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Journal of Occupational & Environmental Medicine:
doi: 10.1097/JOM.0b013e3181d0bef7
Original Articles

Measures of Cognitive Function and Work in Occupationally Active Breast Cancer Survivors.

Calvio, Lisseth PhD; Peugeot, Mark MS; Bruns, Gina L. MA; Todd, Briana L. MA; Feuerstein, Michael PhD, MPH

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Article Outline
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Author Information

From the Department of Medical and Clinical Psychology (Dr Calvio, Mr Peugeot, Ms Bruns, Ms Todd, Dr Feuerstein), Uniformed Services University of the Health Sciences, Bethesda, Md; Department of Psychology (Ms Bruns), American University, Washington, DC; and Department of Psychiatry (Dr Feuerstein), Georgetown University Medical Center, Washington, DC.

The opinions and assertions contained herein are the private views of the authors and are not to be construed as being official or as reflecting the views of the Uniformed Services University of the Health Sciences or the Department of Defense.

Address correspondence to: Michael Feuerstein, PhD, MPH, Department of Medical and Clinical Psychology and Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814; E-mail: mfeuerstein@usuhs.mil.

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Abstract

Objective: This study investigated performance-based and patient-reported cognitive limitations on work output.

Methods: Working breast cancer survivors (BCS) (n = 122) and a non-cancer comparison group (NCCG; n = 113) completed measures of cognitive function, fatigue, distress, job stress, and work output.

Results: Distress, fatigue, and job stress were higher in the BCS group who were on average 3-years post-treatment. Patient-reported cognitive limitations at work were related to work output in BCS (memory β = 0.29; executive function β = 0.26) only. Changes in work output were more responsive to changes in job stress and fatigue in the BCS group.

Conclusions: Reports of cognitive problems at work should be carefully followed up.

Work is an important aspect of life for many cancer survivors.1 The majority of breast cancer survivors (BCS) are employed post-cancer diagnosis and treatment.2 In a study of 253 heterogeneous cancer survivors, Bradley and Bednarek3 found approximately 39% of BCS worked several years post-cancer diagnosis. One study found that 79% of previously working BCS were employed at 3-years post-treatment compared with 85% employment in a comparison group.4 In both groups, the majority of those unemployed (84% of BCS and 76% of comparison) stated that the decision to stop working was their own. Consistently, it has been observed that up to 13% of a heterogeneous group of cancer survivors, of which breast cancer was among the majority, ceased work within 4 years of diagnosis for unspecified “cancer-related reasons.”5

A recent qualitative study of cognitive challenges in working BCS investigated the work experience 1 to 10 years post-diagnosis.6 Survivors reported having difficulties with “feeling stressed out,” coping, and concentrating at their jobs when they returned to work. Approximately one third of participants indicated that they felt their employers or coworkers had high expectations of them on returning to work. An investigation of differences in patterns of alleged workplace discrimination represents another source of stress. A study on approximately 60,000 Americans Disability Act claims in the United States over a 6-year period indicated that disputes in the areas of “termination” and “terms and conditions” were more likely in cancer survivors than other protected groups.7 Although identification of specific cancer types was not possible, the findings suggest that friction between the workplace and cancer survivor was sufficient to justify filing a claim.

A subgroup of BCS report symptoms such as fatigue post-primary treatment.8,9 For example, 34% of BCS experience significant fatigue 5 to 10 years post-diagnosis.8 Symptoms of fatigue, depressive or anxious mood, pain, and changes in cognitive function such as working memory, executive functioning, organization, and multitasking have been observed.10–13 These symptoms often occur as a cluster.14 Research on BCS has demonstrated that these symptoms are related to variations in work output15 3 years post-primary treatment. There is often a need to better manage these symptoms as they can persist for years after primary treatment.9,16

Meta-analytic reviews indicate that BCS who have undergone chemotherapy experience lower levels of memory, language, spatial abilities, motor function, processing speed, and executive function17,18 than non-cancer comparison groups (NCCG). The cause of this difference, however, is not currently understood and in need of further research.19 A recent qualitative study of BCS indicated that cognitive impairment can be troublesome in the context of work.20 In fact, many of the BCS interviewed stated that cognitive limitations are their most problematic post-treatment symptom. They further reported that their cognitive limitations interfered with their daily functioning and that they needed to create personal strategies (eg, using a calendar or journal to record upcoming tasks) to manage these cognitive limitations at work. There is a greater attenuation in work ability in certain types of cancer, including breast cancer.21 Evidence exists that differences in cognitive function can be observed in BCS up to 10 years post-treatment when compared with an NCCG.22,23 A wide range of BCS (ie, 16% to 75%) experience cognitive limitations,24 although when using pre- and post-treatment evaluation data to determine cognitive changes, the range decreases (to 13% to 34% of BCS).25 To date, the research on cognitive function in BCS have concluded: 1) although the magnitude of the cognitive limitations are observed to decrease as time from cancer diagnosis or treatment increases, these changes can persist at some level for many years; 2) cognitive symptoms can interact with other measures of symptom burden such as fatigue,26,27 mood,13 and pain28; and 3) performance-based measures of cognitive function, despite their position as the “gold standard” for the evaluation of classic brain injury, often do not correlate with perceived cognitive function of the cancer survivors themselves.29

