Abstract
Context.
While ~75% of breast cancer patients report changes in attentional function, little is known about how demographic, clinical, symptom, and psychosocial adjustment (e.g., coping) characteristics influence changes in the trajectories of attentional function over time.
Objectives.
This study evaluated inter-individual variability in the trajectories of self-reported attentional function and determined which demographic, clinical, symptom, and psychosocial adjustment characteristics were associated with initial levels and with changes in attentional function from prior to through 12 months after breast cancer surgery.
Methods.
Prior to surgery, 396 women were enrolled. Attentional Function Index (AFI) was completed prior to and nine times within the first 12 months after surgery. Hierarchical linear modeling (HLM) was used to determine which characteristics were associated with initial levels and trajectories of attentional function.
Results.
Given an estimated preoperative AFI score of 6.53, for each additional month, the estimated linear rate of change in AFI score was an increase of 0.054 (p<0.001). Higher levels of comorbidity, receipt of adjuvant chemotherapy, higher levels of trait anxiety, fatigue, and sleep disturbance, and lower levels of energy and less sense of control were associated with lower levels of attentional function prior to surgery. Patients who had less improvements in attentional function over time were Non-white, did not have a lymph node biopsy, had received hormonal therapy, and had less difficulty coping with their disease.
Conclusions.
Findings can be used to identify breast cancer patients at higher risk for impaired self-reported cognitive function and to guide the prescription of more personalized interventions.
Keywords: cancer-related cognitive impairment; attentional function, breast cancer, anxiety; fatigue; sleep disturbance; coping
INTRODUCTION
Cognition is a fundamental aspect of one’s ability to engage in activities and accomplish goals. Cognition involves different inter-related functions, including attention, memory, comprehension, problem solving, verbal fluency, and decision-making.1 Directed attention is connected to working memory and requires mental effort to actively inhibit irrelevant distractions for goal-directed tasks. Attentional function, supported by directed attention, may be among the most essential functions for cancer patients because it helps them acquire important information, make decisions, and carry out self-care-activities.2 Impairments in attentional function may interfere with patients’ self-care activities, such as their ability to adhere to treatment, manage side effects, and re-integrate into the workforce, which has a negative impact on their quality of life (QOL).3,4
Approximately 75% of breast cancer patients experience cancer-related cognitive impairment (CRCI) prior to, during, or after treatment.5 In addition, CRCI remains a significant long-term problem for about 35% of survivors.6-11 Determining the underlying mechanisms and risk factors for, as well as effective interventions for CRCI has been challenging. Findings from objective neuropsychological tests correlate poorly with self-report measures of CRCI,2,12-16 and often do not detect deficits, even when patients have subjective complaints about difficulties with routine activities (e.g., problems with driving, inability to return to work).13,17 Therefore, self-report measures are an essential component of the assessment of CRCI because they are better able to capture patients’ experiences.18,19
Initially, CRCI was hypothesized to occur only with the administration of chemotherapy (CTX; i.e., “chemobrain”). However, accumulating evidence suggests that the etiology of CRCI in breast cancer patients is multi-factorial (e.g., the cancer itself,8 neurotoxic effects of CTX;20-26 chemically or surgically-induced menopause and the effects of hormone treatments on estrogen levels;4,27-29 systemic immune responses induced by localized radiation therapy and subsequent elevation in plasma interleukin (IL)-6 levels;30,31 delirium and stress associated with anesthesia and sugery;32 chronic inflammation, dysregulation of cytokines, and premature aging due to telomere shortening induced by the cancer itself7,32,33) Because most of these data come from studies that evaluated CRCI following surgery,33 additional research is warranted that addresses the occurrence of and risk factors for CRCI prior to and following breast cancer surgery.
A number of demographic and clinical characteristics, co-occurring symptoms, and psychosocial adjustment characteristics are associated with an increased risk for more severe CRCI. For example, while older breast cancer patients are presumed to be at a higher risk for CRCI because of age-related changes in cognition and the use of different coping mechanisms,2 in some studies,23,33-35 younger patients were at increased risk for CRCI during the survivorship period. Co-occurring symptoms, such as anxiety,9,36,37 depressive symptoms,6,36,37 fatigue,6,8,9,37,38 neuropathy,39 and sleep disturbance,6,37,38 have been associated with CRCI both prior to and after breast cancer surgery.13 In addition, in studies that evaluated patients prior to breast cancer surgery,2,6,40 while CRCI was not associated with treatment modality, it was associated with pre-treatment levels of co-occurring symptoms. Of note, findings from recent studies suggest that associations between CRCI and anxiety and depressive symptoms may be related to challenges with emotional regulation, coping (e.g., avoidance), and psychosocial adjustment to breast cancer.41-44 However, because of the observational nature of these studies, the relatively small sample sizes, and the lack of a comprehensive assessment of risk factors, these findings warrant replication to obtain a more comprehensive understanding of the risk factors associated with CRCI prior to and following breast cancer surgery.
In several longitudinal studies that evaluated for CRCI in women with breast cancer6,8,9,11,36,45 findings suggest that cognitive function returns to presurgical levels at approximately 12 months. However, direct comparisons across studies are difficult because of the different aspects of CRCI that were evaluated (e.g., memory, verbal fluency); differences in the use of subjective versus objective measures; and differences in the number and timing of the assessments. In the one study that evaluated for inter-individual differences in CRCI trajectories,6 the patients’ cancer diagnosis and/or co-occurring symptoms were associated with CRCI at each measurement point, from prior to through 24 months post-surgery. Of note, two recent reviews highlighted the paucity of research in this area and recommended that longitudinal studies examine the associations between CRCI and common co-occurring symptoms.36,42
Taken together these findings suggest that breast cancer patients are at relatively high risk for CRCI and that additional research is warranted on inter-individual differences in risk factors for this significant clinical problem. Given that no study has evaluated a comprehensive list of potential risk factors for CRCI from prior to through recovery after surgery, the purposes of this study, in a sample of patients who were assessed from prior to through 12 months after surgery (n=396), were to evaluate for inter-individual variability in the trajectories of self-reported attentional function and to determine which demographic, clinical, symptom and psychosocial adjustment characteristics were associated with initial levels and with changes in the trajectories of attentional function.
