Sleep Disorders in Breast Cancer Survivors

Support Care Cancer DOI 10.1007/s00520-016-3247-6

ORIGINAL ARTICLE

Sleep disorders in breast cancer survivors

Julie L. Otte1 & Lorie Davis2 & Janet S. Carpenter2 & Connie Krier3 & Todd C. Skaar4 & Kevin L. Rand5 & Michael Weaver6 & Carol Landis7 & Yelena Chernyak8 & Shalini Manchanda9

Received: 9 February 2016 /Accepted: 24 April 2016 # Springer-Verlag Berlin Heidelberg 2016

Abstract Keywords Cancer . Survivor . Sleep . Sleep disorder . Purpose The purpose of this study was to evaluate the feasi- Quality of life bility, acceptability, and initial results of a structured assessment of sleep disorders in breast cancer survivors (BCS). Our goal was to determine whether the assessment could be easily used and whether it would capture problems suggestive of one Introduction or more underlying sleep disorders that require referral to a specialist for diagnostic validation through polysomnography Sleep problems (inadequate sleep duration, poor sleep quality, and appropriate specialty treatment. poor sleep timing, sleep disorders) are important public health Methods A cross-sectional, feasibility study using conve- problems that impact over 70 million persons in the USA and nience sampling. lead to an 11–20 % increase in health care costs [1]. The Results A total of 38 BCS completed the study. Recruitment estimated cost of sleep insufficiency has been estimated to procedures were adequate in finding eligible BCS, however, be over $107.5 billion or more [1]. Sleep problems are highly procedures used to establish possible patterns of sleep disor- predictive of negative health outcomes, specifically, poor ders (e.g., interview) were not feasible for screening for sleep health-related quality of life, fatigue, poor healing, cognitive disorders in the clinical setting due to the time it took to com- dysfunction, lost work productivity, safety issues (e.g., acci- plete each interview. A total of seven sleep disorder categories dents), poor relationships, and increased health care costs were identified in the data with the majority of women having [2–14]. at least one possible sleep disorder. Sleep problems are one of the top five most burdensome Conclusions Study findings suggest that population-based lingering issues in breast cancer survivors (BCS). It is well screening for sleep disorders in clinical practice should be a documented that 67–90 % of BCS report sleep problems [15, priority for BCS reporting chronic sleep problems. 16]. BCS are twice as likely to report sleep problems as

* Julie L. Otte 5 Department of Psychology, Indiana University-Purdue University [email protected] Indianapolis, 402 North Blackford Street, LD 124, Indianapolis, IN 46202, USA 6 1 College of Nursing University of Florida, PO Box 100197, Indiana University School of Nursing, 600 Barnhill Drive NUW401, Gainesville, FL 32610, USA Indianapolis, IN 46202, USA 7 University of Washington School of Nursing, Box 357266, 2 Indiana University School of Nursing, 600 Barnhill Drive NU 366, Seattle, WA 98195, USA Indianapolis, IN 46202, USA 8 Indiana University School of Medicine/IU Health Physicians, 3 IU Simon Cancer Center, 980 W. Walnut St., Indianapolis, IN 46202, Goodman Hall / IU Health Neuroscience Center, 355 W. 16th St. USA Suite 2800, Indianapolis, IN 46202, USA 4 Division of Clinical Pharmacology, Indiana University School of 9 Indiana University School of Medicine, 714 N. Senate Ave Suite 120, Medicine, Indianapolis, IN, USA Indianapolis, IN 46202, USA Support Care Cancer women without cancer [17, 18]. African American BCS are at time of study recruitment and enrollment; (9) were 1–10 years an even higher risk for sleep problems and are twice as likely post-completion of surgery, radiation, chemotherapy, and/or to report poor sleep quality [15]. Sleep problems are a long- trastuzumab therapy (endocrine therapy was allowed); (10) term issue for BCS, commonly experienced for as many as reported having sleep problems for ≥3 nights per week in 10 years post-treatment [15]. the past month, (11) had Pittsburgh Sleep Quality Index global Single- or multi-item scales are widely used in research and scores of ≥5; (12) were willing to maintain current sleep prac- clinical practice to assess and classify broad symptoms of poor tices until the in-person study visit was completed; and (13) sleep [12, 19, 20]. However, these measures neglect the im- were not currently performing night-shift work (night shift portant issue of assessing specific types of sleep disorders and was defined as working a shift that