Characteristics Associated with Inter-Individual Differences in the Trajectories of Self-Reported Attentional Function in Oncology Outpatients Receiving Chemotherapy

Patients and Settings

This study is part of a larger, longitudinal study of the symptom experience of oncology outpatients receiving CTX [11]. Eligible patients were ≥18 years of age; had a diagnosis of breast, gastrointestinal (GI), gynecologic (GYN), or lung cancer; had received CTX within the preceding four weeks; were scheduled to receive at least two additional cycles of CTX; were able to read, write, and understand English; and gave written informed consent. Patients were recruited from two Comprehensive Cancer Centers, one Veteran’s Affairs hospital, and four community-based oncology programs.

Instruments

A demographic questionnaire obtained information on age, gender, ethnicity, marital status, living arrangements, education, employment status, and income. The Karnofsky Performance Status (KPS) scale is widely used to evaluate functional status in patients with cancer and has well established validity and reliability [12]. Patients rated their functional status using the KPS scale that ranged from 30 (I feel severely disabled and need to be hospitalized) to 100 (I feel normal; I have no complaints or symptoms) [12,13].

Self-Administered Comorbidity Questionnaire (SCQ) consists of 13 common medical conditions simplified into language that can be understood without prior medical knowledge [14]. Patients indicated if they had the condition; if they received treatment for it (proxy for disease severity) and if it limited their activities (indication of functional limitations). For each condition, the patient can receive a maximum of 3 points. The total SCQ score ranges from 0 to 39. The SCQ has well established validity and reliability [14].

Alcohol Use Disorders Identification Test (AUDIT) is a 10-item questionnaire that assesses alcohol consumption, alcohol dependence, and the consequences of alcohol abuse in the last 12 months. The AUDIT gives a total score that ranges between 0 and 40. Scores of ≥8 are defined as hazardous use and scores of ≥16 are defined as use of alcohol that is likely to be harmful to health [15]. The AUDIT has well established validity and reliability [16]. In this study, its Cronbach’s alpha was 0.63.

Attentional Function Index (AFI) consists of 16 items designed to measure attentional function [17]. A higher total mean score on a 0 to 10 numeric rating scale (NRS) indicates greater capacity to direct attention [17]. Total scores are grouped into categories of attentional function (i.e., <5.0 low function, 5.0 to 7.5 moderate function, >7.5 high function) [18]. The AFI has well established reliability and validity [17]. In this study, the Cronbach’s alpha for the AFI total score was 0.93.

Spielberger State-Trait Anxiety Inventories (STAI-T and STAI-S) each have 20 items that are rated from 1 to 4. The summed scores for each scale can range from 20 to 80. The STAI-T measures a person’s predisposition to anxiety as part of one’s personality. The STAI-S measures a person’s temporary anxiety response to a specific situation or how anxious or tense a person is “right now” in a specific situation. Cutoff scores of ≥ 31.8 and ≥ 32.2 indicate high levels of trait and state anxiety, respectively. The STAI-S and STAI-T inventories have well established validity and reliability [19]. In the current study, the Cronbach’s alphas for the STAI-T and STAI-S were 0.92 and 0.96, respectively.

Center for Epidemiological Studies-Depression scale (CES-D) consists of 20 items selected to represent the major symptoms in the clinical syndrome of depression. A total score can range from 0 to 60, with scores of ≥ 16 indicating the need for individuals to seek clinical evaluation for major depression. The CES-D has well established validity and reliability [20]. In the current study, the Cronbach’s alpha for the CES-D total score was 0.89.

Lee Fatigue Scale (LFS) consists of 18 items designed to assess physical fatigue and energy [21]. Each item was rated on a 0 to 10 NRS. Total fatigue and energy scores are calculated as the mean of the 13 fatigue items and the 5 energy items, respectively. Higher scores indicate greater fatigue severity and higher levels of energy. Using separate LFS questionnaires, patients were asked to rate each item based on how they felt within 30 minutes of awakening (i.e., morning fatigue, morning energy) and prior to going to bed (i.e., evening fatigue, evening energy). The LFS has established cut-off scores for clinically meaningful levels of fatigue (i.e., ≥3.2 for morning fatigue, ≥5.6 for evening fatigue) [22] and energy (i.e., ≤ 6.2 for morning energy, ≤ 3.5 for evening energy) [22]. It was chosen for this study because it is relatively short, easy to administer, and has well established validity and reliability [21]. In the current study, the Cronbach’s alphas were 0.96 for morning and 0.93 for evening fatigue and 0.95 for morning and 0.93 for evening energy.