METHODS
Patients and settings
This descriptive, longitudinal study is part of a larger study that evaluated neuropathic pain and lymphedema in women who underwent breast cancer surgery whose methods were described in detail elsewhere.47-49 In brief, patients were recruited from Breast Care Centers located in a Comprehensive Cancer Center, two public hospitals, and four community practices in Northern California. Patients were eligible to participate if they: were adult women (≥18 years) scheduled to have breast cancer surgery on one breast; were able to read, write, and understand English; agreed to participate; and gave written informed consent. Patients were excluded if they were having breast cancer surgery on both breasts 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 79.5%). For the current analysis, complete data from 396 women were available.
Instruments
Demographic and clinical characteristics
Patients completed a demographic questionnaire, the Karnofsky Performance Status (KPS) scale,50 and the Self-Administered Comorbidity Questionnaire (SCQ).51
Attentional Function
The 16-item Attentional Function Index (AFI) is a commonly used self-report measure of attentional function.18 Each item was rated on a 0 to 10 numeric rating scale (NRS). A higher mean score indicates greater capacity to direct attention.18,52 AFI scores can be grouped into categories (i.e., <5.0 low attentional function, 5.0 to 7.5 moderate function, and >7.5 high function).2 AFI has well established validity and reliability.52,53 Its Cronbach’s alpha was .95 in this study.
Symptom Measures
Spielberger State-Trait Anxiety Inventories (STAI-T, STAI-S) consist of 20 items that are rated from 1 to 4. Scores for each scale are summed and can range from 20 to 80. A higher score indicates greater anxiety. Cut-off scores of ≥31.8 and ≥32.2 indicate high levels of trait and state anxiety, respectively.54 STAI-S and STAI-T inventories have well-established validity and reliability.55,56 Cronbach’s alphas for STAI-T and STAI-S were .88 and .95, respectively.
Center for Epidemiological Studies Depression Scale (CES-D) consists of 20 items assessing major symptoms of depression. Scores can range from 0 to 60, with scores of ≥16 indicating the need for clinical evaluation of major depression. The CES-D has well-established validity and reliability.57-59 Its Cronbach’s alpha was .90 in this study.
The 18-item Lee Fatigue Scale (LFS) assesses physical fatigue and energy.60 Each item was rated on a 0 to 10 NRS. Total fatigue and energy scores were calculated as the mean of 13 fatigue items and 5 energy items. Higher scores indicate greater fatigue severity and higher levels of energy. Patients were asked to rate each item based on how they felt “right now.”A cut-off score >4.4 indicates high levels of fatigue. A cut-off score ≤4.8 indicates low levels of energy.61 LFS has well established validity and reliability. Cronbach’s alphas for the fatigue and energy scales were .96 and .93, respectively.
The 21-item General Sleep Disturbance Scale (GSDS) assesses sleep quality in the past week. Each item was rated on a 0 (never) to 7 (everyday) NRS. The GSDS total score is the sum of 21 items, that ranges from 0 (no disturbance) to 147 (extreme sleep disturbance). A GSDS total score of ≥43 indicates a significant level of sleep disturbance.62 The GSDS has well-established validity and reliability. Its Cronbach’s alpha was .86 in this study.
The occurrence of breast pain prior to surgery was assessed with the question “Are you experiencing pain in your affected breast?” Patients who responded “yes”, rated the severity of their average and worst pain using a 0 (no pain) to 10 (worst imaginable pain) NRS. Patients were asked how many days per week and how many hours per day they experienced pain that interfered with function.
Psychosocial Adjustment Characteristics
Quality of Life Scale-Patient Version (QOL-PV) is a 41-item instrument that assesses four dimensions of QOL in cancer patients (i.e., physical, psychological, spiritual, social well-being), and a total QOL score. Each item was rated on a 0 to 10 NRS with higher scores indicating a better QOL. The QOL-PV has well established validity and reliability.63,64 Cronbach’s alpha for the QOL-PV total score was .86 in this study. Coefficients for the physical, psychological, spiritual and social well-being subscales were .70, .79, .75, and .61, respectively.
Individual items from the QOL-PV were used to assess psychosocial adjustment characteristics (i.e., distress, fear, coping, control). Patients were asked to rate their level of distress regarding their cancer diagnosis, fear of future diagnostic tests, fear of metastasis, level of control they felt over their lives, and difficulties coping as a result of cancer and its treatment. Each of these 5 items was rated using a 0 to 10 NRS with higher scores indicating a more positive appraisal of a particular characteristic. These specific items, that were used in our previous studies,65,66 were chosen for evaluation based on literature reviews of psychosocial adjustment and attentional function in women with breast cancer.44,67
Study procedures
The Committee on Human Research at the University of California, San Francisco and the Institutional Review Board at each of the study sites approved the study protocol. During the patients’ preoperative visit, a clinical staff member explained the study and introduced the patient to the research nurse, who determined eligibility and obtained written informed consent prior to surgery. Patients completed the enrollment questionnaires on average four days prior to surgery and follow-up questionnnaires at 1, 2, 3, 4, 5, 6, 8, 10, and 12 months after surgery. The research nurse met with participants in the Clinical Research Center or in their home. Medical records were reviewed for disease and treatment information.
Statistical analyses
Descriptive statistics and frequency distributions were generated on the sample characteristics, symptom severity scores, and psychosocial adjustment items using SPSS version 23.68 AFI was assessed prior to surgery and at 1, 2, 3, 4, 5, 6, 8, 10, and 12 months after surgery. All other demographic, clinical, symptom and psychosocial adjustment characteristics that were evaluated as predictors in the hierarchical linear modeling (HLM) analysis were assessed prior to surgery.
HLM based on full maximum likelihood estimation was done using the software developed by Raudenbush and colleagues.69,70 This analysis is discussed in detail in our previous publications.61,71,72 In brief, during stage 1, intra-individual variability in AFI scores over time was examined. At this point, the model was constrained to be unconditional (i.e., no predictors) and likelihood ratio tests were used to determine the best fitting model.
The second stage of the HLM analysis examined inter-individual differences in the trajectories of AFI scores by modeling the individual change parameters (i.e., intercept, linear slope) as a function of proposed predictors at level 2. Table 1 presents a list of the proposed predictors that was developed based on a literature review about CRCI in breast cancer patients.6,16,40,44,67,73,74 To improve estimation efficiency and construct a parsimonious model, an exploratory level 2 analysis was completed in which each potential predictor was assessed to determine whether it would result in a better model if it alone were added as a level 2 predictor. Predictors with a t-value of < 2.0 were dropped from subsequent model testing. All potential significant predictors from the exploratory analyses were entered into the model to predict each individual change parameter. Only predictors that maintained a statistically significant contribution in conjunction with other variables were retained in the final model. A p-value of <.05 indicated statistical significance.