In efforts to develop approaches to optimize work ability in occupationally active BCS, it may be useful to model specific relationships among these long-term symptoms and function at work. Also from an occupational health perspective, type of job, work history, job satisfaction, and level of job stress may be confounding factors that need to be controlled for in such analyses. It should be emphasized that this research is focused on those BCS who desire to remain in or return to the workforce post-diagnosis and treatment. A relationship among symptom burden including perceived work-related cognitive limitations and work limitations has been observed in occupationally active BCS working for a minimum of 3 years post-primary treatment.15 This earlier research did not include the current “gold standard” measure of cognitive function; neuropsychological testing.30 To date, the relationship between cognitive limitations and work limitations in BCS has been based exclusively on the perception of cognitive limitations in the context of work. The perceived limitations reported by affected workers themselves are sometimes considered less objective than performance-based tests. Clinical research directed at optimizing work function in BCS could benefit from an assessment of cognitive function that is related to work productivity.

This study is an investigation of the relationship between perceived cognitive function (ie, working memory, executive function, and attention) at work and more generic performance-based neuropsychological measures of these functions and work output in occupationally active BCS. Demographic, non-cognitive measures of reported symptom burden and situational factors that can influence scores on performance measures were accounted for in this investigation. It was hypothesized that cancer survivor reports of cognitive problems in the context of work would be associated with work output to a greater degree than performance-based measures of generic neuropsychological function.

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METHODS

Case Definition
Breast Cancer Participants

Inclusion criteria for this group consisted of female BCS, between the ages of 18 and 65, who were working full-time for a minimum of 1 year before the study. BCS were at least 1 year, but not more than 10 years, from completion of primary treatment (surgery, chemotherapy, radiation therapy, or a combination of treatments). BCS of all races and ethnicities were recruited. The participants had computer and Internet access and usage. Participants were required to have Internet speed higher than dial-up to proceed with study.

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Non-Cancer Control Group

The comparison group consisted of females of working age (18 through 65 years old) who never received a diagnosis of any type of cancer. All races and ethnicities were recruited for the NCCG. Participants were working at the time of assessment and had computer and Internet access. Participants were required to have Internet speed higher than dial-up to proceed with study.

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Exclusion Criteria

Exclusion criteria for both groups were history of a diagnosis of dementia, brain injury, adult attention deficit hyperactivity disorder (ADHD), epilepsy, drug or alcohol abuse, or metastasic cancer.

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Recruitment

BCS and the NCCG were recruited by advertisements and flyers. Different advertisements and flyers were used to recruit each group. Advertisements and flyers were placed at cancer clinics/centers and primary care clinics across the United States, support groups, hospital bulletin boards, newspaper advertisements, and websites. All study participants used a web-based interface. The data analysis was conducted using SPSS version 16.0,31 and data were stored at the Uniformed Services University of the Health Sciences. All participants were asked to complete a series of questions related to demographics, patient-reported cognitive limitations, anxiety, depression, fatigue, and work output. Participants were randomized to receive either the performance-based cognitive tests followed by the perceived cognitive function measures or the reverse order. The Uniformed Services University of the Health Sciences Internal Review Board approved this protocol.

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Measures
Demographics, Medical, and Work Status

Participants completed questions regarding demographics that included information on ethnicity, race, age, marital status, and education. Medical questions included location of tumor, stage of tumor, treatment received (ie, surgery, radiation, chemotherapy), time elapsed since completion of primary treatment, medications, menopausal status, and the presence of any pain.32 Medical questions were asked in a patient-reported survey because the data collection process was done in a non-clinical context and we were unable to confirm information against medical records. It has been demonstrated that patient-reported medical treatment of breast cancer is accurate when compared to medical charts,33 however, the other measures that describe stage might be subject to bias and therefore were not used beyond describing the sample. Work-related questions, including type of occupation, average number of hours worked per week, job stress, and number of sick days in the past year, were also obtained.

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Distress
Hospital Anxiety and Depression Scale (HADS)

The HADS34 is a self-assessment scale for measuring depression and anxiety in a general medical population. The HADS consists of 14 items on two subscales, one measuring Anxiety (A-scale) and one measuring Depression (D-scale), which are scored separately. The HADS has been found to adequately assess depression and anxiety in cancer patients35 and has been used to evaluate depression and anxiety symptoms in the cancer population.29,36 The HADS has high concurrent validity with the Beck Depression Inventory and State-Trait Anxiety Inventory and is effective in detecting anxiety and depressive symptoms in non-medical and medical samples.37 The HADS was included as a measure of current depression and anxiety.

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Fatigue
The Multidimensional Fatigue Symptom Inventory—Short Form Physical Fatigue (MFSI-SF)

The MFSI-SF38 is a 30-item self-report measure of fatigue encompassing five symptom domains: general fatigue, physical fatigue, emotional fatigue, mental fatigue, and vigor. Depression can contribute to fatigue and may impact perceived measurement of fatigue.39 In an effort to control for redundancy of measurement (eg, components of emotional and mental fatigue being captured by the depression measure) and reduce collinearity, only the MFSI-SF physical fatigue subscale was used in the present study.

