Patients

The study was approved by the institutional review board. Forty-five BCS were screened for treatment for sleep disturbances and hot flashes during a 12-month period. Of those screened for the study, 8 were self-referrals responding to a mailing and 37 from physician clinic referrals. 35 of the 45women screen were not eligible or interested for the following reasons; (1) lived to far from the university for weekly visits (n=10), (2) did not have sleep disturbances and hot flashes (n=4), (3) were not 3 months post-treatment (n=3), (4) had prior acupuncture treatment (n=3), (5) had a current psychiatric disorder (n=3), (6) were not post-menopausal (n= 1), (7) did not want treatment for sleep and/or hot flashes (n=1), (8) were too busy to commit to the 8 weekly visits (n=9), and (9) was participating in another clinical trial (n=1). 10 BCS consented to the study.

Women were eligible if they (1) were least 18 years of age, (2) reported sleep disturbances over the past month, (3) reported daily hot flashes and frequent sleep disturbances with desire for treatment, (4) were peri- or post-menopausal, (5) agreed not to change sleep or hot flash medication use or dosages during the course of this study, (6) lived within a 100-mile radius of the study site, (7) were English-speaking, (8) had a known diagnosis of non-metastatic breast cancer and no history of other cancers, and (9) were at least 3 months post-completion of surgery, radiation, and/or chemotherapy. Women were excluded if (1) they had known psychiatric or cognitive disorders, (2) had a prior personal history of acupuncture use, or (3) were participating in other clinical trials.

Design

The study used a single group, non-randomized, quasi-experimental design.

This was an 8-week study (see Table 1). Each subject selected one of four participating certified community acupuncture providers for three acupuncture treatments over a 2-week period. Demographic and disease and treatment questionnaires were administered during the first week of the baseline assessment. Outcome expectancy and credibility were assessed after the first treatment had been completed (treatment week 1) and acceptability at the first follow-up visit. Physiologic monitoring using wrist actigraphy and hot flash monitoring occurred for 2 weeks prior to acupuncture as a determinant of baseline, as well as during the 2 weeks of acupuncture, and during two follow-up weeks (weeks 5, 8 of study). Additionally, self-reported symptom data were obtained using validated questionnaires at baseline, during treatment, and during each follow-up week.

Table 1

Study Schema

Acupuncture sessions

The optimal acupuncture point regimen is unknown for either sleep disturbances or hot flashes. Acupuncture points used during treatment were dependent on the individual subjects’ TCM diagnoses as determined by the licensed acupuncturists. However, each of the contracted licensed acupuncturists agreed to use the same tailored treatment regimen for all three treatments for each individual subject. The protocol gave subjects the option to have treatments from one of four licensed acupuncturists who were located at two separate clinics and held a National Certification Commission for Acupuncture and Oriental Medicine certification and who provided appropriate therapy based on their experience and Traditional Chinese Medicine (TCM) diagnosis. All of the acupuncturists were Caucasian-American, had at least 6 years of patient experience (M=11.33, SD=8.39), had a master’s degree in Oriental Medicine from an accredited American school, and were members of the local and national professional organization for acupuncturists. None of the acupuncturists practiced under a different health care role such as nursing,

Measures

Measures are described below. Monitoring using wrist actigraphy and sternal skin conductance was performed as described below. Each of these devices required that data be downloaded every 7 days. Women were required to visit the onsite clinic each week to return study materials and have their monitors programmed for the subsequent week. Data were downloaded by trained study staff and stored in a secure, encrypted database in de-identified format on a secure server.

Outcome expectancy-credibility and acceptability of treatment

The 6-item Devilly and Borkovec Outcome Expectancy/Credibility Questionnaire was used to assess outcome expectancy and treatment credibility at the on-treatment assessment.60 Three questions assess outcome expectancy and three assess treatment credibility. For outcome expectancy items participants are asked to indicate how much they think treatment will help improve symptoms using a 0% to 100% scale, how much they feel treatment helped improve symptoms using a 0% to 100% scale, and how much they feel treatment reduced symptoms using response options from 1 (not at all) to 5 (somewhat) to 9 (very much). For treatment credibility items, participants are asked to indicate how logical the treatment was, how successfully they think treatment reduced their symptoms, and how confident they are in recommending the treatment to a friend. Each question for treatment credibility is rated on a 1 to 9 scale. Responses to items on each subscale are standardized and summed to create a total subscale score. Higher scores indicate greater belief that the treatment would provide beneficial results (outcome expectancy) or greater belief in the credibility of the treatment (credibility). In studies of men and women, for expectancy Cronbach’s alphas were .79 to .90 and one-week test-retest reliability was r=.82 (p < .001). Cronbach’s alphas for credibility ranged from .81 to .86 with one-week test-retest reliability of r=.75 (p<.001).60 For this study, Cronbach’s alpha was 0.67 for the outcome expectancy subscale and .96 for the treatment credibility subscale.