Table 1 –
Potential predictors of the intercept (I) and linear coefficient (LC) for attentional function using preoperative characteristics
Characteristic | I | LC |
---|---|---|
Demographic characteristics | ||
Age | ![]() |
|
Lives alone | ||
Education | ![]() |
|
Marital status | ||
Ethnicity | ![]() |
![]() |
Employment status | ||
Clinical characteristics | ||
Body mass index | ![]() |
|
Karnofsky Performance Status score | ![]() |
|
Self-administered Comorbidity Questionnaire score | ![]() |
|
Neoadjuvant chemotherapy | ![]() |
|
Type of surgery | ||
Sentinel lymph node biopsy | ![]() |
|
Axillary lymph node dissection | ![]() |
|
Breast reconstruction at the time of surgery | ![]() |
|
Menopausal status | ||
Adjuvant radiation therapy in the first six months after surgery | ||
Adjuvant chemotherapy in the first six months after surgery | ![]() |
|
Use of complementary therapy in first six months after surgery | ![]() |
|
Use of hormonal therapy in the first six months after surgery | ![]() |
|
Symptoms | ||
Trait anxiety score | ![]() |
|
State anxiety score | ![]() |
![]() |
Center for Epidemiological Studies Depression Scale score | ![]() |
![]() |
General Sleep Disturbance Scale score | ![]() |
![]() |
Lee Fatigue Scale score | ![]() |
![]() |
Lee Energy Scale score | ![]() |
|
Attentional Function Index score | ![]() |
|
Presence of breast pain prior to surgery | ![]() |
|
Worst pain | ![]() |
|
Average pain | ![]() |
|
Number of days per week in pain | ![]() |
|
Number of hours per day in pain | ![]() |
|
Severity of hot flashes | ![]() |
|
Psychosocial adjustment characteristics | ||
Distress at initial cancer diagnosis | ![]() |
![]() |
Fear of future diagnostic tests | ![]() |
![]() |
Fear of metastasis | ![]() |
![]() |
Difficulty coping as a result of disease/treatment | ![]() |
![]() |
Control of things in your life | ![]() |
RESULTS
Patient Characteristics
The demographic, clinical, symptom, and psychosocial adjustment characteristics for the patients (n=396) are summarized in Table 2. On average, patients were 55 years of age, well-educated, and underwent breast conserving surgery (80.3%). Most patients self-identified as White (64.9%), were post-menopausal (64.9%), and were unemployed (52.3%).
Table 2 –
Demographic, clinical, symptom, and psychosocial adjustment characteristics of the patients prior to surgery (n=396)
Demographic and clinical characteristics | Mean (SD) |
---|---|
Age (years) | 54.9 (11.6) |
Education (years) | 15.7 (2.6) |
Karnofsky Performance Status score | 93.2 (10.3) |
Self-Administered Comorbidity Questionnaire score | 4.3 (2.8) |
% | |
Non-white | 35.1 |
Married or partnered | 41.4 |
Working for pay | 23.7 |
Postmenopausal | 47.7 |
Stage of disease | |
0 | 18.4 |
I | 38.4 |
IIA and IIB | 34.8 |
IIIA, IIIB, IIIC, and IV | 8.4 |
Received neoadjuvant chemotherapy | 19.9 |
Type of surgery | |
Breast conservation surgery | 80.3 |
Mastectomy | 19.7 |
Sentinel lymph node biopsy | 82.6 |
Axillary lymph node dissection | 37.1 |
Underwent reconstruction at the time of surgery | 21.7 |
Received adjuvant radiation therapy in the first six months | 56.6 |
Received adjuvant chemotherapy in the first six months | 33.6 |
Symptom severity scores prior to surgery | Mean (SD) |
Attentional Function Index score | 6.6 (1.9) |
Trait Anxiety Inventory score | 35.3 (8.8) |
State Anxiety Inventory score | 41.6 (13.3) |
Center for Epidemiological Studies-Depression score | 13.7 (9.7) |
Lee Fatigue Scale - Fatigue score | 3.1 (2.3) |
Lee Fatigue Scale - Energy score | 4.9 (2.5) |
General Sleep Disturbance Scale score | 48.1 (21.3) |
Pain in affected breast prior to surgery (% yes) | 27.5 |
Psychosocial adjustment characteristics | |
Distress at initial cancer diagnosis | 8.1 (2.7) |
Fear of future diagnostic tests | 5.2 (3.3) |
Fear of metastasis | 6.0 (3.5) |
Difficulty coping as a result of disease/treatment | 3.3 (2.6) |
Control of things in your life | 6.1 (2.6) |
Abbreviation: SD = standard deviation
Individual and mean change in attentional function
The first stage of HLM analysis examined how attentional function changed from prior to through 12 months after surgery. Table 3 presents the estimates of the unconditional, linear model. Because the model had no covariates, the intercept represents the estimated level of attentional function (i.e., 6.543 on a 0 to 10 scale) at the preoperative assessment. The estimated linear rate of change in attentional function, for each additional month, was .054 (p<.001). Figure 1A displays the trajectory for attentional function from the preoperative assessment through 12 months after surgery. Attentional function increased slightly over the course of 12 months. The mean attentional function scores for the various groups depicted in all of the figures are estimated or predicted means based on the HLM analysis.
Table 3 –
Hierarchical linear model of attentional function
Coefficient (SE) | ||
---|---|---|
Unconditional Model |
Final Model | |
Fixed effects | ||
Intercept | 6.543 (.084)+ | 6.543 (.057)+ |
Timea (linear rate of change) | .054 (.007)+ | .053 (.006)+ |
Time invariant covariates | ||
Intercept | ||
Level of comorbidity | −.044 (.020)* | |
Receipt of adjuvant chemotherapy | −.547 (.116)+ | |
Trait anxiety | −.038 (.007)+ | |
Fatigue | −.171 (.029)+ | |
Energy | .118 (.024)+ | |
Sleep disturbance | −.016 (.003)+ | |
Control of things in life | .117 (.024)+ | |
Linear | ||
Non-white ethnicity x time | −.047 (.012)+ | |
Sentinel lymph node biopsy x time | .053 (.015)** | |
Receipt of hormonal therapy x time | −.025 (.012)* | |
Attentional function x time | −.010 (.003)** | |
Difficulty coping x time | .008 (.002)** | |
Variance components | ||
In intercept | 2.401+ | .922+ |
In slope | .007+ | .004+ |
Goodness-of-fit deviance (parameters estimated) | 11649.144 (6) | 11290.122 (18) |
Model comparison (X2) | 359.021 (12)+ |
Time was coded as zero at the time of the preoperative visit
Abbreviation: SE = standard error
p<.05
p<.01
p<.001
Figure 1.