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Visual Analog Scale of Fatigue at Work

A 10-centimeter Visual Analog Scale (VAS) with anchors “I do not feel tired at all” to “I feel completely exhausted” was created and used as a simple measure of general fatigue on a “typical workday.” VAS scales have been used to measure a wide range of subjective phenomena reliably and validly.40 Research has further shown that a VAS fatigue scale is a better indicator of fatigue than a multi-item Likert scale.41

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Stress At Work
Job Stress (Behavioral Risk Factor Survey)

Because the ADA claims data from a previous study we conducted suggested7 that friction at work may be present in the workplace of certain cancer survivors and it is well known that stress is associated with cognitive function42 and work output6 job stress was measured. To minimize participant burden, only one question from the Behavioral Risk Factor Surveillance Survey43 was included to assess job stress. This single item asks the participant to rate how often (never, seldom, sometimes, or often) they think their current work situation puts them under too much stress. This measure has been used previously in cancer survivor and work studies.15,44

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Caffeine, Nicotine, and Alcohol Use Before Testing

Caffeine, nicotine, or alcohol use can influence cognitive performance.45–47 Self-report of use before completing the neuropsychological test was assessed. Caffeine ingestion before the completion of the cognitive performance test was obtained from the caffeine consumption questionnaire (accessed online from http://www.drkeddy.com/client/caffeine.pdf). The Behavioral Risk Factor Surveillance System Questionnaire (accessed online from: http://www.cdc.gov/NCHS/data/nhanes/nhanes_01_02/sp_smq.pdf), provided the items to measure time since consumption and amount of alcohol and onset of performance-based neuropsychological assessment.48

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Self-Reported Cognitive Function
Perceived Cognitive Function: Cognitive Symptoms Checklist-Modified

The Cognitive Symptoms Checklist (CSC) was developed for use as a self-report measure of cognitive symptoms in the context of work tasks.49 The original CSC format was modified into a dichotomous discrimination (ie, problem/no problem) asking whether the participant indicated that a certain cognitive function was a problem for them at work.15 In a previous study,15 the modified CSC was factor analyzed and three factors emerged. The factors and their current internal consistency are as follows: working memory (Cronbach α = 0.93), executive functioning (Cronbach α = 0.91), and attention (Cronbach α = 0.86) sub-scales.

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Performance-Based Cognitive Function: Central Nervous System Vital Signs (CNSVS)

The CNSVS is a computerized neurocognitive battery that measures memory, psychomotor speed, reaction time, complex attention, and cognitive flexibility administered over the Internet. The overall battery is comprised of several well-established neuropsychological tests, such as finger tapping, digit symbol coding, the Stroop test, and a continuous performance test. The subscales have good test-retest reliability: attention (r = 0.65), memory (r = 0.66), psychomotor speed (r = 0.88), cognitive flexibility (r = 0.71), and reaction time (r = 0.75).50 The test has been validated with a normative sample and has been used to detect mild to moderate cognitive impairments in patients with mild and severe brain injury, early dementia, postconcussion syndrome, attention deficit hyperactivity disorder (ADHD), and depression.50 The subtests used were memory (verbal memory test and visual memory test), executive function/cognitive flexibility (shifting attention test), and attention (continuous performance test). The CNSVS used in this study typically required less than 30 minutes to complete. Scores are available as raw score, standardized score, percentile, and by performance categories.51

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Outcome
Work Limitations Questionnaire (WLQ)

There is currently no “gold standard” measure of work limitations or work output. Evaluation of the self-reported measures of work productivity concluded that the WLQ is comparable to other perceived and observed measures and is one of the more extensively reviewed and implemented measures.52 The WLQ has been used with several medical populations,53 including working BCS.15 Prasad et al54 reviewed 12 measures of work productivity and concluded that the WLQ provided an accurate assessment of the role of a worker's health on labor productivity.54 The WLQ has been validated against performance-based measures of work output with 800 telephone operators and 120 warehouse personnel. These studies found that the WLQ was related to quantitative measures of work output/productivity.55–57

The WLQ is composed of subscales for time, physical, mental-interpersonal, and output demands. The time demands, mental-interpersonal demands, and physical demands scales measure the degree to which these factors have made it difficult to perform specific job demands.51 The output scale has predicted actual quantitative productivity loss and has the highest internal consistency (Cronbach α = 0.9) of all four scales. The output scale was used as the outcome of interest.

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Statistical Analyses

The purpose of the analyses were to 1) identify differences in socio-demographic factors between the BCS and the NCCG; 2) determine if there were differences between the two groups on the symptom burden and job stress measures including the patient-reported and performance-based measures of cognitive function; and 3) determine whether there were group differences in the relationship between the perceived measures of cognitive limitations and performance-based measures of cognitive function and work output accounting for the role of confounders.

χ2 and t tests were conducted to determine any differences in demographics between the BCS and the NCCG. Group differences in the symptom burden and job stress measures were assessed with a multivariate Hotelling T-squared test. The Hotelling T-squared test allowed us to examine the multivariate and univariate differences in the symptom burden and job stress measures between the two groups.

