectively. Inter-assay coefficients of variation for low, medium, and high controls were 10.9%, 10.5%, and 5.5%. Participants were instructed not to eat, drink, smoke, brush their teeth, or use mouthwash 30 min before the saliva collection and to postpone collection if they had mouth wounds. Alcohol consumption was discouraged on the days when saliva samples were collected.Collection and Computation of RSATFPlacement of electrodes and sensors, data recording, and data reduction followed conventions and published guidelines.53 Briefly, cardiopulmonary channels were sampled at 400 Hz using a standard lead II ECG and thoracic and abdominal bellows (Lafayette Instrument, Lafayette, IN) connected to pneumographic transducers (James Long Company, Inc, Caroga Lake, NY). Data were analyzed with MATLAB (Mathworks, Inc., Natick, MA). High frequency (RSA fluctuation, lnHF), low frequency (lnLF), and very low frequency (lnVLF) power of heart period variability was computed as the natural logarithm of the summed power spectral density of RR interval between 0.15–0.5 Hz, 0.07–0.15 Hz, and 0.0033–0.07 Hz respectively. A respiration-controlled transfer function, adjusting the lnHF estimate of RSA for respiratory rate and depth alteration confounds (RSATF), was quantified by fast Fourier transform (FFT) and the averaged periodogram method relating RR interval to lung volume oscillations at the peak respiratory frequency.54 RR interval and tidal volume time series were resampled at 4 Hz and partitioned into 60-s segments, overlapping by 30 sec. Each segment was then linearly detrended and Hanning windowed to remove any transition effects. Zero padding enlarged the segments to 64 sec. FFT was applied to each segment for frequency decomposition. The resulting power spectral density functions for RR intervals and tidal volume were adjusted to account for attenuation produced by the Hanning window. For each segment, the cross-spectral density was calculated by multiplying the square roots of the power spectral densities of both variables at each sample point. The average of the cross-spectral densities was computed for each segment. The ratio of the averaged cross-spectral density and the power spectral density of the tidal volume signal represents the transfer function magnitude. The measure of TF-RSA magnitude was the value of this function at the peak respiratory frequency, which was automatically detected as the greatest local maximum in the 0.13–0.5 Hz tidal volume power spectral density function. Spectral coherence for RSATF was required to be at least 0.5 for the TF-RSA estimate to be valid. The physiological data were reviewed by a senior psychophysiologist blind to patient information. Improbable or inconsistent values prompted reanalysis.In the current study, baseline RSA provides a snapshot of the parasympathetic tone among women with metastatic breast cancer—a chronic stress condition, whereas the RSA in response to the TSST provides a direct assessment of acute stress reactivity--the ability of these women to mount appropriate PNS responses to acute stressors while simultaneously having a chronic stress-inducing illness. The inclusion of both measures is common in studies.Actigraphy Measures of Sleep DisruptionA wrist actigraph (Micro Mini-Motionlogger, Ambulatory Monitoring, Systems, Ardsley, NY) was worn during baseline cortisol collection. An actigraph is capable of detecting arm movement through the use of an accelerometer and represents a useful proxy for detecting sleep and wake cycles.55 Data were stored as 60-s epochs. Data were analyzed using Action 4 (v1.13) and ACT Millenium (beta v3.8.8.9) software (Ambulatory Monitoring, NY). Measures derived from this analysis included duration of time in bed (TIB), latency to sleep onset (SL) from entry into bed, sleep efficiency (SE) calculated as the ratio of time asleep to TIB, number and average length of nocturnal wake episodes (WE), and total duration of wake after sleep onset (WASO).Self-Report Measures of SleepOn the day of their TSST test, patients were asked to complete a brief questionnaire that asked them to report their average number of hours of sleep per night.Data AnalysesCortisol data were log transformed to stabilize variance. Baseline cortisol slope was calculated by regressing cortisol values on time from waking on all points for the 2 days. The waking cortisol was the average of waking levels for 2 days, and the waking rise was the 2-day average of the difference