The Acceptability Scale was administered at weeks 4 and 8 of follow-up. It is a 10-item investigator-designed questionnaire that contains 10 items taken from a questionnaire used in a prior study evaluating hot flash interventions.59 Women are asked to read each of 10 statements and choose a response ranging from 5 (strongly agree) to 1 (strongly disagree) with 3 being neutral. For example, women rated their level of agreement or disagreement with statements such as “I enjoyed the acupuncture sessions” (see Table 3). Frequencies of individual item responses were reported in the analysis of this study; a total score was not calculated. Since frequency of individual items are reported psychometrics were not appropriate for this questionnaire.

Table 3

Acceptability Scale Results

Statistical Analysis

Due to the feasibility nature of this study, we planned to accrue 12 subjects to generate hypotheses for further study. According to Julious,61 12 subjects is roughly the minimum sample size needed for a pilot study using continuous outcomes (e.g., number of hot flashes and sleep disturbance measures).

Demographic and breast cancer treatment information was analyzed with descriptive statistics and frequencies using SPSS 17.0 (Chicago, IL). Questionnaires and objective measures were evaluated for missing data points. There were no missing questionnaire data. The two baseline assessments were averaged for all outcome variables to facilitate statistical analyses.

Because of the number and complexity of acupuncture points used for treatments, descriptive statistics were used to determine the mean number of points administered per treatment per participant and reported side effects. Frequencies were used to determine the number of different acupuncture points and placement location. Paired t tests were used to determine if the mean number of acupuncture points received per treatment per participant changed over time. The data was reviewed and the assumptions of paired t tests were met. Alpha was set at p<0.05 for all analyses. With conducting multiple t tests, the overall probability of a Type I error is typically > 5%. The authors’ note that this inherent risk for a Type I error did not justify an adjustment in alpha given the exploratory nature of study, limited power due to the small sample size, and need for confirmation in future studies. This should be considered by the reader when interpreting the findings of the study.

Descriptive statistics and frequencies were used to evaluate outcome expectancy, treatment credibility, and acceptability of treatment. Chi square tests of independence were used to compare individual treatment acceptability questionnaire responses between the two follow-up time points.

Descriptive statistics were used to report mean global sleep and mean hot flash interference scores over time. For objective measures, sleep disturbances were evaluated using the average of common sleep variables: 1) wake after sleep onset (WASO) in minutes, 2) total sleep time (TST) in minutes, 3) sleep efficiency (range from 0% to 100%), and 4) number of nighttime awakenings. Due to missing data for sleep monitoring, three consecutive days were used for analysis. The 3-day time frame could not include the first day of recording and had to have all hours of the day represented with a complete sleep log. Averages were then calculated based on the software output with additional visual inspection to ensure accuracy. Physiologic hot flash frequency was calculated as the total number of hot flashes per 24-hour day.

Lastly, to determine patterns of change in sleep disturbances and hot flashes across the 8 time points, continuous outcome variables were evaluated using paired t tests (SPSS 17.0). This test was selected since it is more powerful than other non-parametric tests for small sample sizes.

Subjects

Ten women were enrolled to participate in the 8-week study. Of the 10 BCS that completed baseline, 2 withdrew after the last baseline assessment due to time commitments that prohibited them from completing weekly study visits. The remaining 8 BCS completed all time points. The BCS averaged 53 years (SD=10.07), all were Caucasian (100%), and most were college educated (63%), married or partnered (88%), working full or part-time (88%), and not Hispanic or Latino (88%). The majority (63%) did not have non-cancer related co-morbidities. Mean time from diagnosis was 6.75 years (SD=2.60), and mean body mass index was 23.32 (SD=4.37). Most had stage 0–1 breast cancer (57%) and all had received some type of cancer treatment such as surgery, chemotherapy, or radiotherapy (100%). The majority of BCS were not taking a hormone modulator at the time of this study (38%).

Patterns of acupuncture point use

A total of 38 different acupoints was used for treatment. The mean number of treatment points administered per subject per treatment was not significantly different among the three treatments (t= −0.42 to −0.55; p=0.60–0.69) or among the four different therapists. The majority of treatment points were located on the Lu (lung) meridian. The second and third most common points were the Sp (spleen) and Li (large intestine) meridians. Lastly, Ki (kidney), HT (heart), and Ren vessel meridians had similar patterns of usage. The most common acupoints used are listed in Table 2. The location and number of acupuncture points per participant remained constant over the 3 treatments (treatment 1- M=10.13, SD=2.03; treatment 2- M=10.50; SD=2.93; treatment 3- M=10.38, SD=2.39). There were no reported side effects for any subjects. The sessions were mainly conducted at one clinic (n=6).