A series of three-step linear regressions were conducted to examine the contribution of symptom burden as well as patient-reported and performance-based cognitive limitations to work output. We conducted three regressions including the patient-reported cognitive limitations: BCS alone, NCCG alone, or all participants. We also conducted three regressions including the performance-based cognitive measures: BCS alone, NCCG alone, or all participants. Due to the large number of potential confounders and power limitations, a systematic variable reduction technique was employed.15

This analysis was conducted in two parts. The first analysis consisted of a series of univariate linear regressions for each potential confounder (ie, age, education level, race, ethnicity, marital status, menopausal status, years at current job, primary occupation, job satisfaction, job stress, measures of fatigue in general and at work, pain severity, depressive and anxiety symptoms, substance use prior to/during the test, distracters during the test, and Internet speed). For the second step, all variables that met the P < 0.10 criteria from this initial analysis were entered into the final multivariate regression models. The dependent variable for both the data reduction regression and the final regressions was the output demands scale of the WLQ.

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RESULTS

Participants

A total of 281 participants were invited to complete the study after a screening determined that they met the requirements for the study. Two hundred thirty-five participants (84%) successfully completed both the survey and neuropsychological testing and are included in the following analyses. The sample consisted of 122 BCS and 113 NCCG participants.

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Demographics

There were differences in demographics between the BCS and the NCCG as indicated in Table 1 (N = 235). Specifically, the t tests and χ2 analyses indicated that the BCS were older (M = 44.88, SD = 9.51) than the NCCG participants (M = 39.18, SD = 11.87). In addition, a greater number of BCS were white in contrast to other races (χ2 = 16.88, df = 3, P < 0.01). A difference in ethnicity between the two groups was also detected with non-Hispanics being disproportionately higher in the BCS group (χ2 = 5.92, df = 1, P < 0.05) than in the NCCG. BCS were more likely to be married (χ2 = 10.16, df = 4, P < 0.01). The NCCG were more likely to be pre-menopausal as compared to the BCS who were more likely to be currently going through menopause or be postmenopausal (χ2 = 5.06, df = 2, P < 0.001).

Table 1
Table 1
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χ2 analyses of current job characteristics, primary occupation, years in current employment, and job satisfaction showed no significant differences between the two groups. It was only in household income where a significant difference was detected (χ2 = 18.89, df = 6, P < 0.01). BCS were more likely to report an annual household income of $100,000 or more as compared to the NCCG. The group difference in income is most likely an artifact of the significantly greater number of BCS married and/or cohabitating with a partner.

Due to the observed differences in marital status, race, ethnicity, age, income, and menopausal status, these variables were controlled for when determining group differences in symptom burden, job stress, and patient-reported and performance-based cognitive limitations.

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Clinical Descriptors and Treatment Exposures

As indicated in Table 2, BCS on average were 3.09 years post-primary treatment. Within the study, BCS with stage II tumors (44%) were the most prevalent group followed by stage I (37%) and finally stage III (17%). Nearly all BCS underwent surgery (97%) and most had chemotherapy (83%) and radiation treatment (73%).

Table 2
Table 2
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Symptom Burden and Job Stress

A multivariate analysis of covariance was performed controlling for marital status, race, ethnicity, age, income, and menopausal status. As Table 3 indicates, BCS reported higher levels of symptom burden and job stress. An overall significant difference was detected between the two groups (F[14,214] = 6.64, P < 0.001). Significant differences were detected in anxiety-related symptoms (F[1,227] = 7.22, P < 0.01), depressive symptoms (F[1,227] = 12.54, P < 0.001), fatigue-MFSI-SF (F[1,227] = 39.85, P < 0.001), fatigue-VAS (F[1,227] = 20.70, P < 0.001), pain (F[1,227] = 5.50, P < 0.05), and job stress (F[1,227] = 5.40, P < 0.05). Patient-reported work-related memory difficulties (F[1,227] = 58.27, P < 0.001), attention (F[1,227] = 11.98, P < 0.01), and executive functioning (F[1,227] = 29.18, P < 0.001) were also greater in BCS. There were also significant differences detected between the two groups on the performance-based measure of attention (F[1,227] = 4.90, P < 0.05). Unexpectedly, the BCS demonstrated higher functioning than the NCCG on this subtest.

Table 3
Table 3
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Cognitive Measures and Work Output

Two independent linear regressions were conducted for each group to determine the ability of symptom burden and either patient-reported or performance-based measures of cognitive limitations to predict the work output score of the WLQ. The three parts of the model included 1) covariates, 2) symptom burden, and 3) cognitive limitations, which were measured by a performance-based test or a patient-reported instrument.

The covariates included all variables that met the P < 0.10 criteria in the above-mentioned univariate analyses. As demonstrated in Tables 4 and 5, for BCS alcohol use the day of the test (β = 0.18, P < 0.05) was a significant confounder in both models.

Table 4
Table 4
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Table 5
Table 5
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The second portion of the regression analyses examined the impact that symptom burden had on the models. As Tables 4 and 5 demonstrate, for BCS job stress (β = 0.29, P < 0.01) was the only significant factor in this step. In the NCCG, the second step only indicated that depressive symptoms (β = 0.25, P < 0.05) significantly contributed to work output limitations. For the NCCG, symptom burden accounted for less of the total models' variances (R2 change = 0.21, P < 0.001) than symptom burden did for the BCS (R2 change = 0.34, P < 0.01).