Trajectory of cognitive function evaluated using the Attentional Functional Index over the 12 months (A). Influence of comorbidity (B) and receipt of adjuvant chemotherapy (CTX) (C) on interindividual differences in the severity of attentional function over 12 months.
Inter-individual differences in the trajectories of attentional function
The second stage of the HLM analysis evaluated how attentional function at the preoperative assessment and its change over time were associated with specific demographic, clinical, symptom, and psychosocial adjustment characteristics. As shown in the final model in Table 3, the characteristics that were associated with inter-individual differences in preoperative levels of attentional function were: level of comorbidity; receipt of adjuvant CTX; severity of trait anxiety, fatigue, energy, and sleep disturbance; and perception of control over things in one’s life. The characteristics that were associated with inter-individual differences in the linear slope for attentional function were ethnicity, having had a sentinel lymph node biopsy (SLNB), receipt of hormonal therapy, level of attentional function prior to surgery, and difficulty coping with cancer and its treatment.
To illustrate the effects of each of these characteristics on patients’ initial levels and trajectories of attentional function, Figures 1B and 1C display the adjusted change curves for attentional function that were estimated based on differences in level of comorbidity (i.e., lower/higher level of comorbidity calculated based on one standard deviation [SD] below and above the mean SCQ score) and receipt of adjuvant CTX (i.e., yes/no), respectively. Figures 2A through 2E display the adjusted change curves for attentional function that were estimated based on differences in trait anxiety, fatigue, energy, sleep disturbance and sense of control (i.e., higher/lower levels of each characteristic calculated based on one SD above and below the mean scores), respectively. Figures 3A through 3E display the adjusted change curves for attentional function that were estimated based on differences in ethnicity (White/Non-white), underwent SLNB (yes/no), receipt of hormonal therapy (yes/no), AFI score at enrollment, and difficulty coping with cancer and its treatments.
Figure 2.
Influence of levels of trait anxiety (A), fatigue (B), energy (C), sleep disturbance (D), and sense of control (E) on interindividual differences in the severity of attentional function over 12 months.
Figure 3.
Influence of race/ethnicity (A), receipt of a sentinel lymph node biopsy (B), receipt of hormonal therapy (C), preoperative level of attentional fuction (D), and level of difficulty coping with the disease (E) on interindividual differences in severity of attentional fatigue over 12 months.
In summary, patients with lower levels of self-reported attentional function prior to surgery had a higher level of comorbidity; were scheduled to receive adjuvant CTX; had higher levels of trait anxiety, fatigue, and sleep disturbance and lower levels of energy; and reported less control over things in their life. In addition, patients with less improvement in AFI scores over time were more likely to be non-White, to have not had a SLNB, to have been prescribed hormonal therapy following surgery, and to have reported less difficulty coping as a result of their cancer and its treatments prior to surgery.
DISCUSSION
This study is the first to use HLM to examine inter-individual differences in the trajectories of attentional function and to evaluate whether a comprehensive list of demographic, clinical, symptom, and psychosocial adjustment characteristics were associated with AFI scores prior to surgery and over a period of 12 months. Prior to surgery, our patients had a mean AFI score of 6.5 which suggests that these women had some pre-existing impairments in attentional function. Our finding is consistent with a study by Cimprich and collegues (i.e., preoperative AFI score of 6.6)2 but lower than the AFI score reported by Chen and colleagues (preoperative AFI score of 8.2).6 While our sample’s overall AFI score improved over the twelve months following surgery, at the end of one year, it remained in the moderate range (i.e., estimated at 7.18). However, as seen in Figure 3D, and consistent with a previous report,75 patients in our study with lower preoperative AFI scores demonstrated greater improvements in attentional function in the 12 months following surgery. The minimal increase in AFI scores in our sample may be associated with inter-individual variability in the relatively large number of characteristics associated with decrements in attentional function that were identified in this study.
Consistent with previous reports,9,36 no differences in preoperative AFI scores were found between our White and non-White patients. However, over the 12 months of the study, compared to the White patients, non-White patients had less improvements in their AFI scores over time. This association may be related to a number of factors including level of education,76,77 employment status and ability to return to work,78 and/or financial burden and high out-of-pocket costs associated with cancer and its treatments.79 Our findings suggest that breast cancer patients from diverse ethnic backgrounds may need additional support and resources to improve their level of attentional function.
In terms of clinical characteristics and consistent with previous reports,80-82 a higher level of comorbitiy was associated with lower preoperative AFI scores. In addition, while having an axillary lymph node dissection was not associated with changes in attentional function, patients who did not have a SLNB (i.e., 17.4% of the sample) reported worse AFI scores over time. This finding is most likely related to the fact that women who did not have a SLNB were most likely to be diagnosed with more advanced stage disease and had received neoadjuvant CTX and/or a mastectomy with an axillary lymph node dissection.
While receipt of neoadjuvant CTX was identified as a potential predictor in the exploratory analyses, it was not included in the final model. However, consistent with previous reports,23,36,75,83 receipt of adjuvant CTX was associated with lower AFI scores. In addition, patients who received hormonal treatment had a decline in attentional function over the 12 months of the study. The molecular mechanisms associated with CTX- and hormonally-induced changes in cognitive function are extremely complex and include: disruption of the blood-brain-barrier; deoxyribonucleic acid (DNA) damage and associated deficits in DNA repair mechanisms; telomere shortening; oxidative stress and associated inflammatory responses; polymorphisms in genes associated with neural repair; alterations in neural transmission; as well as changes in levels of sex steroid hormones that under physiologic conditions are neuroprotective and reduce oxidative stress (for reviews see 84-86). Additional research is warranted that examines associations between changes in attentional function and each of these molecular mechanisms. These types of investigations may identify potential therapeutic targets.
This study is the first to evaluate for associations between a comprehensive list of common co-occurring symptoms and changes in attentional function. Of note, in the exploratory analysis, all of the symptoms evaluated (i.e., trait anxiety, state anxiety, depression, fatigue, decrements in energy, sleep disturbance, pain, hot flashes) were associated with initial levels and/or the trajectories of attentional function. However, only trait anxiety, fatigue, decrements in energy, and sleep disturbance were retained in the final model. Consistent with previous studies,6,8,36,87 higher levels of fatigue and lower levels of energy were associated with poorer attentional function at enrollment that persisted over the 12 months of the study. The association among these three symptoms may be related to a number of shared pathophysiologic mechanisms including: increases in inflammatory responses,88, as well as the deleterious effects of cancer87,89 and its treatments8,9,87 on DNA repair mechanisms and neural transmission.
