Patients and Settings
This longitudinal study was part of a larger study that evaluated neuropathic pain and lymphedema in a sample of women who underwent breast cancer surgery. Patients were recruited from breast care centers located in a comprehensive cancer center, two public hospitals, and four community practices. Women were eligible to participate if they: were >18 years of age; underwent breast cancer surgery on one breast; were able to read, write, and understand English; and provided written informed consent. Women were excluded if they were having bilateral breast cancer surgery and/or had distant metastasis at the time of diagnosis. A total of 516 patients were approached and 410 enrolled in the study (response rate of 79.4%). For this analysis, questionnaire booklets were completed by 396 patients. The major reasons for refusal were: too busy, overwhelmed with the cancer diagnosis, or insufficient time available to do the baseline assessment prior to surgery.
At enrollment, demographic and clinical information were obtained. Medical records were reviewed for disease and treatment information. At each subsequent assessment, patients provided information on current treatments for breast cancer.
Functional status was evaluated using the Karnofsky Performance Status (KPS) score. Patients rated their functional status using the KPS scale that ranged from 30 (“I feel severely disabled and need to be hospitalized”) to 100 (“I feel normal; I have no complaints or symptoms.” The KPS scale has well-established validity and reliability.24
The Self-Administered Comorbidity Questionnaire (SCQ) consists of 13 common medical conditions that were simplified into language that could be understood without any prior medical knowledge. Patients indicated if they had the condition using a dichotomous “yes/no” format. If they indicated that they had a condition, they were asked if they received treatment for it (yes/no; proxy for disease severity) and if it limited their activities (yes/no; indication of functional limitations). Patients could add two additional conditions not listed on the instrument. For each condition, patients could receive a maximum of three points. Because 13 defined medical conditions are listed, the maximum score is 39 points. The SCQ has well-established validity and reliability and has been used in studies of patients with a variety of chronic conditions.25,26
The 21-item General Sleep Disturbance Scale (GSDS) was used to evaluate overall sleep disturbance over the past week. Each item is rated on a scale that ranges from 0 (never) to 7 (everyday). The GSDS comprises seven subscales (i.e., quality of sleep, quantity of sleep, sleep onset latency, mid-sleep awakenings, early awakenings, medications for sleep, DS) that can range from 0 to 7 and a total score that can range from 0 (no disturbance) to 147 (extreme sleep disturbance). A total GSDS score of ≥43 indicates a clinically meaningful level of sleep disturbance.27
The GSDS has high internal consistency reliability among oncology samples.28,29
Cronbach’s alpha for the GSDS total score was 0.86. The total GSDS score and the subscale score for DS were used in these analyses.
DS was evaluated using the seven items from the GSDS that make up the DS subscale.30
This subscale ascertains the level of DS by asking questions about ability to stay awake and scheduled and unscheduled napping during the day. Additional questions evaluate irritability, alertness, and sleepiness during the daytime hours. Scores can range from 0 to 7 and represent the number of days a week a patient finds that DS is problematic. A score ≥3 indicates a clinically meaningful level of disturbance.
The Center for Epidemiological Studies-Depression Scale (CES-D) consists of 20 items selected to represent the major symptoms in the clinical syndrome of depression. Scores can range from 0 to 60, with scores of ≥16 indicating the need for individuals to seek clinical evaluation for major depression. The CES-D has well-established concurrent and construct validity.31,32
Cronbach’s alpha for the CES-D was 0.90.
The Spielberger State-Trait Anxiety Inventories (STAI-T and STAI-S) contain 20 items each that are rated from 1 to 4. Scores are summed and can range from 20 to 80. Higher scores indicate greater anxiety. Cutoff scores of ≥31.8 and ≥32.2 indicate high levels of trait and state anxiety, respectively. The STAI-T and STAI-S inventories have well-established criterion and construct validity and internal consistency reliability coefficients.33,34
Cronbach’s alphas for the STAI-T and STAI-S were 0.88 and 0.95, respectively.
The Lee Fatigue Scale (LFS) comprises 18 items designed to assess physical
fatigue and energy.35
Each item is rated on a 0 (not at all) to 10 (extremely) numeric rating scale (NRS). Higher scores indicate greater fatigue severity and higher levels of energy. Cutoff scores of ≥4.4 and ≤4.8 indicate higher levels of fatigue and lower levels of energy, respectively. The LFS has well-established validity and reliability with oncology patients.28,36
Cronbach’s alphas for the fatigue and energy subscales were 0.96 and 0.93, respectively.
The Attentional Function Index (AFI) consists of 16-items designed to measure attentional
fatigue in patients with cancer. Each item is rated on a 0 to 10 NRS. A mean AFI score was calculated, with higher scores indicating greater capacity to direct attention and, therefore, lower levels of attentional fatigue.37
Based on a previously conducted analysis of the frequency distributions of the AFI scores,38
attentional fatigue can be grouped into categories of functional status (i.e., patients who score <5.0 functioning poorly and experiencing high levels of attentional fatigue, patients who score 5.0 to 7.5 functioning moderately well and experiencing moderate levels of attentional fatigue, patients who score >7.5 functioning well and experiencing low levels of attentional fatigue). The AFI has established reliability and validity.37
Cronbach’s alpha for the AFI was 0.95.