General Sleep Disturbance Scale (GSDS) consists of 21-items designed to assess the quality of sleep in the past week. Each item was rated on a 0 (never) to 7 (everyday) NRS. The GSDS total score is the sum of the seven subscale scores that can range from 0 (no disturbance) to 147 (extreme sleep disturbance). A GSDS total score of ≥ 43 indicates a significant level of sleep disturbance [22]. The GSDS has well established validity and reliability [23]. In the current study, the Cronbach’s alpha for the GSDS total score was 0.83.

Occurrence of pain was evaluated using the Brief Pain Inventory [24]. Patients who responded yes to the question about having pain were asked to indicate if their pain was or was not related to their cancer treatment.

Study Procedures

The study was approved by the Institutional Review Board at each of the study sites. Eligible patients were approached in the infusion unit by a member of the research team to discuss participation in the study. Written informed consent was obtained from all patients. Depending on the length of their CTX cycles (i.e., 14-day, 21-day, or 28-day), patients completed study questionnaires in their homes, a total of six times over two cycles of CTX, namely:prior to CTX administration (i.e., recovery from previous CTX cycle at assessments 1 and 4), approximately 1 week after CTX administration (i.e., acute symptoms at assessments 2 and 5) and approximately 2 weeks after CTX administration (i.e., potential nadir at assessments 3 and 6).

Data Analyses

Descriptive statistics and frequency distributions were generated on the sample characteristics and symptom severity scores at enrollment using the Statistical Package for the Social Sciences (SPSS) version 22 [25].

Hierarchical linear modeling (HLM) based on full maximum likelihood estimation was performed in two stages using software developed by Raudenbush and Bryk [26]. The HLM methods are described in detail elsewhere [27]. In brief, during stage 1, intra-individual variability in attentional function over time was examined (i.e., evaluation of the unconditional model). A piecewise model strategy was employed to evaluate the pattern of change in AFI scores over time because the six assessments encompassed two cycles of CTX. The six assessments were coded into two pieces. Assessments 1, 2, and 3 comprised the first piece (PW1) that was used to model changes over time during the first CTX cycle. Assessments 4, 5, and 6 comprised the second piece (PW2) that was used to model changes over time during the second CTX cycle. A piecewise model can be more sensitive to the timing and sequencing of changes in a dependent variable than conventional HLM models that would have assessed linear, quadratic, or cubic changes over the six assessments and would not have paid attention to the two different CTX cycles [28].

The second stage of the HLM analysis examined inter-individual differences in the piecewise trajectories of attentional function by modeling the individual change parameters (i.e., intercept and slope parameters) as a function of a list of proposed predictors. Supplementary Table 1 lists the potential demographic, clinical, and symptom predictors that were developed based on a review of the literature on factors associated with changes in attentional function and cognitive in oncology patients undergoing CTX (for reviews see 10, 29–31).

To improve estimation efficiency and construct a parsimonious model, exploratory level 2 analyses were completed in which each potential predictor was assessed to determine whether it would result in a better fitting model if it alone were added as a level 2 predictor. Predictors with a t value of <2.0 were excluded 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 predictors were retained in the final model. A p-value of <.05 indicated statistical significance.

Sample Characteristics

The demographic, clinical, and symptom characteristics of the sample (n=1,329) are presented in Table 1. The sample was predominately female (78%) with a mean age of 57 years, was well educated (16 years), currently not employed (65%), partnered (65%), and did not have child care responsibilities (78%). On average, the patients were two years from their cancer diagnosis (median = 0.42 years), primarily being treated with 21-day CTX cycles (51%), and had one metastatic site. At enrollment, the mean scores on the GSDS, the STAI-T, and STAI-S were above the cut-off scores for clinically meaningful levels of sleep disturbance, trait anxiety, and state anxiety, respectively. In addition, morning energy scores were below the clinically meaningful cutoff score. The mean AFI score at enrollment (6.38 ± 1.82) was in a range that indicated a moderate level of attentional function.