Table 2

Description of Most Commonly Used Acupuncture points

Outcome expectancy, credibility, and acceptability of treatment

BCS reported high outcome expectancy, that is, they believed that acupuncture would help improve their symptoms (M=21.37, SD=4.07). BCS also rated that acupuncture treatment as having high credibility (M=21.00, SD=3.42). BCS reported that acupuncture was acceptable and helped with symptoms of sleep disturbances and hot flashes, and that the sessions were enjoyable, not painful, and comfortable (Table 3). Women did not think the treatment sessions took too much time out of the day. They found it easy to make treatment appointments, stated that the acupuncturists seemed to want to help diminish symptoms, and would not have preferred to have a different acupuncturist perform the treatments. Overall, the women would recommend acupuncture to a friend and would not have preferred a different treatment to help with symptoms.

Patterns of symptom change

As shown in Table 4, at baseline women reported poor global sleep scores (M=9.25, SD=4.10) and, as objectively measured, had less than the recommended total sleep time of 7–9 hours of sleep per night62(M=6.84, SD=0.73), took almost 18 minutes to fall asleep, and experienced nearly 47 minutes of wakefulness after sleep onset. The average number of nighttime awakenings was 32 (SD=10.22), with an average sleep efficiency of 83%. The mean number of objective hot flashes was 12.58 (SD=13.41) per 24 hours, and on average hot flash daily interference was mild (M=3.60, SD=2.69).

Table 4

Patterns of Symptom Change Over Time

Three significant patterns of symptom change were noted. First, average sleep latency significantly increased after the acupuncture treatment stopped from study week 4 to week 8 (t=−2.57, p=0.04). Second, although marginally significant, there was a decrease in time spent awake after sleep onset from baseline to time 8 (t=2.53, p=0.05). Lastly, the average number of hot flashes recorded by the sternal monitor significantly decreased from baseline to time 4 (t=2.95, p=0.02). No other significant changes over time were found (Table 4).

Limitations

There were several limitations of this study. First, the small sample size limited our ability to determine a meaningful effect size. Second, the number of treatments per subject was limited to 3 over 2 weeks, which is fewer than most acupuncture studies. Third, there is a need to assess treatment fidelity in a larger study. Fourth, the sessions were mainly conducted at one clinic with one acupuncturist limiting our understanding of treatment patterns. Finally, this was a homogeneous, highly-motivated sample of BCS therefore the generalizability of results is limited. These limitations should be considered when interpreting the findings of this study.

Implications for Clinical Nurse Specialists

The use of complementary therapy provides non-pharmacological treatment options for symptom management in cancer patients. Serving as patient advocates, Clinical Nurse Specialists (CNS) integrate existing evidence into clinical practice and provide cost-effective treatment for both inpatients and outpatients who have sleep disturbances and hot flashes. One study showed that nurses’ personal knowledge, experience, and attitudes relative to complementary therapy can influence their use of such treatments in critically ill patients.66 Communication between nurses and other caregivers is important to ensure the appropriate use of acupuncture for symptom management. CNSs should work in tandem with acupuncturists by being sure the latter are informed at every point about relevant patient status variables so they can select the most appropriate points and length of treatment for individual patients. The CNS also needs to identify any barriers to this type of treatment in partnership with the patient, other health care providers, and family members but recognize that this might not be a desirable treatment option for all patients.67 The current study has added to our knowledge about the role of acupuncture as an option for highly motivated patients seeking symptom management and suggests how the CNS could conduct future studies.

Future research

Our goal is to build on these study results by conducting a large-scale randomized controlled clinical trial using a larger number of community acupuncturists. Future studies should allow the treating acupuncturists to continue to select appropriate points for the patient to provide a more holistic approach that adheres to the traditional Chinese approach to treatment. Studies should 1) continue to evaluate specific points used to determine patterns of effective treatment points, 2) use fewer assessment visits to reduce the need for weekly travel to the study site and possibly increase interest in participation, and 3) increase the number of treatment sessions to allow for possible greater treatment efficacy over time.

The authors would like to acknowledge support from statisticians Jingwei Wu and Michael Weaver; research nurses Jill Deluca and Kathy Tutor; licensed acupuncturists Mitch Harris, Erica Harris, Shane Haggard, and Jennifer Meador-Stone; and editor Phyllis Dexter.

Dr. Julie L. Otte is an Assistant Professor at the Indiana University School of Nursing. She was a doctoral student and post-doctoral fellow at the time this project was implemented.

Dr. Janet S. Carpenter is a Professor in the Indiana University School of Nursing. She was an Associate Professor at Indiana University during this project.

Ms. Xin Zhong is a Clinical Nurse Researcher at the Indiana University School of Medicine. She was a master’s student at the time this project was implemented.

Dr. Peter A. S. Johnstone is a Professor at the Indiana University School of Medicine and Director of the Department of Radiation Oncology.

Disclosure of Funding: National Institutes of Health KL2 RR025760, National Cancer Institute R25 CA117865.