between the cortisol levels at waking and 30 min post-waking. Steeper diurnal cortisol slopes represent cortisol levels that are declining throughout the day as they normally do. Steeper slopes are represented by lower or more negative slope values. Flatter slopes represent cortisol values that are more abnormal, and include cortisol levels that decline slowly, have abnormal peaks in the afternoon or evening, or levels that actually increase throughout the day. These fluctuations are represented by less negative or even positive slope values.56 We report means and standard deviations for actigraphy data. Instead of means and standard deviations for cortisol data, we report cortisol scores at the median (50th percentile) and the interquartile ranges (25th and 75th percentiles) because of non-normal distribution and outliers.Area under the curve (AUC) is a summary measure that is routinely used in research when there are multiple repeated measurements over time. Since we assessed RSA multiple times during the TSST, we decided to use AUC to preserve power and avoid increasing Type I error associated with multiple testing. In our study, a graph of the AUC consists of the area under the RSA values measured over time. To calculate the AUC we used the formula proposed by Pruessner et al.57 We calculated the AUC from 6 summary time points (baseline, anticipation, speech, math, 5-min post-assessment, 10-min post-assessment). There were 3 other time points (paced breathing at 9.0, 11.0 and 15.0 cpm) that were excluded from the AUC calculation. The initial autonomic data assessment at the baseline point started a median time of 6.3 min (from instructions) to a median stop time of 15.5 min (from instructions). The median length of the TSSTs from instructions to 60 min post-assessment was 107 minutes. But RSA was only recorded from baseline to 10-min post-assessment.RSA outliers >2 SD from the group mean that appeared improbable for that individual or measure were eliminated. Less than 1% of data were excluded. RSA data are presented as medians (50th percentile) and interquartile ranges (25th and 75th percentiles). Spearman rank correlations were used to evaluate the associations among sleep variables, cortisol levels, and RSA.Several of our sleep variables were not normally distributed. Specifically, sleep latency, WASO, and average wake episode were positively skewed while sleep efficiency was negatively skewed. We attempted to log-transform our variables, both latency and average wake episodes became more normally distributed while WASO and sleep efficiency remained skewed. We attempted to transform sleep efficiency and WASO using other types of transformations but were unsuccessful. As a result of that we dichotomized those two variables using median split and conducted logistic regressions. Multiple linear regressions were conducted with the other 4 sleep variables.Four linear and 2 logistic regression models were conducted using sleep variables as dependent variables and demographic, disease severity, psychological and physiological variables as independent variables. Since we had an unacceptable ratio of variables to participants we reduced our independent variables. We entered the resulting variables in blocks of 3: demographics, disease severity and physiological and psychological variables. The first block included age, the second block included treatment (radiation, chemotherapy or hormone) and dominant site of metastasis, and the third block included perceived measures of perceived stress, depression, sleep medication, pain baseline cortisol log and RSA AUC. We used the backward method to find the solution with the best predictors.RESULTSEstimates from 2 nights of actigraphy indicate that participants spent 478.5 ± 77.15 minutes (7.98 hours ± 1.29 hours), median = 492 minutes (8.2 hours) (range, 228.7–636.0) in bed, taking an average of 11.50 ± 10.24 minutes to fall asleep, median = 8.67 minutes (range, 0–51.67), and had a wakefulness after sleep onset (WASO) of 71.44 ± 50.34 minutes, median = 55.67 (range, 5.67–225.3), giving a sleep efficiency of 84.5 ± 10.6%, median = 88 (range, 55.3–98.9). Participants had 15 ± 6.6 wake episodes each night, median = 14.5 (range, 2.7–31), each with a duration of 4.81 ± 2.62 minutes, median = 4.16 (range, 1.48–16.6). Self-report indicated a habitual 7.6 ± 1.33 hours of sleep per night, median = 8 (range, 4–12).As seen in Table 3, there were several associations between self-reported number