Changes in Attentional Function Over Time

The first HLM analysis examined how AFI scores changed within the two cycles of CTX. The estimates for the initial piecewise model are presented in Table 2. Since the model was unconditional (i.e., no covariates), the intercept represents the average AFI score at enrollment (i.e., 6.385 on a scale of 0 to 10). The estimated linear piecewise rates of change were −0.605 and −0.425 (both p<.0001) for piecewise linear 1 and piecewise linear 2, respectively. The estimated quadratic piecewise rates of change were 0.385 and 0.137 (both p<.0001) for piecewise quadratic 1 and piecewise quadratic 2, respectively. The combination of each coefficient determines the curves for the two piecewise components’ changes in attentional function scores over time.

Figure 1A displays the mean AFI scores over the two cycles of CTX. From assessment 1 to 2, AFI scores declined over time and recovered by assessment 3. Over the second CTX cycle, while a similar pattern was observed, the decline in scores was less steep. The results indicate a sample-wide change in AFI scores over time. However, they do not indicate that all of the patients’ AFI scores changed at the same rate over time. The variance components (Table 2) suggest that considerable inter-individual variability existed in the trajectories of attentional function. A spaghetti plot of a random sample of 50 patients demonstrates the inter-individual variability in AFI scores (Figure 1B). These results supported additional analyses of predictors of inter-individual differences in initial levels as well as in the trajectories of attentional function.

Predictors of Initial Levels of Attentional Function

As shown in the final model (Table 2), the demographic, clinical, and symptom characteristics that predicted inter-individual differences in initial levels of attentional function (i.e. intercept) were: employment status and KPS score, as well as enrollment levels of trait anxiety, depressive symptoms, sleep disturbance, evening fatigue, and morning energy. To illustrate the effects of the demographic and clinical characteristics, Figures 2A–B display the adjusted change curves for AFI scores that were estimated based on differences in employment status (i.e., employed or not employed) and functional status (i.e., lower/higher calculated as one SD above and below the mean KPS score). To illustrate the effects of the symptom characteristics, Figures 3A–E display the adjusted change curves for AFI scores that were estimated based on differences in trait anxiety (i.e., lower/higher calculated as one SD above and below the mean STAI-T score), depressive symptoms (i.e., lower/higher calculated as one SD above and below the mean CES-D score), sleep disturbance (i.e., lower/higher calculated as one SD above and below the mean GSDS score), evening fatigue (i.e., lower/higher calculated as one SD above and below the mean LFS evening fatigue score), and morning energy (i.e., lower/higher calculated as one SD above and below the mean LFS morning energy score).

Predictor of the Trajectories of Attentional Function

The only characteristic that predicted inter-individual differences in the trajectories of attentional function was gender. Figure 4A displays the adjusted change curves for AFI score for the male and female patients.

Predictor of Both Initial Levels of and the Trajectories of Attentional Function

The only characteristic that predicted inter-individual differences in initial levels and in the trajectories of attentional function was morning fatigue. Figure 4B displays the adjusted change curves for AFI scores that were estimated based on differences in morning fatigue (i.e. lower/higher calculated as one SD above and below the mean LFS morning fatigue score).

Non-modifiable Characteristics

Two non-modifiable characteristics (i.e., gender, employment status) were associated with decrements in attentional function. While no gender differences in initial levels of attentional function were found in the current study, females had slightly worse attentional function scores over the two cycles of CTX (Figure 4A). While the majority of the studies that used the AFI evaluated patients with breast cancer, findings regarding gender differences in attentional function during and following cancer treatment are inconclusive. For example, in one study [33], no gender differences in AFI scores were reported. In contrast, in another study, compared to men with prostate cancer [6], women with breast cancer reported lower AFI scores. Given the extremely modest gender differences in AFI scores found in our study, additional research is warranted on gender differences in self-reported attentional function because several lines of evidence suggest that the impact of gender on cognitive function is complex. For example, in the general population, gender differences in cognitive function are noted in a number of domains [34]. In addition, sex steroid hormones are known to modulate cognitive function [35].

Employment status was classified as a non-modifiable characteristic in this study because it is unlikely that patients can easily change their employment status during CTX treatment. Consistent with a previous report of women undergoing radiation therapy for breast cancer [7], patients who were employed at the time of enrollment into the current study reported higher levels of attentional function (Figure 2A). However, in other studies [33,36], no association was found between employment status and AFI scores. As noted by Williams and colleagues [37], being employed may condition the mechanisms involved in directing attention to function more efficiently. Therefore, when patients are not working, they do not experience this routine conditioning. This deficit may contribute to the perception of decreases in attentional function.