The third step of the regression analyses examined how much variance was explained by measurements of perceived or performance-based cognitive limitations. As seen in Table 4, the CSC patient-reported measure accounted for a significant portion of the total variance in the BCS (R2 change = 0.16, P < 0.001) but not for the NCCG (R2 change = 0.05, P = n.s.). Overall, these regression models including patient-reported limitations accounted for 55.8% of the variance in the BCS and 30.7% of the variance in the NCCG when all steps in model were considered. As indicated in Table 5, the performance-based measures of cognitive performance accounted for a significant portion of the total variance for the NCCG (R2 change = 0.09, P < 0.05) but not for the BCS (R2 change = 0.02, P = n.s.). Overall, when all steps in the models were considered, performance-based limitations accounted for 41.7% of the variance in the BCS and 33.9% of the variance in the NCCG.

Finally, two three-step regressions were completed for the entire sample combined. One regression examined the contribution of patient-reported cognitive limitations whereas the other regression considered performance-based cognitive testing. As seen in Table 6, the regression for patient-reported cognitive limitations explained 50% of the variance in work output limitations (R2 = 0.50, P < 0.001) with the following factors as main effects: alcohol today (β = 0.17, P < 0.01), group (β = −0.12, P < 0.05), job stress (β = 0.19, P < 0.01), HADS depression score (β = 0.15, P < 0.05), VAS fatigue (β = −0.15, P < 0.05), CSC memory (β = 0.29, P < 0.01), and CSC executive function (β = 0.17, P < 0.05). The regression for the performance-based cognitive limitations explained 39% of the variance in work limitations (R2 = 0.39, P < 0.001) with the following factors as main effects: alcohol today (β = 0.17, P < 0.01), group (β = −0.12, P < 0.05), job stress (β = 0.19, P < 0.01), HADS depression score (β = 0.15, P < 0.05), VAS fatigue (β = −0.15, P < 0.05), and CNSVS executive function (β = −0.18, P < 0.05).

Table 6
Table 6
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Group x Symptom Burden on Work Output

Interaction terms were created for the significant main effects of the symptom burden, patient-reported cognitive limitations, and the performance-based cognitive subtest found in the two three-step regressions for the total sample combined. The group by job stress (β = −0.55, P < 0.01) and the group by VAS fatigue (β = −0.45, P < 0.05) interactions were significant. Figures 1 and 2 indicate that a relationship between work output limitations and fatigue and work output limitations and job stress exists in both groups. However, in both relationships, the interactions depict a steeper slope for the BCS indicating a more rapid decrease in work output related to an increase in both job stress and fatigue.

Figure 1
Figure 1
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Figure 2
Figure 2
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DISCUSSION

BCS, on average 3-years post-diagnosis, reported higher levels than the NCCG of anxiety-related and depressive symptoms, fatigue, pain, and job stress. BCS also endorsed higher levels of cognitive difficulties, yet performed better on a measure of attention than the NCCG. When taking into account group differences in symptom burden, patient-reported cognitive limitations predicted work output in BCS only, whereas performance-based cognitive function predicted work output in the NCCG only. Further, job stress and fatigue were more strongly related to work output in BCS than in the NCCG.

This study's finding that occupationally active BCS reported higher levels of patient-reported cognitive limitations than a NCCG is consistent with past research.15,58 Of interest is the finding that on performance-based measures of attention BCS demonstrated a higher score on attention than the NCCG. Attention is one of the most commonly reported cognitive limitations in cancer survivors.59 Nevertheless, a meta-analysis, which examined studies measuring attention in BCS who had received chemotherapy found that there was not a significant effect of chemotherapy on attention.17 Perhaps, cancer survivors try to compensate for their perceived attention difficulties during performance-based testing by putting forth more effort. Although this hypothesis could account for our findings, future research is needed for confirmation.

There was a clear difference between the performance-based and the patient-reported outcome measures of cognitive function in their ability to explain the variance in work output. The NCCG's performance-based testing results were consistently related to work output whereas their self-report was not. On the other hand, survivors' ratings of the impact of cognitive limitations were consistently related to work output while performance-based measures were not. This difference provides further evidence that these two types of measures are not recording the same dimensions of cognitive function and are not related to work output in a consistent way. The results are also consistent with research that indicates a poor relationship between performance-based and patient-reported measures of cognitive function in BCS.58 Although the outcome of interest was self-reported work output and self-report measures are typically highly correlated with one another, the work limitation measure has been validated against observed work performance.55–57

There is no gold standard for the measurement of cognitive function in cancer survivors.19 Problems experienced with cognitive function and their relationship to operations required of work in survivors may escape detection by traditional performance-based methods. Rather than simply dismissing cognitive problems, these findings indicate that the reports of occupationally active BCS should initiate a serious exploration of the exact nature of the problem and active approaches to reduce the impact of these cognitive problems at work. Future research needs to be focused on development of work-based approaches to address this problem.