crosses midnight). mainly focus on insomnia symptoms (e.g., trouble falling To eliminate potential confounding factors, BCS with asleep and staying asleep, nighttime disturbances) that are known major psychiatric illness (e.g., schizophrenia, bipolar common to several different sleep disorders. Identifying sleep disorder, major anxiety, or major depression requiring hospi- disorders is very important because different disorders require talization in the past 3 months) were excluded because pre- different interventions even if symptoms overlap. Most inter- existing psychiatric illness is a strong predictor of sleep prob- vention studies in BCS have tested the use of cognitive–be- lems (50–80 % prediction rate) [15, 22]. BCS with controlled havioral therapies to target undefined subtypes of insomnia, depression were eligible and were carefully assessed. The [16, 21] without screening out other sleep disorders that re- overall accrual goal was 40 BCS with 20 being African quire additional disorder specific therapies. Because the focus American. has been on symptoms of poor sleep, BCS may be receiving treatments for sleep problems that are inappropriate or inade- Study procedures quate. Identifying the presence of possible sleep disorders is requisite for appropriate referral and treatment. A cross-sectional, feasibility study was conducted that incor- To our knowledge, no studies have conducted an in-depth porated questionnaires, interviews, and serum blood draws. evaluation of sleep problems in BCS to ascertain if self- Two methods were used for study recruitment. First, targeted reported symptoms suggest possible underlying sleep disor- advertisements were used to recruit local BCS. BCS were able ders [21]. The purpose of this study was to evaluate the feasi- to self-refer to the study by telephoning the project office. This bility, acceptability, and initial results of a structured assess- occurred if women: (1) called or e-mailed in response to an ment of sleep disorders in BCS. Our goal was to determine advertisement placed with various breast cancer survivor sup- whether the assessment could be easily used and whether it port groups, (2) called in response to an online advertisement would capture problems suggestive of one or more underlying through the Indiana Center for Translational Sciences Institute sleep disorders that require referral to a specialist for diagnos- (CTSI) INresearch voluntary registry, or (3) called in response tic validation through polysomnography and appropriate spe- to local cancer care clinics or community support groups cialty treatment. where the study’s recruitment brochure was available for pick-up, posted, and/or study contact information was shared with BCS during routine communications. Second, in-person Methods clinic recruitment was performed. Trained recruiters screened BCS at two Midwest university breast cancer clinics and in- Sample and setting troduced the study with the aid of a recruitment brochure and followed the same study procedures as the telephone-based A convenience sample of BCSs was recruited from local ad- screening to assess eligibility. Names of eligible and interested vertisements and an outpatient cancer clinic located in the BCS were forwarded to the project office for initiation of Midwest between September 2013 and May 2014. Prior to study procedures. All research staff and recruiters were trained recruitment, all study procedures were approved by the local in all aspects of the study. institutional review board and cancer center scientific review Eligible and interested women who agreed to be in the committee. study were provided a packet that included two consent and Eligible subjects: (1) were at least 21 years of age; (2) were HIPAA authorization forms, a medication list to complete, and willing and able to provide informed consent and protected directions to the in-person clinic visit either in person (clinic health information (PHI) authorization; (3) were able to read, recruitment) or by mail (self-referred by telephone). Once the write, and speak English; (4) were in good general health; (5) signed consent form and medication list was completed and were willing to participate in one clinic visit; (6) had a non- returned (via mail), the participant received a telephone call to metastatic, breast cancer diagnosis (node involvement was schedule her for the single, in-person visit. If study materials acceptable); (7) had no other cancer (basal cell skin cancer were not returned, reminder phone calls were made to deter- was allowed); (8) were disease