Modifiable Characteristics

A number of modifiable characteristics were associated with lower AFI scores (i.e., poorer functional status, higher trait anxiety, higher depression, higher sleep disturbance, higher evening fatigue, higher morning fatigue, lower morning energy). First, poorer functional status at enrollment was associated with lower levels of attentional function at enrollment (Figure 2B). This association is not surprising given that a growing body of evidence in the gerontology literature suggests that cognition and mobility are intertwined (for review see 38). For example, attention is a necessary cognitive resource for maintaining one’s ability to walk. In addition, attentional deficits are independently associated with postural instability, impairments in the performance of activities of daily living, and future falls [39]. These findings suggest that oncology patients undergoing CTX may need referrals to physical therapy for exercise interventions to improve both cognition and physical function.

While the current study is the first to evaluate the impact of a number of common symptoms on initial levels as well as changes in attentional function at multiple points over two cycles of CTX, our findings are consistent with a number of cross-sectional studies that reported associations between these symptoms and cognitive function. For example, higher levels of trait anxiety and depression were associated with lower levels of attentional function in women newly diagnosed with breast cancer [36]. In addition, in a study of patients with breast and prostate cancer [6]. higher levels of sleep disturbance were associated with lower levels of attentional function.

Morning fatigue was the only modifiable symptom characteristic that was associated with both initial levels of as well as the trajectories of attentional function over the two cycles of CTX (Figure 4B). Our findings are consistent with data from several studies [31,40,41], and a systematic review [29], that found that increases in physical fatigue in oncology patients were associated with decrements in cognitive function. This association may be explained by the fact that recent evidence suggests that cancer and its treatments trigger inflammatory processes that contribute to increased levels of physical fatigue and cognitive dysfunction in oncology patients [31].

In terms of these modifiable symptom characteristics, it should be noted that at the time of enrollment into the current study, patients had levels of trait anxiety and sleep disturbance that were above the clinically meaningful cutoff scores. In addition, levels of depression, morning and evening fatigue, and decrements in morning and evening energy were in the moderate range. Therefore, for patients whose scores for these latter six symptoms were one standard deviation above the mean score for the entire sample, the severity of their symptoms were at clinically meaningful levels. Our findings suggest that oncology patients undergoing CTX warrant a comprehensive symptom assessment and management plan. The exact relationships among these symptoms and decrements in cognitive function are undoubtedly complex and warrant investigation in future studies.

Limitations

Several study limitations warrant consideration. First, our evaluation of cognitive function was limited to a self-report measure that primarily evaluated changes in executive function [17]. Therefore, our findings regarding changes in attentional function over time, as well as the characteristics associated with decrements in attentional function warrant confirmation using objective measures of various components of cognitive function. Although our findings suggest that a number of characteristics are associated with decrements in attentional function, future studies need to consider the impact of multiple co-occurring symptoms or symptoms clusters on attentional function [41–43].

Some studies of cognitive changes during cancer treatment compared patients undergoing cancer treatment with healthy controls [17, 44]. In some of these studies [17], levels of cognitive function in patients beginning cancer treatment were lower than those of the healthy controls. In the current study, AFI scores at enrollment were in the moderate range and the majority of the patients had received previous treatment for their cancer. Future studies should evaluate patients prior to the initiation of CTX and compare findings to healthy controls.

Clinical Implications and Directions for Future Research

All of the modifiable characteristics associated with decrements in attentional function are amenable to clinical interventions. Clinicians need to assess patients for decrements in attentional function and associated risk factors and prescribe evidenced-based interventions to improve cognitive function and/or reduce co-occurring symptoms. Of note, a number of studies demonstrated that increased physical activity has beneficial effects on both physical and cognitive function [38,45]. In addition, increased physical activity may reduce sleep disturbance and fatigue and improve mood in these patients [46,47].

Additional research is warranted on changes in cognitive function from prior to through and following the completion of CTX. Findings from longitudinal studies with both subjective and objective measures of cognitive function and associated demographic, clinical, and symptom characteristics will provide important information to educate patients about changes in cognitive function during and following treatment. Studies are needed that evaluate the efficacy of multimodal interventions to reduce symptom burden and enhance cognitive function.