These findings also question the clinical wisdom of using traditional performance-based neuropsychological measures to help address BCS' reported challenges at work. There is a need for validated measures that are in fact related to work. Perhaps, the use of innovative measurement approaches will provide a more sensitive index of cognitive function at work.60 Even clinic-based evaluation of functional brain activity may provide useful discrimination of work-related cognitive problems (eg, fMRI61). The study of differential methods for evaluating cognitive function and their relation to dynamic work processes represent a potentially fruitful area for further investigation. The higher scores in BCS on attention is puzzling, however, this finding provides evidence that the performance-based measures are not consistent with reported variations in work function. This observation would benefit from additional research on the validity of these performance-based measures in the context of ongoing work.

Symptoms of depression and anxiety in all participants were below the established clinical cut offs for these measures.34 The cancer survivors had higher levels of depressive symptoms than those working without a history of cancer, yet it was job stress and fatigue that were more strongly related to work output in BCS. The work-related VAS fatigue measure was more sensitive than the more generic physical fatigue scale (MFSI-SF) in cancer survivors as it related to work output.62 This finding provides further support that the more specific to the actual task the assessment is, the more valid the evaluation. The two-way interactions indicate that job stress and fatigue are related to work output in both groups although the BCS work output was more responsive (ie, steeper slope) to higher levels of both. Earlier detection and management of job stress and fatigue may improve work output. Such an implication of the current findings requires specific study.

The cross-sectional design of this study prevents determination of specific causal pathways linking job stress and fatigue to work output. The findings must also be considered in the context of potential sources of bias. Selection bias is a possibility in a web-based study, though it may not be as great as it was earlier thought to be.63 With regard to the BCS group, diagnoses and treatment exposures were consistent with data obtained from the medical records of BCS.64 The figures for treatment are similar to what was seen in an earlier study15 and what is observed in BCS in general.65 The Internet-based neuropsychological testing methods used have been determined to be valid measures of generic cognitive processes when compared to traditional neuropsychological tests.50 Other potential confounders of the web-based evaluation such as Internet speed, smoking, and alcohol use before evaluation were also accounted for in the analyses.

A formal evidence-based model of the complex relationship among cognitive limitations, other long-term or late symptoms, and workplace factors needs to be developed to help guide future research and practice in this area.66 This study supports the need for more specific information describing how job stress and fatigue affect cognitive function at work, and consequently work productivity. Investigation of the potential biobehavioral mechanisms such as psycho-neuroendocrine processes underlying these relationships67,68 may prove helpful in the search for future approaches that can improve long-term symptom burden and optimize work productivity.66 Until such knowledge is generated and can be applied in the occupational setting, health care providers and supervisors should attend to reported cognitive function. Quality clinical management of these cases require consideration of the association among perceived cognitive function, job stress, and fatigue on overall work output in occupationally active BCS.

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ACKNOWLEDGMENTS

The authors thank Andrew J. Saykin, PsyD, for his thoughtful input, David Cella, PhD, for use of the FACT-Cognitive Function measure and scoring, and Cara Olsen, MS, DrPH for her guidance.

This research was supported by the Cancer Survivorship Fund, Henry M Jackson Foundation, and USUHS.

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REFERENCES

1. Amir Z, Neary D, Luker K. Cancer survivors' views of work 3 years post diagnosis: a UK perspective. Eur J Oncol Nurs. 2008;12:190–197.

2. de Boer AGEM, Taskila T, Ojajarvi A, van Dijk FJH, Verbeek JHAM. Cancer survivors and unemployment: a meta-analysis and meta-regression. JAMA. 2009;301:753–762.

3. Bradley CJ, Bednarek HL. Employment patterns of long-term cancer survivors. Psychooncology. 2002;11:188–198.

4. Maunsell E, Drolet M, Brisson J, Brisson C, Masse B, Deschenes L. Work situation after breast cancer: results from a population-based study. J Natl Cancer Inst. 2004;96:1813–1822.

5. Short PF, Vasey JJ, Tunceli K. Employment pathways in a large cohort of adult cancer survivors. Cancer. 2005;103:1292–1301.

6. Kennedy F, Haslam C, Munir F, Pryce J. Returning to work following cancer: a qualitative exploratory study into the experience of returning to work following cancer. Eur J Cancer Care (Engl). 2007;16:17–25.

7. Feuerstein M, Luff GM, Harrington CB, Olsen CH. Pattern of workplace disputes in cancer survivors: a population study of ADA claims. J Cancer Surviv. 2007;1:185–192.

8. Bower JE, Ganz PA, Desmond KA, et al. Fatigue in long-term breast carcinoma survivors: a longitudinal investigation. Cancer. 2006;106:751–758.

9. Helgeson V, Tomich P. A comparison of 5-year disease-free breast cancer survivors with healthy women. Psychooncology. 2005;14:307–317.

10. Gandubert C, Carriere I, Escot C, et al. Onset and relapse of psychiatric disorders following early breast cancer: a case-control study. Psychooncology. 2009;18:1029–1037.

11. Wefel JS, Lenzi R, Theriault RL, Davis RN, Meyers CA. The cognitive sequelae of standard-dose adjuvant chemotherapy in women with breast carcinoma: results of a prospective, randomized, longitudinal trial. Cancer. 2004;100:2292–2299.