free for breast cancer at the mine continued interest in the study. If no materials were Support Care Cancer received after 6 weeks, the subject was considered not inter- score of 27 [28, 29]. Higher scores represent increased sever- ested in participating and no further reminder calls were made. ity of depression. Scores have been matched with treatment Research staff reminded subjects of their study visit by re- actions that should be considered by clinicians. The PHQ-9 contacting them the day before the scheduled appointment. has been validated and widely used as a brief diagnostic and Participants were reminded of the date, time, location, and severity measure of depression in cancer and non-cancer forms to bring with them for their in-person study visit. populations. Eligible participants provided informed consent and authorization to use protected health information by a trained re- Pre-clinic visit search assistant prior to the start of the in-person study visits. All other collection of questionnaire and serum data oc- Medication list: A study-specific form was mailed to all inter- curred at the in-person clinic visit. At the in-person clinic visit, ested participants and used to document medications taken at the following occurred. Physical measurements including the present time and in the past 3 months. This included pre- blood pressure, pulse, height, and weight were obtained by scription drugs, inhalers, injections, creams, over-the-counter trained study staff to describe the participants. Blood samples medications, vitamins, herbs, and other supplements. Subjects were obtained in the outpatient research center by a trained compiled the list at home and then brought the list to the study nurse for hemoglobin, ferritin, and thyroid-stimulating hor- visit for review by the research staff. This list was used to mone. Samples were analyzed by the university hospital lab- facilitate specific questions in the Duke Structured Interview oratory. Semi-structured, audiotaped interviews focusing on for Sleep Disorders questionnaire. sleep problems were conducted by two trained research staff. In-person clinic visit Data entry and management Demographic questionnaire: This is a standard questionnaire Collected data were entered into the REDCap (Research to record basic demographic information. Information on this Electronic Data Capture) database system. Entered data were form includes age, race, ethnicity, marital status, employment examined post-export to verify that the data had been properly status, socio-economic status, education, health provider con- exported and to identify any outliers or errors. Audiotaped tact information, menopausal status, and history of cigarette interviews were stored on a secure university computer server smoking. only accessible by study team members. These tapes were Disease and treatment information: Disease and treatment used to clarify any interview responses by participants. information was obtained by self-report. Information included date of diagnosis, stage of disease, and dates and types of Measures treatments including surgery, chemotherapy, radiation, selec- tive estrogen receptor modulators, and aromatase inhibitors. Screening for eligibility The Self-Administered Comorbidity Questionnaire (SCQ): The SCQ is a measure of self-reported co-morbidities. The Pittsburgh Sleep Quality Index (PSQI): The PSQI was de- questionnaire consists of 12 medical conditions with Byes^ signed for assessment of sleep quality [23]. The tool contains or B no^ responses regarding the presence of a disease state. 19 items that produce a global sleep quality score based on If Byes^ responses are selected, two additional questions ask if seven component scores: sleep quality, sleep latency, sleep the participant is receiving treatment (yes/no) and if the con- duration, habitual sleep efficiency, sleep disturbance, use of dition limits the individual’s activities (yes/no). A maximum sleep medications, and daytime dysfunction using varying re- of 3 points is given to those conditions that are present, being sponse categories. Responses are based on the prior month’s treated, and limiting current activities. Acceptable reliability habits. Scores > 5 indicate poor sleep quality. Psychometric has been established in cancer patients (Cronbach’sal- properties of the PSQI such as content validity and internal pha = 0.94) [30]. We modified the SCQ instrument by adding consistency reliability have been widely supported in a variety items for fibromyalgia, lupus, thyroid disease, seizures, head- of