of hours of typical sleep and the actigraphic measure of total number of hours in bed (TIB) during the 2 recording nights. In addition, the self-reported typical sleep length correlated significantly and positively with the number of wake episodes and wake after sleep onset (WASO).Table 2 Descriptive Statistics for Medical Variables in Metastatic Breast Cancer ParticipantsVariableNPercentile25thMedian (50th) or %75thLog cortisol slope (2-day mean)96−0.21−0.16−0.11Waking cortisol (2-day mean)970.420.530.7130 min waking rise in cortisol (2-day mean)97−0.040.210.47RSA baseline720.030.050.08RSA AUC680.130.220.35Disease free interval, months9313.537.085.0Estrogen receptor negative, No. (%)2729.3%Dominant site of metastasis at study entry, No. (%)93Bone21 (22.6%)Chest33 (35.5%)Viscera39 (41.9%)Chemotherapy, No. (%)9380 (86%)Radiation, No. (%)9275 (81.5%)Hormonal therapy, No. (%)9361 (65.6%)Table 3 Spearman rho Intercorrelations Among Sleep Measures in Women with Metastatic Breast CancerMean TotalTime inBed (min)MeanLatency(min)MeanSleepEfficiencyMean Numberof WakeEpisodesMean Wakeafter SleepOnset (min)Average WakeEpisodeperiod (min)Objective (Actiwatch) Mean total time in bed (min)—————— Mean latency (min)0.27**————— Mean sleep efficiency−0.05−0.35**———— Mean number of wake episodes0.38**0.32**−0.69**——— Mean wake after sleep onset (min)0.28**0.39**−0.96**0.75**—— Average wake episode period (min)0.020.25*−0.75**0.170.74**—Self-Report How many hours do you typically sleep in a night?0.63**0.11−0.090.27*0.24*0.08*p < 0.05.**p < 0.01.Sleep Disruption, Demographics, Disease Severity and Psychological VariablesThe correlations are presented in Table 4. TIB correlated negatively with age (r = −0.24, p = 0.02), chemotherapy (r = −0.29, p = 0.006), pain intensity (r = −0.23, p = 0.03) and depression measured by SCID (r = 0.21, p = 0.05). Mean sleep latency was associated with radiation (r = 0.21, p = 0.05), perceived stress scale (r = −0.22, p = 0.04). Mean sleep efficiency was positively associated with dominant site of metastases being chest only vs. bone or viscera (r = 0.27, p = 0.01). WASO was negatively related to metastases site being chest only (r = −0.31, p = 0.003) and positively to hormone therapy (r = 0.24, p = 0.03). Mean number of wake episodes was negatively associated with age (r = −0.23, p = 0.03), metastases site being chest only (r = −0.23, p = 0.03) and positively with medication for sleep (r = 0.26, p = 0.012) and receiving hormone therapy (r = 0.23, p = 0.03). Average wake episode period was only related to dominant site of metastasis and was negatively associated with it (r = −0.28, p = 0.006).Table 4 Spearman rho correlations among sleep measures, demographics, disease severity and psychological and physiological markers in women with metastatic breast cancerTotal Timein BedLatencySleepEfficiencyWASOMean Numberof WakeEpisodesAverageWake EpisodeperiodHours ofSleepLast NightDemographics Age−0.24*−0.080.03−0.07−0.23*0.060.10 Race0.050.08−0.090.140.100.110.12 Marital status−0.070.09−0.130.110.090.04−0.06 Medication for sleep0.100.02−0.120.140.26*−0.02−0.02Disease Severity Dominant Site Chest−0.14−0.170.27**−0.31**−0.23*−0.28**−0.04 Bone−0.030.20−0.130.140.100.08−0.20 Viscera0.160.02−0.160.190.180.190.21 Disease-free interval−0.13−0.040.15−0.18−0.20−0.06−0.06 Chemotherapy−0.29**−0.14−0.120.0400.09−0.14 Radiation−0.080.21*−0.140.100.130.09−0.08 Hormone0.160.20−0.190.24*0.23*0.12−0.08 Estrogen receptor status0.100.18−0.050.070.030.05−0.13Psychological Variables Pain intensity−0.23*−0.020.02−0.08−0.10−0.05−0.04 SCID/Antidepressant0.21*0.05−0.020.070.13−0.040.05 PSS−0.02−0.22*0.06−0.07−0.12−0.04−0.13 BDI0.02−0.07−0.050.05−0.060.11−0.07Physiological Variables 2-day baseline log cortisol slope−0.050.05−0.12−0.120.090.010.21* 2-day cortisol rise 30 min post-waking−0.10−0.10−0.12−0.190.150.040.20 2-day waking cortisol−0.20−0.03−0.080.08−0.12−0.08−0.07 RSA baseline−0.08−0.210.170.39**−0.38**−0.22−0.43** RSA AUC0.07−0.120.31*0.45**−0.40**−0.26*−0.41***p < 0.05**p < 0.01Cortisol Descriptives and Sleep DisruptionCortisol was measured in micrograms per deciliter (μg/dL). On Day 1, wake cortisol was 0.58 ± 0." @default.
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• W2146228908 date "2008-10-15" @default.
• W2146228908 modified "2023-10-06" @default.
• W2146228908 title "Vagal Regulation, Cortisol, and Sleep Disruption in Women with Metastatic Breast Cancer" @default.
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