Consistent with previous studies,2,6, 16,38,73,90 higher levels of sleep disturbance were associated with lower AFI scores. At enrollment, our patients reported relatively high levels of sleep disturbance (i.e., mean GSDS score 48.1 (α21.3); cut-off score of ≥43 indicates a significant level of sleep disturbance). Again, the association between decrements in attentional function and sleep disturbance may be due to decreases in the restorative processes associated with 6 to 8 hours of sleep91,92 as well as excessive daytime sleepiness which is often associated with sleep disturbance. In addition, these two symptoms may share common underlying mechanisms including: increased levels of pro-inflammatory cytokines, changes in activity with the hypothalamic-pituitary adrenal axis, and alterations in DNA repair mechanisms.33,87,93,94
Consistent with other studies,2,6,9,36,44,45,75,95,96 associations were found between higher preoperative levels of trait and state anxiety and lower levels of attentional function. Our patients reported levels of trait and state anxiety that were above the clinically meaningful cutoff scores for the instruments. In addition, findings from several longitudinal studies suggest that positive associations between anxiety and decrements in attentional function persist over time.6,9,45 Of note, while anxiety and depressive symptoms often co-occur in cancer patients,97 even though depressive symptoms were identified as a potential predictor in the exploratory analysis, it was not retained in the final model. Additional research is warranted on the co-occurrence of these two psychological symptoms and associated decrements in attentional function.
The relationship between higher levels of state anxiety and decrements in attentional function may be partially explained by women’s use of disengagement coping strategies (e.g., avoidance, denial, self-blame).41,44,98 This hypothesis is partially supported by our finding that women who reported that they perceived that they had less control over things in their life had lower levels of attentional function at enrollment. However, it is not readily apparent why an association was found with lower levels of difficulty with coping at enrollment and lack of improvements in attentional function over time. One could hypothesize that patients with more difficulties coping prior to surgery were more likely to seek and obtain support to improve their coping skills and had associated improvements in cognitive function. That said, our findings suggest that clinicians need to assess patients prior to surgery for anxiety, as well as various psychosocial adjustment characteristics (e.g., coping styles) so that patient education and/or appropriate referrals can be initiated.99,100
While this longitudinal study had numerous strengths including a relatively large sample size; a comprehensive evaluation of associations between demographic, clinical, symptom, and psychosocial adjustment characteristics and decrements in self-reported attentional function; as well as 12 months of follow-up, several limitations warrant consideration. The majority of our patients were White, well educated, and diagnosed with early stage disease, which limits the generalizability of our study findings. Despite the fact that findings from objective neuropsychological tests correlate poorly with self-report measures of CRCI,2,12-16 and often do not detect deficits, even when patients have subjective complaints about difficulties with routine activities,13,17 future studies should evaluate for longitudinal changes in CRCI using both types of measures. In addition, future studies should include age-matched controls without breast cancer. Our analysis focused on an evaluation of associations with preoperative levels of co-occurring symptoms. Given that symptom severity changes over time, future studies need to consider the use of statistical techniques like parallel process growth modeling to evaluate for changes over time in the severity of attentional function and each of the co-occurring symptoms.
While the clinical characteristics associated with deficits in attentional function (i.e., level of comorbidity, receipt of adjuvant CTX, receipt of hormonal therapy) cannot be changed, many of the other characteristics can be assessed and addressed with appropriate pharmacologic and non-pharmacologic interventions. The initiation of these interventions, in the perioperative period, may result in a decrease in patients’ overall symptom burden, as well as improvements in attentional function. In addition, timely referrals to mental health professionals and/or social workers may decrease patients’ levels of anxiety and stress, as well as improve their ability to cope with their cancer treatment(s) and maintain their level of cognitive function.
Acknowledgments
This study was funded by grants from the National Cancer Institute (CA107091 and CA118658). Dr. Christine Miaskowski is an American Cancer Society Clinical Research Professor. This project was supported by NIH/NCRR UCSF-CTSI Grant Number UL1 RR024131. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.
Footnotes
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Conflicts of interest – The authors have no conflicts of interest to declare.
REFERENCES
- 1.Blazer DG, Yaffe K, Liverman CT. Cognitive aging: Progress in understanding and opportunities for action, National Academies Press; Washington, DC:, 2015. [PubMed] [Google Scholar]
- 2.Cimprich B, So H, Ronis DL, Trask C. Pre-treatment factors related to cognitive functioning in women newly diagnosed with breast cancer. Psychooncology 2005;14:70–78. [DOI] [PubMed] [Google Scholar]
- 3.Arndt J, Das E, Schagen SB, et al. Broadening the cancer and cognition landscape: the role of self-regulatory challenges. Psychooncology 2014;23:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Horowitz TS, Suls J, Trevino M. A call for a neuroscience approach to cancer-related cognitive impairment. Trends Neurosci 2018;41:493–496. [DOI] [PubMed] [Google Scholar]
- 5.Janelsins MC, Kohli S, Mohile SG, et al. An update on cancer- and chemotherapy-related cognitive dysfunction: current status. Semin Oncol 2011;38:431–438. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Chen ML, Miaskowski C, Liu LN, Chen SC. Changes in perceived attentional function in women following breast cancer surgery. Breast Cancer Res Treat 2012;131:599–606. [DOI] [PubMed] [Google Scholar]