populations, [24–26] including healthy individuals (n =52; aches, hot flashes, and cancer. We deleted the Bother^ open- Cronbach’salpha=0.83)[23]andBCS(n = 102; Cronbach’s ended items to minimize issues in analyzing open-ended re- alpha = 0.80) [27]. We used the established cut-off score to sponses. We also collected year of co-morbid diagnosis, verify eligibility. which was evaluated independently and not included in the Patient Health Questionnaire (PHQ-9): The PHQ-9 is a 9- scoring. item scale based on the Diagnostic and Statistical Manual of Generalized Anxiety Disorder (GAD-7): The GAD-7 [31] Mental Disorders, fourth edition (DSM-IV) symptoms of ma- is a seven-item screening and severity measure validated for jor depressive disorder. Responses range from Bnot at all^ =0 the four most common anxiety disorders in primary care: gen- to Bnearly every day^ = 3, resulting in a maximum summed eralized anxiety, panic, social anxiety, and posttraumatic stress Support Care Cancer disorder. The reliability and validity of the GAD-7 were contributing factors of sleep problems found in the interviews. established in a study of more than 2,700 general medical Hemoglobin from the complete blood count (CBC) was used outpatients [31, 32]. Scores on the GAD-7 can range from 0 to evaluate for anemia, ferritin was used to evaluate for iron to 21, with cut points of 5, 10, and 15 representing mild, deficiency anemia that can been attributed to symptoms of moderate, and severe anxiety symptoms, respectively. restless leg syndrome. Thyroid-stimulating hormone (TSH) Hot Flash-Related Daily Interference Scale (HFRDIS): The was evaluated to assess for the presence of insomnia symp- HFRDIS is a 10-item scale assessing how much hot flashes toms that can be related thyroid dysfunction. interfere with nine daily activities and overall quality of life Acceptability Questionnaire: The questionnaire was a 25- (QOL) [33]. Validity, reliability, and sensitivity to change over item investigator-designed questionnaire that contained items time have been established in BCS and healthy women [33]. taken from a questionnaire we used in our prior study [38]. Participants rate the degree to which hot flashes have inter- Women are asked to read each of the 25 statements and choose fered with each of the activities during the previous four a response ranging from 5 (strongly agree)to1( strongly weeks using a 0 (Bdo not interfere^)to10(Bcompletely inter- disagree) with 3 being neutral. We used individual item re- fere^) scale. A total score is computed by summing the items. sponse scores for the analysis in this study. Higher scores indicate greater interference by hot flashes and, thus, greater impact on QOL. Data analysis Symptom Experience Report (SER): Other possible cancer and non-cancer-related symptoms were assessed using a Sample characteristics (demographics, disease and treatment, symptom checklist created by combining items from the depression, anxiety, hot flashes) were quantified using de- Greene Menopausal Index, the Menopause Rating Scale, scriptive statistics appropriate for level of measurement (e.g., and the National Surgical Adjuvant Breast and Bowel means, standard deviations, frequencies, and percentages). Project (NSABP) symptom checklist. Menopausal symptoms To evaluate the feasibility of study procedures of the one- are embedded within a larger checklist to prevent response time, in-person structured assessment of sleep disorders, the bias. Respondents are asked to circle Byes^ or Bno^ to indicate following were described: (1) number of local eligible BCS whether they have experienced the symptom during the past who mailed or e-mailed using recruitment methods (local ad- week. If the symptom was present, they are then asked to rate vertising, CTSI, in-person recruitment); (2) number of BCS severity using a 0-to-4-point scale. We have previously used who self-referred from the three recruitment methods in an 8- versions of this scale and reported Cronbach’salphasof>.80 month time frame; (3) number of eligible, ineligible, and infor symptom prevalence and symptom severity [34]. terested women; (4) the refusal rate and drop-out rate before PEG 3-Item Pain Scale: Pain was assessed using a three- the in-person interview; and (5) number of women whose item pain scale created from the Brief Pain Inventory [35]. The sleep problems could not be formally classified into specific abbreviated scale includes three items with response selec- sleep disorders using study questionnaires and interviews. tions of 0–10 (0 being no pain, 10 being high pain