The occurrence of breast pain prior to surgery was determined by asking “Are you experiencing pain in your affected breast?” If women responded yes, they rated the severity of their average and worst pain using a 0 (no pain) to 10 (worst pain imaginable) NRS.39
Women were asked how many days a week and how many hours a day they experienced significant pain (i.e., How many days out of a typical week do you currently have pain in your affected breast that interferes with your mood and/or activities? On those days when you have pain in your affected breast, how many hours of the day does it currently last?).
The occurrence of hot flashes prior to surgery was determined by asking “Did you have hot flashes in the last week?” If women responded yes, they rated the severity and distress associated with the hot flashes on a 0 (none and not at all distressing, respectively) to 10 (intolerable and very distressing, respectively) NRS.
The Quality of Life-Patient Version (QOL-PV) is a valid and reliable 41-item instrument that measures four dimensions of QOL in cancer patients (i.e., physical well-being, psychological well-being, spiritual well-being, social well-being) as well as a total QOL score.40,41
Cronbach’s alpha for the QOL-PV total score was 0.86.
Individual items from the QOL-PV were used to assess a number of psychosocial adjustment characteristics (i.e., coping, distress, fear, control). One item asked patients to rate their difficulty coping as a result of cancer and its treatment. Another item asked patients to rate the distress associated with their initial cancer diagnosis. Fear was assessed with two questions, one regarding fear of future diagnostic tests and another regarding fear of developing a second cancer. Finally, one question asked the patient to rate her level of control over things in her life. Each item was rated using a 0 to 10 NRS, with higher scores indicating a better QOL.
The Committee on Human Research at the University of California, San Francisco and the Institutional Review Boards at each of the study sites approved the study. During the patient’s preoperative visit, a staff member explained the study to the patient. For those women who were willing to participate, the staff member introduced the patient to the research nurse who met with the women, determined eligibility, and obtained written informed consent prior to surgery. After providing consent, patients completed the baseline study questionnaires (Assessment 0). Following the completion of these questionnaires, the research nurse obtained the patient’s height and weight. Patients were contacted two weeks after surgery to schedule the first postoperative visit. The research nurse met with the patients in their home, the Clinical Research Center, or the clinic at one, two, three, four, five and six months after surgery. During each study visit, the women completed the study instruments.
Descriptive statistics and frequency distributions were generated on the sample characteristics, baseline symptom severity scores, and QOL-PV scores using SPSS v. 18 (SPSS Inc., Chicago, IL).42
For each of the seven assessments, mean total GSDS and DS subscale scores were calculated for use in the subsequent statistical analyses.
Hierarchical linear modeling (HLM), based on full maximum likelihood estimation, was done using the software developed by Raudenbush and Bryk.43
The repeated measures of overall sleep disturbance and DS were conceptualized as being nested within individuals. Compared with other methods of analyzing change, HLM has two major advantages. First, HLM can accommodate unbalanced designs, which allows for the analysis of data when the number and the spacing of the assessments vary across respondents. Second, HLM has the ability to model individual change, which helps to identify more complex patterns of change that are often overlooked by other methods.43,44
With HLM, the repeated measures of the outcome variables (i.e., overall sleep disturbance and DS) are nested within individuals and the analysis of change in these scores has two levels: within persons (level 1) and between persons (level 2). At level 1, the outcome is conceptualized as varying within individuals and is a function of person-specific change parameters plus error. At level 2, these person-specific change parameters are multivariate outcomes that vary across individuals. These level 2 outcomes can be modeled as a function of demographic, clinical, and symptom characteristics that vary between individuals, plus an error associated with the individual. Combining level 1 and level 2 results in a mixed model with both fixed and random effects.
Separate HLM analyses were done to evaluate changes over time in ratings of overall sleep disturbance and DS. Each HLM analysis proceeded in two stages. First, intra-individual variability in the sleep parameter over time was examined. In this study, time, in months, refers to the length of time from the preoperative visit to six months after the completion of surgery (i.e., six months with a total of seven assessments). Three level 1 models, which represented that the patients’ sleep parameter levels a) did not change over time (i.e., no time effect), b) changed at a constant rate (i.e., linear time effect), and c) changed at a rate that accelerates or decelerates over time (i.e., quadratic effect), were compared. At this point, the level 2 model was constrained to be unconditional (i.e., no predictors), and the likelihood ratio tests were used to determine the best model.
The second stage of the HLM analysis, examined interindividual differences in the trajectories of overall sleep disturbance and DS by modeling the individual change parameters (i.e., intercept, linear, and quadratic slopes) as a function of proposed predictors at level 2. presents a list of the proposed predictors that was developed based on a review of the literature of sleep disturbance in women with breast cancer.2,6,8,15,17–23
To improve estimation efficiency and construct a model that was parsimonious, an exploratory level 2 analysis was done in which each potential predictor was assessed to see it if would result in a better fitting model if it alone was added as a level 2 predictor. Predictors with a t
value of less than 2.0, which indicates a lack of a significant effect, were dropped from subsequent model testing. All of the potentially significant predictors from the exploratory analyses were entered into the model to predict each individual change parameter. Only predictors that maintained a significant contribution in conjunction with other variables were retained in the final model. A P
-value of <0.05 indicates statistical significance.
Potential Predictors of Intercepts (I), Linear Coefficients (LC), and Quadratic Coefficients (QC) for the Overall Sleep Disturbance and Daytime Sleepiness