- 7.Ganz PA, Petersen L, Castellon SA, et al. Cognitive function after the initiation of adjuvant endocrine therapy in early-stage breast cancer: an observational cohort study. J Clin Oncol 2014;32:3559–3567. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gullett JM, Cohen RA, Yang GS, et al. Relationship of fatigue with cognitive performance in women with early-stage breast cancer over 2 years. Psychooncology 2019;28:997–1003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lyon DE, Cohen R, Chen H, et al. The relationship of cognitive performance to concurrent symptoms, cancer- and cancer-treatment-related variables in women with early-stage breast cancer: a 2-year longitudinal study. J Cancer Res Clin Oncol 2016;142:1461–1474. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Merriman JD, Sereika SM, Brufsky AM, et al. Trajectories of self-reported cognitive function in postmenopausal women during adjuvant systemic therapy for breast cancer. Psychooncology 2017;26:44–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ribi K, Aldridge J, Phillips KA, et al. Subjective cognitive complaints one year after ceasing adjuvant endocrine treatment for early-stage breast cancer. Br J Cancer 2012;106:1618–1625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Andreotti C, Root JC, Schagen SB, et al. Reliable change in neuropsychological assessment of breast cancer survivors. Psychooncology 2016;25:43–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Janelsins MC, Heckler CE, Peppone LJ, et al. Cognitive complaints in survivors of breast cancer after chemotherapy compared with age-matched controls: An analysis from a nationwide, multicenter, prospective longitudinal study. J Clin Oncol 2017;35:506–514. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Jenkins V, Shilling V, Deutsch G, et al. A 3-year prospective study of the effects of adjuvant treatments on cognition in women with early stage breast cancer. Br J Cancer 2006;94:828–834. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Pullens MJ, De Vries J, Roukema JA. Subjective cognitive dysfunction in breast cancer patients: a systematic review. Psychooncology 2010;19:1127–1138. [DOI] [PubMed] [Google Scholar]
- 16.Van Dyk K, Bower JE, Crespi CM, Petersen L, Ganz PA. Cognitive function following breast cancer treatment and associations with concurrent symptoms. NPJ Breast Cancer 2018;4:25. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Boykoff N, Moieni M, Subramanian SK. Confronting chemobrain: an in-depth look at survivors' reports of impact on work, social networks, and health care response. J Cancer Surviv 2009;3:223–232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Cimprich B, Visovatti M, Ronis DL. The Attentional Function Index--a self-report cognitive measure. Psychooncology 2011;20:194–202. [DOI] [PubMed] [Google Scholar]
- 19.Savard J, Ganz PA. Subjective or objective measures of cognitive functioning-what's more important? JAMA Oncol 2016;2:1263–1264. [DOI] [PubMed] [Google Scholar]
- 20.Ahles TA, Saykin AJ. Candidate mechanisms for chemotherapy-induced cognitive changes. Nat Rev Cancer 2007;7:192–201. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ahles TA, Saykin AJ, McDonald BC, et al. Longitudinal assessment of cognitive changes associated with adjuvant treatment for breast cancer: impact of age and cognitive reserve. J Clin Oncol 2010;28:4434–4440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Biglia N, Bounous VE, Malabaila A, et al. Objective and self-reported cognitive dysfunction in breast cancer women treated with chemotherapy: a prospective study. Eur J Cancer Care 2012;21:485–492. [DOI] [PubMed] [Google Scholar]
- 23.Gregorowitsch ML, Ghedri A, Young-Afat DA, et al. The effect of chemotherapy on subjective cognitive function in younger early-stage breast cancer survivors treated with chemotherapy compared to older patients. Breast Cancer Res Treat 2019;175:429–441. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Hedayati E, Alinaghizadeh H, Schedin A, Nyman H, Albertsson M. Effects of adjuvant treatment on cognitive function in women with early breast cancer. Eur J Oncol Nurs 2012;16:315–322. [DOI] [PubMed] [Google Scholar]
- 25.Hermelink K. Chemotherapy and cognitive function in breast cancer patients: the so-called chemo brain. NCI Monogr 2015;2015:67–69. [DOI] [PubMed] [Google Scholar]
- 26.Hurria A, Somlo G, Ahles T. Renaming "chemobrain". Cancer Invest 2007;25:373–377. [DOI] [PubMed] [Google Scholar]
- 27.Pendergrass JC, Targum SD, Harrison JE. Cognitive impairment associated with cancer: A brief review. Innov Clin Neurosci 2018;15:36–44. [PMC free article] [PubMed] [Google Scholar]
- 28.Vodermaier A Breast cancer treatment and cognitive function: the current state of evidence, underlying mechanisms and potential treatments. Womens Health 2009;5:503–516. [DOI] [PubMed] [Google Scholar]
- 29.Zwart W, Terra H, Linn SC, Schagen SB. Cognitive effects of endocrine therapy for breast cancer: keep calm and carry on? Nat Rev Clin Oncol 2015;12:597–606. [DOI] [PubMed] [Google Scholar]
- 30.Ganz PA, Kwan L, Castellon SA, et al. Cognitive complaints after breast cancer treatments: examining the relationship with neuropsychological test performance. J Natl Cancer Inst 2013;105:791–801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Shibayama O, Yoshiuchi K, Inagaki M, et al. Association between adjuvant regional radiotherapy and cognitive function in breast cancer patients treated with conservation therapy. Cancer Med 2014;3:702–709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Ahles TA, Root JC. Cognitive effects of cancer and cancer treatments. Annu Rev Clin Psychol 2018;14:425–451. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hardy SJ, Krull KR, Wefel JS, Janelsins M. Cognitive changes in cancer survivors. Am Soc Clin Oncol Educ Book 2018;38:795–806. [DOI] [PubMed] [Google Scholar]
- 34.Freedman RA, Partridge AH. Adjuvant therapies for very young women with early stage breast cancer. Breast 2011;20 Suppl 3:S146–149. [DOI] [PubMed] [Google Scholar]
- 35.Rey D, Bouhnik AD, Mancini J, et al. Self-reported cognitive impairment after breast cancer treatment in young women from the ELIPPSE40 cohort: the long-term impact of chemotherapy. Breast J 2012;18:406–414. [DOI] [PubMed] [Google Scholar]
- 36.Janelsins MC, Heckler CE, Peppone LJ, et al. Longitudinal trajectory and characterization of cancer-related cognitive impairment in a nationwide cohort study. J Clin Oncol 2018:Jco2018786624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Von Ah D, Tallman EF. Perceived cognitive function in breast cancer survivors: evaluating relationships with objective cognitive performance and other symptoms using the functional assessment of cancer therapy-cognitive function instrument. J Pain Symptom Manage 2015;49:697–706. [DOI] [PubMed] [Google Scholar]