and high Descriptive statistics such as frequencies, percentages, means, interference) during the past week. The total score is the aver- and ranges were used to evaluate feasibility of the study age of the item responses (range 0–10) [35]. procedures. Duke Structured Interview for Sleep Disorders (DSISD): The acceptability of the proposed study procedures by BCS The DSISD was also used to define classifications of sleep who completed the study was evaluated using an investigator- disorders [36]. The DSISD is based on the DSM-IV-TR and generated questionnaire. Frequencies and percentages were ICSD-2 classification systems. Five modules are assessed: used to describe the distribution of ratings for acceptability insomnia disorders, other sleep disorders (environment-in- of procedures using items contained within the Acceptability duced and short sleeper), sleep disorders associated with ex- Questionnaire. cessive daytime sleepiness and hypersomnia, circadian Frequency percentages were used to describe distribution rhythm disorders, and parasomnias. The insomnia module is of symptoms suggestive of sleep disorders. To ensure the ac- further divided into subtypes by evaluating mental disorders, curacy of the sleep assessment findings, the study team medical disorders, substance abuse, circadian disorders, and worked collectively to ensure accurate classification of the other insomnia subtypes. Discriminant validity and inter-rater appropriate sleep disorder(s). All sleep assessment summaries reliability have been established for insomnia subtypes (k for each subject were reviewed to rectify any inconclusive range = 0.42–0.71), [36] and the scale has been used in BCS findings. Specifically, each individual’s results were quanti- [37]. Although polysomnography has been used in conjunc- fied into specific types of sleep disorders on the DSISD, and tion with the DSISD, sensitivity and specificity have not been the lab results from the serum lab values were reviewed. The published for this instrument. results of DSISD results for each subject were categorized Serum blood draw: Blood analyses were conducted on all using the four modules assessed (insomnia disorders, sleep participants for abnormal chemistry values that could be disorders associated with excessive daytime sleepiness and Support Care Cancer hypersomnia, circadian rhythm disorders, and parasomnias). Given the lack of empirical effect size information on The insomnia module of the DSISD was further divided into which to base sample size to provide suitable power and the subtypes by evaluating mental disorders, medical disorders, descriptive nature of the aims of this pilot feasibility study, substance abuse, circadian disorders, and other insomnia sub- adequacy of the sample size was judged based on literature types. The third step was to evaluate the serum lab results to reports and recommendations for pilot study sample size. The rule out anemia, iron deficiency, and thyroid dysfunction, all 38 observations available for this study is consistent with lit- of which supported possible disorders of restless leg syn- erature reports of a median pilot or feasibility study sample drome or insomnia related to a medical condition. All data size of 30 [40] and recommendations for minimum sample sources were analyzed on an individual basis and then cate- size of 24 [41]. gorized into ICSD-2 categories and entered into the study As shown in Table 1, BCS included in this study had a database since that is the classification most recommended mean of 59 years of age and most (95 %) were non- for use in sleep disorders (this study was completed prior to Hispanic or Latino. There were similar proportions of Black the introduction of the ICSD-3 and therefore analyzed accord- or African American (47 %; n = 18) and White (45 %; n =17) ing to those parameters) [39]. participants. A majority (58 %; n = 22) were single, never smoked (84 %; n = 32), had at least a high school education (87 %; n = 33), and had last menstrual cycle more than 1 year Results ago, and on average had a body mass index (BMI) of 31.1 (SD = 6.4). Sample Women were stage 0–III at the time of enrollment with a mean 6.3 years (SD = 3.21) from diagnosis of their breast can- A total of 144 women self-referred to the study or were cer. The majority had received surgery (97 %), chemotherapy approached for participation in the study (Fig. 1). Of the 120 (50 %), and radiotherapy (66 %). The BCS were currently women who were interested in hearing about the study, 57 using or had past use of tamoxifen (50 %) or an