12. Wagner LI, Cella D. Fatigue and cancer: causes, prevalence and treatment approaches. Br J Cancer. 2004;91:822–828.

13. Deimling GT, Bowman KF, Sterns S, Wagner LJ, Kahana B. Cancer-related health worries and psychological distress among older adult, long-term cancer survivors. Psychooncology. 2006;15:306–320.

14. Finnegan L, Campbell R, Ferrans C, Wilbur J, Wilkie D, Shaver J. Symptom cluster experience profiles in adult survivors of childhood cancers. J Pain Symptom Manag. 2009;38:258–269.

15. Hansen J, Feuerstein M, Calvio LC, Olsen C. Breast cancer survivors at work. J Occup Environ Med. 2008;50:777–784.

16. Mao JJ, Armstrong K, Bowman MA, Xie SX, Kadakia R, Farrar JT. Symptom burden among cancer survivors: impact of age and comorditiy. J Am Board Fam Med. 2007;20:434–443.

17. Stewart A, Bielajew C, Collins B, Parkinson M, Tomiak E. A meta-analysis of the neuropsychological effects of adjuvant chemotherapy treatment in women treated for breast cancer. Clin Neuropsychol. 2006;20:76–89.

18. Falleti MG, Sanfilippo A, Maruff P, Weih L, Phillips KA. The nature and severity of cognitive impairment associated with adjuvant chemotherapy in women with breast cancer: a meta-analysis of the current literature. Brain Cogn. 2005;59:60–70.

19. Vardy J, Wefel JS, Ahles TA, Tannock IF, Schagen SB. Cancer and cancer-therapy related cognitive dysfunction: an international perspective from the Venice cognitive workshop. Ann Oncol. 2008;19:623–629.

20. 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.

21. Munir F, Yarker J, McDermmot H. Employment and the common cancers: correlates of work ability during or following cancer treatment. Occup Med (Lond). 2009;59:381–389.

22. Silverman DHS, Dy CJ, Castellon SA, et al. Altered frontocortical, cerebellar, and basal ganglia activity in adjuvant-treated breast cancer survivors 5–10 years after chemotherapy. Breast Cancer Res Treat. 2007;103:303–311.

23. Ahles TA, Saykin AJ, Furstenberg CT, et al. Neuropsychologic impact of standard-dose systemic chemotherapy in long-term survivors of breast cancer and lymphoma. J Clin Oncol. 2002;20:485–493.

24. Bower JE. Behavioral symptoms in patients with breast cancer and survivors. J Clin Oncol. 2008;26:768–777.

25. Wefel JS, Witgert ME, Meyers CA. Neuropsychological sequelae of non-central nervous system cancer and cancer therapy. Neuropsychol Rev. 2008;18:121–131.

26. Fan HG, Houede-Tchen N, Yi QL, et al. Fatigue, menopausal symptoms, and cognitive function in women after adjuvant chemotherapy for breast cancer: 1- and 2-year follow-up of a prospective controlled study. J Clin Oncol. 2005;23:8025–8032.

27. Valentine AD, Meyers CA. Cognitive and mood disturbance as causes and symptoms of fatigue in cancer patients. Cancer. 2001;92(6 Suppl):1694–1698.

28. Roth RS, Geisser ME, Theisen-Goodvich M, Dixon PJ. Cognitive complaints are associated with depression, fatigue, female sex, and pain catastrophizing in patients with chronic pain. Arch Phys Med Rehabil. 2005;86:1147–1154.

29. Poppelreuter M, Weis J, Kulz AK, Tucha O, Lange KW, Bartsch HH. Cognitive dysfunction and subjective complaints of cancer patients. a cross-sectional study in a cancer rehabilitation centre. Eur J Cancer. 2004;40:43–49.

30. Tannock IF, Ahles TA, Ganz PA, Van Dam FS. Cognitive impairment associated with chemotherapy for cancer: report of a workshop. J Clin Oncol. 2004;22:2233–2239.

31. SPSS for Windows, Rel. 17.0.0. Chicago: SPSS Inc.; 2008.

32. Scott J, Huskisson EC. Vertical or horizontal visual analogue scales. Ann Rheum Dis. 1979;38:560.

33. Maunsell E, Drolet M, Ouhoummane N, Robert J. Breast cancer survivors accurately reported key treatment and prognostic characteristics. J Clin Epidemiol. 2005;58:364–369.

34. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67:361–370.

35. Hopwood P, Howell A, Maguire P. Screening for psychiatric morbidity in patients with advanced breast cancer: validation of two self-report questionnaires. Br J Cancer. 1991;64:353–356.

36. Spiegel D, Giese-Davis J. Depression and cancer: mechanisms and disease progression. Biol Psychiatry. 2003;54:269–282.

37. Michopoulos I, Douzenis A, Kalkavoura C, et al. Hospital Anxiety and Depression Scale (HADS): validation in a Greek general hospital sample. Ann Gen Psychiatry. 2008;7:4.

38. Stein KD, Jacobsen PB, Blanchard CM, Thors C. Further validation of the multidimensional fatigue symptom inventory-short form. J Pain Symptom Manage. 2004;27:14–23.