- 38.Crouch A, Von Ah D. Incidence and factors associated with attentional fatigue in working long-term breast cancer survivors. Clin Nurse Spec 2018;32:177–181. [DOI] [PubMed] [Google Scholar]
- 39.Klemp JR, Myers JS, Fabian CJ, et al. Cognitive functioning and quality of life following chemotherapy in pre- and peri-menopausal women with breast cancer. Support Care Cancer 2018;26:575–583. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Lehto RH, Cimprich B. Anxiety and directed attention in women awaiting breast cancer surgery. Oncol Nurs Forum 1999;26:767–772. [PubMed] [Google Scholar]
- 41.Cheng CT, Ho SMY, Liu WK, et al. Cancer-coping profile predicts long-term psychological functions and quality of life in cancer survivors. Support Care Cancer 2019;27:933–941. [DOI] [PubMed] [Google Scholar]
- 42.Hsiao FH, Kuo WH, Jow GM, et al. The changes of quality of life and their correlations with psychosocial factors following surgery among women with breast cancer from the post-surgery to post-treatment survivorship. Breast 2019;44:59–65. [DOI] [PubMed] [Google Scholar]
- 43.Kolokotroni P, Anagnostopoulos F, Hantzi A. The role of optimism, social constraints, coping, and cognitive processing in psychosocial adjustment among breast cancer survivors. J Clin Psychol Med Settings 2018;25:452–462. [DOI] [PubMed] [Google Scholar]
- 44.Wirkner J, Weymar M, Low A, et al. Cognitive functioning and emotion processing in breast cancer survivors and controls: An ERP pilot study. Psychophysiology 2017;54:1209–1222. [DOI] [PubMed] [Google Scholar]
- 45.Jung MS, Zhang M, Askren MK, et al. Cognitive dysfunction and symptom burden in women treated for breast cancer: a prospective behavioral and fMRI analysis. Brain Imaging Behav 2017;11:86–97. [DOI] [PubMed] [Google Scholar]
- 46.Yang Y, Hendrix CC. Cancer-Related Cognitive impairment in breast cancer patients: influences of psychological variables. Asia Pac J Oncol Nurs 2018;5:296–306. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.McCann B, Miaskowski C, Koetters T, et al. Associations between pro- and anti-inflammatory cytokine genes and breast pain in women prior to breast cancer surgery. J Pain 2012;13:425–437. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Miaskowski C, Cooper B, Paul SM, et al. Identification of patient subgroups and risk factors for persistent breast pain following breast cancer surgery. J Pain 2012; 13:1172–1187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Van Onselen C, Cooper BA, Lee K, et al. Identification of distinct subgroups of breast cancer patients based on self-reported changes in sleep disturbance. Support Care Cancer 2012;20:2611–2619. [DOI] [PubMed] [Google Scholar]
- 50.Karnofsky D Performance scale Factors that influence the therapeutic response in cancer: a comprehensive treatise. In: Plenum Press, New York, 1977. [Google Scholar]
- 51.Sangha O, Stucki G, Liang MH, Fossel AH, Katz JN. The Self-Administered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research. Arthritis Rheum 2003;49:156–163. [DOI] [PubMed] [Google Scholar]
- 52.Cimprich B Attentional fatigue following breast cancer surgery. Res Nurs Health 1992;15:199–207. [DOI] [PubMed] [Google Scholar]
- 53.Jansen CE, Dodd MJ, Miaskowski CA, Dowling GA, Kramer J. Preliminary results of a longitudinal study of changes in cognitive function in breast cancer patients undergoing chemotherapy with doxorubicin and cyclophosphamide. Psychooncology 2008;17:1189–1195. [DOI] [PubMed] [Google Scholar]
- 54.Spielberger CD. Manual for the State-Trait Anxiety Inventory STAI (form Y)(" self-evaluation questionnaire"). 1983. [Google Scholar]
- 55.Bieling PJ, Antony MM, Swinson RP. The State-Trait Anxiety Inventory, Trait version: structure and content re-examined. Behav Res Ther 1998;36:777–788. [DOI] [PubMed] [Google Scholar]
- 56.Kennedy BL, Schwab JJ, Morris RL, Beldia G. Assessment of state and trait anxiety in subjects with anxiety and depressive disorders. Psychiatr Q 2001;72:263–276. [DOI] [PubMed] [Google Scholar]
- 57.Carpenter JS, Andrykowski MA, Wilson J, et al. Psychometrics for two short forms of the Center for Epidemiologic Studies-Depression Scale. Issues Ment Health Nurs 1998;19:481–494. [DOI] [PubMed] [Google Scholar]
- 58.Radloff L Scale: A self-report depression scale for research in the general population. J Clin Exp Neuropsychol 1997;19:340–356.9268809 [Google Scholar]
- 59.Sheehan TJ, Fifield J, Reisine S, Tennen H. The measurement structure of the Center for Epidemiologic Studies Depression Scale. J Pers Assess 1995;64:507–521. [DOI] [PubMed] [Google Scholar]
- 60.Lee KA, Hicks G, Nino-Murcia G. Validity and reliability of a scale to assess fatigue. Psychiatry Res 1991;36:291–298. [DOI] [PubMed] [Google Scholar]
- 61.Dhruva A, Dodd M, Paul SM, et al. Trajectories of fatigue in patients with breast cancer before, during, and after radiation therapy. Cancer Nurs 2010;33:201–212. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Fletcher BS, Paul SM, Dodd MJ, et al. Prevalence, severity, and impact of symptoms on female family caregivers of patients at the initiation of radiation therapy for prostate cancer. J Clin Oncol 2008;26:599–605. [DOI] [PubMed] [Google Scholar]
- 63.Ferrell BR, Wisdom C, Wenzl C. Quality of life as an outcome variable in the management of cancer pain. Cancer 1989;63:2321–2327. [DOI] [PubMed] [Google Scholar]
- 64.Padilla GV, Presant C, Grant MM, et al. Quality of life index for patients with cancer. Res Nurs Health 1983;6:117–126. [DOI] [PubMed] [Google Scholar]
- 65.Kyranou M, Puntillo K, Dunn LB, et al. Predictors of initial levels and trajectories of anxiety in women before and for 6 months after breast cancer surgery. Cancer Nurs 2014;37:406–417. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Kyranou M, Puntillo K, Aouizerat BE, et al. Trajectories of depressive symptoms in women prior to and for six months after breast cancer surgery. J Appl Biobehav Res 2014;19:79–105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Henneghan A Modifiable factors and cognitive dysfunction in breast cancer survivors: a mixed-method systematic review. Support Care Cancer 2016;24:481–497. [DOI] [PubMed] [Google Scholar]
- 68.SPSS. IBM SPSS for Windows (Version 23), Armonk, NY: SPSS, Inc, 2015. [Google Scholar]
- 69.Raudenbush SW. Comparing personal trajectories and drawing causal inferences from longitudinal data. Annu Rev Psychol 2001;52:501–525. [DOI] [PubMed] [Google Scholar]
- 70.Raudenbush SW, Bryk AS. Hierarchical linear models: Applications and data analysis methods, Sage, 2002. [Google Scholar]