aromatase were eligible for the study (47.5 %). Major reasons for ineli- inhibitor (50 %). They reported a mean of 14.2 symptoms gibility were not being a full year from the end of treatment (SD = 6.4). The top 10 reported symptoms were being tired and having a secondary cancer. Only 6 of 144 screened BCS (90 %), joint pain (87 %), hot flashes (81 %), forgetfulness did not have global sleep quality scores high enough for in- (61 %), numbness and tingling of the hands and feet (58 %), clusion (PSQI > 5). Five women were lost to contact after the irritable or nervous (58 %), worry about their body (53 %), dry initial screen with unknown eligibility. A total of 52 women mouth (53 %), and vaginal dryness (50 %).The majority of the scheduled for study visits, with 38 completing the in-person BCS had at least one additional co-morbid condition other clinic evaluations (26 % withdrawal rate). The large with- than cancer (M = 3.7; SD = 1.8), the most prevalent of which drawal rate was primarily due to loss of contact and no longer were hypertension (58 %), headaches (39 %), arthritis (31 %), being interested or too busy to participate in the study. and diabetes (18 %). The majority of the BCS had high global sleep quality scores (M = 11.9; SD = 3.0), low anxiety scores (M =3.3; 144 Assessed for Eligibility SD = 2.8), low depression scores (M = 3.6; SD = 3.1), and high hot flash interference scores (M = 25.5; SD = 21.7). Pain interference was low for all three item responses (Table 1). Since 87 Excluded the study had equal racial group numbers, we analyzed sleep • 63 Not Eligible outcomes to determine trends between the groups. The mean • 24 Not Interested global sleep quality scores were similar between African • 5 Unable to American (M = 12.1; SD 2.9) and Caucasian (M =11.6; determine/lost to follow- SD = 3.2) BCS. Hot flash interference was moderate and highly variable among participants (M = 25.5; SD = 21.7). 52 Eligible Feasibility and acceptability

24 Withdrew before study visit The recruitment procedures used for this study were effective in identifying close to the desired number of local BCS who were having poor sleep through several recruitment methods 38 Consented and Completed (community flyers, clinic recruitment) over the narrow 8- month time frame we established for enrollment. Fig. 1 Study accrual flow diagram Requirement inquiries by women included 27 self-referrals Support Care Cancer

Table 1 Sample description and symptom report disease (n = 10), not having global sleep quality scores over Demographic characteristic Mean (SD) Range 5(n = 1), and working night shift (n = 1). Five women were eligible and interested but lost to follow-up for consent. Of the Age (years) 58.7 (9.2) 43.0–81.0 52 eligible BCS for the study, 14 lost interest after the initial Body mass index 31.1 (6.4) 20.6–52.1 screening call because of the estimated time it would take for Symptom Experience Report (SER) 14.2 (6.4) 3.0–26.0 the in-person clinic visit. Comorbidity Questionnaire (SCQ) 3.7 (1.8) 1.0–7.0 The procedures used to establish possible patterns of sleep Pittsburgh Sleep Quality Global 12.0 (3.0) 6.0–19.0 disorders (e.g., interview) were not feasible for integration into Patient Health Questionnaire (PHQ-9) 3.6 (3.1) 0.0–11.0 practice for oncology providers. In-person study visits were Generalized Anxiety Scale (GAD) 3.3 (2.8) 0.0–10.0 lengthy, taking a mean of 2.1 hours (SD = 55 min) (range 1– Hot Flash Daily Interference Scalea (HFDIS) 25.5 (21.7) 0.0–75.0 3 h 20 min). The in-person clinic time reflects the total time for Pain in the past month 3.8 (2.7) 0.0–10.0 all in-person data collection (questionnaires, biometrics of Pain interference with life 2.6 (2.7) 0.0–10.0 height/weight, and serum blood draw). Although the team Pain interference with activity 2.7 (3.0) 0.0–10.0 did not anticipate that the lengthy assessment would be trans- %(n) latable, our experience verified that a shorter set of question- Ethnicity naires is needed in order to be applicable to clinical practice. Not Hispanic or Latino origin 94.7 (36) The study procedures and measures used to evaluate sleep Hispanic or Latino origin 5.3 (2) problems in the BCS were found to be acceptable, with the Race exception of one item. Response rates exceeding 80 % were Black or African American 47.4 (18) used as a benchmark to establish acceptability of items. The White or Caucasian 44.7 (17) item regarding the amount of time it took to screen partici- Other or do not wish to report 7.8 (3) pants for eligibility was rated slightly below the acceptable Marital status