39. Jean-Pierre P, Figueroa-Moseley CD, Kohli S, Fiscella K, Palesh OG, Morrow GR. Assessment of cancer-related fatigue: implications for clinical diagnosis and treatment. Oncologist. 2007;12(Suppl 1):11–21.

40. Gift AG. Visual analogue scales: measurement of subjective phenomena. Nurs Res. 1989;38:286–287.

41. Brunier G, Graydon J. A comparison of two methods of measuring fatigue in patients on chronic haemodialysis: visual analogue vs Likert scale. Int J Nurs Stud. 1996;33:338–348.

42. Calvio LC, Feuerstein M, Hansen J, Luff GM. Cognitive limitations in occupationally active brain tumor survivors. Occup Med (Lond). 2009;59:406–412.

43. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance Systems Survey Questionnaire: US Department of Health and Human Services. Atlanta, GA: Centers for Disease Control and Prevention; 1999.

44. Feuerstein M, Hansen JA, Calvio LC, Johnson L, Ronquillo JG. Work productivity in brain tumor survivors. J Occup Environ Med. 2007;49:803–811.

45. Newhouse PA, Potter A, Singh A. Effects of nicotinic stimulation on cognitive performance. Curr Opin Pharmacol. 2004;4:36–46.

46. Peeling P, Dawson B. Influence of caffeine ingestion on perceived mood states, concentration, and arousal levels during a 75-min university lecture. Adv Physiol Educ. 2007;31:332–335.

47. Weissenborn R, Duka T. Acute alcohol effects on cognitive function in social drinkers: their relationship to drinking habits. Psychopharmacology (Berl). 2003;156:306–312.

48. Baraona E, Abittan CS, Dohmen K, et al. Gender differences in pharmacokinetics of alcohol. Alcohol Clin Exp Res. 2001;25:502–507.

49. O'Hara C, Harrell M, Bellingrath E, Lisicia K. Cognitive Symptom Checklists-Clinician's Guide. Florida: Psychological Assessment Resources, Inc.; 1993.

50. Gualtieri CT, Johnson LG. Reliability and validity of a computerized neurocognitive test battery, CNS vital signs. Arch Clin Neuropsychol. 2006;21:623–643.

51. Lerner D, Amick BC III, Rogers WH, Malspeis S, Bungay K, Cynn D. The work limitations questionnaire. Med Care. 2001;39:72–85.

52. Mattke S, Balakrishnan A, Bergamo G, Newberry SJ. A review of methods to measure health-related productivity loss. Am J Manag Care. 2007;13:211–217.

53. Lofland JH, Pizzi L, Frick KD. A review of health-related workplace productivity loss instruments. Pharmacoeconomics. 2004;22:165–184.

54. Prasad M, Wahlqvist P, Shikiar R, Shih YC. A review of self-report instruments measuring health-related work productivity: a patient-reported outcomes perspective. Pharmacoeconomics. 2004;22:225–244.

55. Amick BC III, Lerner D, Rogers WH, Rooney T, Katz JN. A review of health-related work outcome measures and their uses, and recommended measures. Spine. 2000;25:3152–3160.

56. Allen HM Jr, Bunn WB III. Validating self-reported measures of productivity at work: a case for their credibility in a heavy manufacturing setting. J Occup Environ Med. 2003;45:926–940.

57. Lerner D, Amick BC III, Lee JC, et al. Relationship of employee-reported work limitations to work productivity. Med Care. 2003;41:649–659.

58. Shilling V, Jenkins V. Self-reported cognitive problems in women receiving adjuvant therapy for breast cancer. Eur J Oncol Nurs. 2007;11:6–15.

59. Dietrich J, Monje M, Wefel J, Meyers C. Clinical patterns and biological correlates of cognitive dysfunction associated with cancer therapy. Oncologist. 2008;13:1285–1295.

60. Parasuraman R, Rizzo M, eds. Neuroergonomics: The Brain at Work. New York: Oxford University Press; 2008.

61. Ferguson RJ, McDonald BC, Saykin AJ, Ahles TA. Brain structure and function differences in monozygotic twins: possible effects of breast cancer chemotherapy. J Clin Oncol. 2007;25:3866–3870.

62. Brown LF, Kroenke KK. Cancer-related fatigue and its associations with depression and anxiety: a systematic review. Psychosomatics. 2009;50:440–447.

63. Whitehead LC. Methodological and ethical issues in Internet-mediated research in the field of health: an integrated review of the literature. Soc Sci Med. 2007;65:782–791.

64. Ries LAG, Melbert D, Krapcho M, et al, eds. SEER Cancer Statistics Review, 1975–2005. Bethesda, MD: National Cancer Institute; 2006.

65. American Cancer Society. Breast Cancer Facts & Figures 2005-2006. Atlanta, GA: American Cancer Society, Inc.; 2005.

66. Feuerstein M, ed. Work and Cancer Survivors. New York: Springer-Verlag; 2009.

67. Seruga B, Zhang H, Bernstein LJ, Tannock IF. Cytokines and their relationship to the symptoms and outcome of cancer. Nat Rev Cancer. 2008;8:887–899.

68. Dantzer R, Capuron L, Irwin MR, et al. Identification and treatment of symptoms associated with inflammation in medically ill patients. Psychoneuroendocrinology. 2008;33:18–29.

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