- 71.Langford DJ, Paul SM, Tripathy D, et al. Trajectories of pain and analgesics in oncology outpatients with metastatic bone pain during participation in a psychoeducational intervention study to improve pain management. J Pain 2011;12:652–666. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Miaskowski C, Paul SM, Cooper BA, et al. Predictors of the trajectories of self-reported sleep disturbance in men with prostate cancer during and following radiation therapy. Sleep 2011;34:171–179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Hartman SJ, Marinac CR, Natarajan L, Patterson RE. Lifestyle factors associated with cognitive functioning in breast cancer survivors. Psychooncology 2015;24:669–675. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Park JH, Jung YS, Jung YM, Bae SH. The role of depression in the relationship between cognitive decline and quality of life among breast cancer patients. Support Care Cancer 2018. [DOI] [PubMed] [Google Scholar]
- 75.Tometich DB, Small BJ, Carroll JE, et al. Pretreatment psychoneurological symptoms and their association with longitudinal cognitive function and quality of life in older breast cancer survivors. J Pain Symptom Manage 2019;57:596–606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Diaz-Venegas C, Downer B, Langa KM, Wong R. Racial and ethnic differences in cognitive function among older adults in the USA. Int J Geriatr Psychiatry 2016;31:1004–1012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Park MH, Smith SC, Neuburger J, et al. Sociodemographic characteristics, cognitive function, and health-related quality of life of patients referred to memory assessment services in england. Alzheimer Dis Assoc Disord 2017;31:159–167. [DOI] [PubMed] [Google Scholar]
- 78.Mujahid MS, Janz NK, Hawley ST, et al. Racial/ethnic differences in job loss for women with breast cancer. J Cancer Surviv 2011;5:102–111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Cheng ASK, Zeng Y, Liu X, et al. Cognitive challenges while at work and work output in breast cancer survivors employed in a rapidly evolving economy. J Cancer Surviv 2018;12:753–761. [DOI] [PubMed] [Google Scholar]
- 80.Utne I, Loyland B, Grov EK, et al. Co-occuring symptoms in older oncology patients with distinct attentional function profiles. Eur J Oncol Nurs 2019;41:196–203. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Patel SK, Wong AL, Wong FL, et al. Inflammatory biomarkers, comorbidity, and neurocognition in women with newly diagnosed breast cancer. J Natl Cancer Inst 2015;107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Mandelblatt JS, Stern RA, Luta G, et al. Cognitive impairment in older patients with breast cancer before systemic therapy: is there an interaction between cancer and comorbidity? J Clin Oncol 2014;32:1909–1918. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Zheng Y, Luo J, Bao P, et al. Long-term cognitive function change among breast cancer survivors. Breast Cancer Res Treat 2014;146:599–609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Lacourt TE, Heijnen CJ. Mechanisms of neurotoxic symptoms as a result of breast cancer and its treatment: Considerations on the contribution of stress, inflammation, and cellular bioenergetics. Curr Breast Cancer Rep 2017;9:70–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Ren X, Boriero D, Chaiswing L, et al. Plausible biochemical mechanisms of chemotherapy-induced cognitive impairment ("chemobrain"), a condition that significantly impairs the quality of life of many cancer survivors. Biochim Biophys Acta Mol Basis Dis 2019;1865:1088–1097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Wu LM, Amidi A. Cognitive impairment following hormone therapy: current opinion of research in breast and prostate cancer patients. Curr Opin Support Palliat Care 2017;11:38–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Bender CM, Merriman JD, Sereika SM, et al. Trajectories of cognitive function and associated phenotypic and genotypic factors in breast cancer. Oncol Nurs Forum 2018;45:308–326. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Williams AM, Shah R, Shayne M, et al. Associations between inflammatory markers and cognitive function in breast cancer patients receiving chemotherapy. J Neuroimmunology 2018;314:17–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Hermelink K, Voigt V, Kaste J, et al. Elucidating pretreatment cognitive impairment in breast cancer patients: the impact of cancer-related post-traumatic stress. J Natl Cancer Inst 2015;107. [DOI] [PubMed] [Google Scholar]
- 90.Henneghan A, Stuifbergen A, Becker H, Kesler S, King E. Modifiable correlates of perceived cognitive function in breast cancer survivors up to 10 years after chemotherapy completion. J Cancer Surviv 2018;12:224–233. [DOI] [PubMed] [Google Scholar]
- 91.Brinkman JE, Sharma S. Physiology, Sleep In: StatPearls, Treasure Island (FL): StatPearls Publishing StatPearls Publishing LLC., 2019. [Google Scholar]
- 92.Grandner MA. Sleep, health, and society. Sleep Med Clin 2017;12:1–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Kim HJ, Barsevick AM, Fang CY, Miaskowski C. Common biological pathways underlying the psychoneurological symptom cluster in cancer patients. Cancer Nurs 2012;35:E1–E20. [DOI] [PubMed] [Google Scholar]
- 94.Santos JC, Pyter LM. Neuroimmunology of behavioral comorbidities associated with cancer and cancer treatments. Front Immunol 2018;9:1195. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Berman MG, Askren MK, Jung M, et al. Pretreatment worry and neurocognitive responses in women with breast cancer. Health Psychol 2014;33:222–231. [DOI] [PubMed] [Google Scholar]
- 96.Vardy JL, Stouten-Kemperman MM, Pond G, et al. A mechanistic cohort study evaluating cognitive impairment in women treated for breast cancer. Brain Imaging Behav 2019;13:15–26. [DOI] [PubMed] [Google Scholar]
- 97.Peng YN, Huang ML, Kao CH. Prevalence of depression and anxiety in colorectal cancer patients: A literature review. Int J Environ Res Public Health 2019;16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Guimond AJ, Ivers H, Savard J. Is emotion regulation associated with cancer-related psychological symptoms? Psychol Health 2019;34:44–63. [DOI] [PubMed] [Google Scholar]
- 99.Levkovich I, Cohen M, Alon S, et al. Symptom cluster of emotional distress, fatigue and cognitive difficulties among young and older breast cancer survivors: The mediating role of subjective stress. J Geriatr Oncol 2018;9:469–475. [DOI] [PubMed] [Google Scholar]
- 100.Wang AW, Bouchard LC, Gudenkauf LM, et al. Differential psychological effects of cognitive-behavioral stress management among breast cancer patients with high and low initial cancer-specific distress. J Psychosom Res 2018;113:52–57. [DOI] [PMC free article] [PubMed] [Google Scholar]