benchmark (74 %) by BCS so it was not characterized as Single 57.9 (22) unacceptable due to the small sample size. Ninety-eight per- cent of participants found the use of electronic data collection Married or partnered 42.1 (16) to be acceptable, 89 % participants rated the location of the Employment interview acceptable, 100 % of participants rated the interview Full-time 31.6 (12) session overall to be acceptable. Not employed 50 (19) Part-time 18.4 (7) Symptoms suggestive of sleep disorders Education Some high school 13.1 (5) There were seven sleep disorder categories represented in the High school degree 47.4 (18) data generated by the clinical interviews (Table 2). The ma- Undergraduate degree 18.4 (7) jority of women had more than one possible disorder, with Graduate degree 21.1 (8) insomnia and circadian rhythm disorders being the two most Smoking status frequent potential disorders. Interestingly, 79 % of the BCS I have never smoked 84.2 (32) had high symptom burden potentially related to sleep apnea. Current smoker 15.8 (6) Other major categories represented included two movement Menstrual cycle disorders (restless leg syndrome [61 %; n = 23] and periodic Last menstrual cycle > 1 year 94.7 (36) limb movement [5 %; n = 2]), circadian rhythm disorder ≤ Last menstrual cycle 1 year 5.3 (2) (84 %; n = 32), parasomnia (57 %; n = 22), hypersomnia a Only 31 reported hot flashes and completed the scale (32 %; n = 12), and isolated symptoms (3 %; n =1).Further SD standard deviation subsets of specific types are also presented in Table 2.The laboratory values were abnormal in a small proportion of these BCS. The most frequent abnormal values included low hemo- and 117 women approached in two local breast cancer clinics. globin and high ferritin values (see Table 3). Although infor- Only 24 women (16.7 %) refused screening, although 63 mative, the values did not add additional information to the women were not eligible for the study. The reasons for ineli- assessment findings. gibility included not being 1 year out from cancer treatment The mean number of sleep disorder classifications per sub- (n = 20), having a history of a second type of cancer (n =15), ject was 4.16 (1.3), with a range 1–6. The mean number of being over 10 years from the end of treatment (n =10),not possible sleep disorders was similar between African having sleep problems ≥3 nights per week for the past month American (M = 4.2; SD = 1.2) and Caucasian BCS (M =4.1; or more (n = 5), having active breast cancer or metastatic SD = 1.3) BCS. Since this was a feasibility study, we were Support Care Cancer

Table 2 Suggestive sleep disorders Our first major finding was validation that population- Disorder classification % (n) based screening for sleep disorders needs to be given serious consideration. We had no difficulty identifying BCS with Chronic insomnia 98 (37) chronic sleep problems, and the absence of sleep problems Insomnia subtypes was a relatively uncommon reason for exclusion. We did iden- Psychophysical (racing mind) 86.8 (33) tify eligibility criteria that hindered women from participating Inadequate sleep hygiene 86.8 (33) such as end dates for initial cancer treatment. The rationale for Medical condition 60.5 (23) that inclusion criterion was that it has been reported that sleep Medication 60.5 (23) quality can fluctuate during the first year after completion of Environmental issues 65.8 (25) surgery, chemotherapy, and radiotherapy. The investigative Mental condition 55.3 (21) team was initially looking for those with continued sleep prob- Sleep-related breathing (sleep apnea) 78.9 (30) lems after that first year. However, in moving forward with Sleep-related movement this line of research, it will be important to reduce that time Restless leg syndrome 60.5 (23) frame to expand generalizability of findings throughout the Periodic limb movement 5.3 (2) entire cancer trajectory. Acceptability of incorporating these Circadian rhythm 84.2 (32) interview methods for sleep disorders was further endorsed by Hypersomnia 31.6 (12) the finding that women were supportive of a relatively lengthy Parasomnia 57.1 (22) assessment of their sleep problems. BCS stated they were Parasomnia subtypes willing and wanted referrals to a sleep specialist and desired Nightmares 18.4 (7) non-pharmacological treatment options to alleviate their sleep Teeth grinding (bruxism) 26.3 (10) problems. Groaning 7.9 (3) To conduct population-based screening, a more stream- Hallucinations 10.5 (4) lined assessment is needed. Our comprehensive assessment Confusional arousals 15.8 (6) with serum testing was too lengthy to use in busy clinical practices and length. In addition, based on our screening time Leg cramps 39.5 (15) acceptability rates, improvements can be made to further re- Isolated symptoms 2.63 (1) duce the perceived time to screen for initial eligibility for this More than one disorder 97.4 (37) type of study. A clinical decision tool is needed that will screen BCS for sleep disorders to ensure that their sleep problems are appropriately managed in clinical practice. To not powered to look at statistically significant differences for achieve this, oncology providers need a comprehensive this comparison. No BCS had symptoms of sleep problems screening and personalized referral algorithm that includes that could not be classified into a disorder. Inter-rater reliabil- standardized, psychometrically sound screening question- ity for the randomly selected files was 99 %. naires and suggested referral recommendations for further di- agnostics and treatment. Once the comprehensive screen and referral structure is complete, implementation strategies can Discussion be used to change practice. The second major finding is support for our hypothesis that The purpose of this study was to evaluate the feasibility, ac- BCS may have one or more sleep disorders underlying symp- ceptability, and initial results of a structured assessment of toms of poor sleep with matching co-morbid conditions that sleep disorders in BCS. The two major findings are discussed are typical of chronic sleep problems. In fact, all but one of our in detail below. participants had symptoms suggesting more than one sleep disorder. Our findings are similar to the few studies that have examined specific sleep disorders. One study found that 40 % Table 3 Percentage of abnormal lab values of BCS had symptoms of both generic insomnia and a sleep- related movement disorder [6]. Another recent study found Value % (n) high prevalence of periodic limb movements in BCS [42]. Low hemoglobin 18.4 (7) Although sleep apnea has long been assumed to be uncom- High ferritin 26.3 (10) mon in women (<9 %), one study of women found that 53 % Low ferritin 2.6 (1) met minimum criteria for possible sleep apnea [43]. In studies High thyroid-stimulating hormone 2.6 (1) of midlife women without cancer, the estimated prevalence Low thyroid-stimulating hormone 5.3 (2) rates of sleep disorders vary greatly, and the fact that there is no clear understanding of specific types of sleep disorders in Support Care Cancer that population making it difficult to compare findings with 9. Koopman C, Nouriani B, Erickson V, Anupindi R, Butler LD, BCS [44]. This lack of prevalence data can be attributed to the Bachmann MH, Sephton SE, Spiegel D (2002) Sleep disturbances in women with metastatic breast cancer. Breast J 8(6):362–370 fact that women are disproportionately included in sleep re- 10. Lee K, Cho M, Miaskowski C, Dodd M (2004) Impaired sleep and search and often underdiagnosed in the clinical setting [45]. rhythms in persons with cancer. Sleep Med Rev 8(3):199–212 This study had both strengths and limitations. It was the 11. Roscoe JA, Morrow GR, Hickok JT, Bushunow P, Matteson S, first study to attempt to categorize symptoms of poor sleep Rakita D, Andrews PL (2002) Temporal interrelationships among fatigue, circadian rhythm and depression in breast cancer patients into possible sleep disorders. Our study sample was diverse, undergoing chemotherapy treatment. Support Care Cancer 10(4): which increases the understanding of sleep findings a non- 329–336 Caucasian population. However, our study was limited to a 12. Savard J, Morin CM (2001) Insomnia in the context of cancer: a convenience sample BCS and findings may not generalize to review of a neglected problem. J Clin Oncol 19(3):895–908 other female cancer groups or to men with cancer. The types 13. Deimling GT, Kahana B, Bowman KF, Schaefer ML (2002) Cancer survivorship and psychological distress in later life. of sleep disorders we identified were not validated through Psychooncology 11(6):479–494 polysomnography, although the instrument we used has pre- 14. Ganz PA, Desmond KA, Leedham B, Rowland JH, Meyerowitz viously been found to be sensitive and specific for identifying BE, Belin TR (2002) Quality of life in long-term, disease-free sur- sleep disorders [36]. The types of sleep disorders present vivors of breast cancer: a follow-up study. J Natl Cancer Inst 94(1): 39–49 would need to be verified by more extensive evaluation; how- 15. 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