Abstract
BACKGROUND:
Fatigue is a common and disabling side effect of targeted therapies such as tyrosine kinase inhibitors (TKIs) used to treat chronic myeloid leukemia (CML). The goal of the current study was to conduct a pilot randomized trial of the first cognitive behavioral intervention developed for fatigue due to targeted therapy.
METHODS:
Patients with CML treated with a TKI who were reporting moderate to severe fatigue were recruited and randomized 2:1 to cognitive behavioral therapy for targeted therapy–related fatigue (CBT-TTF) delivered via FaceTime for the iPad or to a waitlist control (WLC) group. The outcomes were acceptability, feasibility, and preliminary efficacy for fatigue (Functional Assessment of Chronic Illness Therapy–Fatigue; primary outcome) and quality of life (Functional Assessment of Cancer Therapy–General; secondary outcome). Participants were assessed before randomization and after treatment (ie, approximately 18 weeks later).
RESULTS:
A total of 44 patients (mean age, 55 years; 48% female) were assigned to CBT-TTF (n = 29) or WLC (n = 15). The study participation rate was 59%. Among the patients assigned to CBT-TTF, 79% completed the intervention. Intent-to-treat analyses indicated that patients assigned to CBT-TTF demonstrated greater improvements in fatigue (d = 1.06; P < .001) and overall quality of life (d = 1.15; P = .005) than those assigned to WLC. More patients randomized to CBT-TTF than WLC demonstrated clinically significant improvements in fatigue (85% vs 29%) and quality of life (88% vs 54%; P values ≤ .016).
CONCLUSIONS:
CBT-TTF displays preliminary efficacy in improving fatigue and quality of life among fatigued patients with CML treated with TKIs. The findings suggest that a larger randomized study is warranted.
Keywords: chronic myeloid leukemia, cognitive behavioral therapy, fatigue, quality of life, randomized controlled trial
INTRODUCTION
Targeted therapies such as tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of many types of cancer. The first targeted therapy, imatinib, was approved for chronic myeloid leukemia (CML) in 2001. Eight-year survival rates for CML increased from less than 15% in 1983 to 87% after 2001.1 The development of second-generation TKIs for CML, including nilotinib, dasatinib, and bosutinib, soon followed. Although often significantly less toxic than the drugs they have replaced (eg, interferon-α in CML), TKIs are not without side effects.
One of the most common and debilitating side effects of TKIs is fatigue.2–4 Up to 68% of patients with CML treated with a TKI report moderate to severe fatigue.3 Targeted therapy–related fatigue in patients with CML is associated with large deficits in quality of life. For example, Efficace et al5 described differences in physical and emotional quality of life between patients reporting high fatigue and patients reporting low fatigue that were more than 8 and 7 times the magnitude of a clinically meaningful difference, respectively. These differences led the authors to conclude that “fatigue is the main factor limiting the quality of life of CML patients who receive long-term imatinib therapy.”5 Because many patients with CML will be treated with a TKI for several years or the rest of their lives, fatigue has the potential to negatively affect patients for a long period of time. There are currently no evidence-based interventions for targeted therapy–related fatigue.
Cognitive behavioral therapy (CBT) has been shown to significantly reduce fatigue in disease-free cancer survivors after treatment.6,7 CBT is recommended as an evidence-based treatment for cancer-related fatigue by the American Society of Clinical Oncology and the National Comprehensive Cancer Network.8,9 Previous studies have found CBT for fatigue to be efficacious in reducing fatigue after treatment in patients with various cancer types;6,7 reductions in clinically significant fatigue have been sustained up to 14 years in half of patients.10 CBT is based on the precipitating-perpetuating model of cancer-related fatigue, which posits that cancer or its treatment precipitates fatigue; patients then cope with fatigue in ways that are helpful in the short term but perpetuate the problem in the long term (eg, increased napping and decreased physical activity).11 CBT aims to address these perpetuating factors by teaching patients new ways to think about and cope with their fatigue. We previously adapted cognitive behavioral therapy for targeted therapy–related fatigue (CBT-TTF) based on in-depth interviews with patients with CML and providers.12 The original 6 modules of CBT were retained (ie, Sleep/Wake Rhythms, Activity Regulation, Dysfunctional Thinking, Insufficient Processing, Social Support and Interactions, and Fear of Disease Recurrence), although vignettes and wording were modified to be reflective of CML (eg, “disease activity” rather than “disease recurrence”). In addition, a Psychoeducation module was added to increase understanding of CML and the importance of adherence to TKI therapy. Consistent with the original CBT for fatigue, patients and providers indicated that CBT-TTF should be tailored to patients’ unique needs. Patients also indicated familiarity with the internet and receptivity to using FaceTime to receive the intervention.12
The goal of the current study was to conduct a pilot randomized trial of internet-assisted CBT-TTF in comparison with a waitlist control (WLC) in fatigued patients with CML treated with a TKI. The current article reports on the acceptability (ie, participation rate), feasibility (ie, retention and completion rates), and preliminary efficacy of the intervention for the primary outcome (ie, fatigue) and a major secondary outcome (ie, quality of life). We hypothesized that CBT-TTF would be acceptable and feasible and that the CBT-TTF group would demonstrate significantly improved fatigue and quality of life in comparison with the WLC group.
MATERIALS AND METHODS
Participants
Participants were recruited from the Moffitt Cancer Center in Tampa, Florida, between October 2015 and September 2017. Eligible participants were required to 1) be at least 18 years old, 2) be able to speak/read English, 3) be diagnosed with chronic-phase CML, 4) not have been treated for another cancer (except nonmelanoma skin cancer) in the past 5 years, 5) be under the care of a physician at the Moffitt Cancer Center, 6) be on the same oral TKI for longer than 3 months, 7) have reported a new onset or worsening of fatigue since starting a TKI, 8) have reported moderate-severe fatigue in the past week (Fatigue Symptom Inventory average rating ≥ 4 on a scale of 0–10),13 and 9) have no clinical history of another disease (eg, multiple sclerosis or fibromyalgia) that could account for their fatigue presentation. Patients who were scheduled to discontinue their TKI under medical supervision within the next 3 months were excluded.
Procedures
Study procedures were approved by the Chesapeake institutional review board. The trial was registered at ClinicalTrials.gov (). Potentially eligible patients were identified through a review of medical records in consultation with their treating oncologist and were approached by phone or in person at a regularly scheduled clinic visit. After providing written informed consent, participants were asked to complete baseline self-report questionnaires. The first 2 patients were intentionally assigned to CBT-TTF to pilot the intervention. Participants were then randomized in blocks of 3 to receive CBT-TTF or WLC on a 2:1 basis with a computer-generated randomization schedule and were stratified by sex. The computer-generated allocation sequence was prepared by an independent statistician. Study staff were not blinded for allocation after randomization because of practical constraints.
CBT-TTF
Participants assigned to the intervention condition met with a CBT-TTF therapist at an initial in-person session held at the Moffitt Cancer Center. Patients worked with the same therapist throughout the intervention. The goal of this first session was to introduce the intervention and its rationale and outline the tailored treatment plan. Tailoring was determined on the basis of patient responses to baseline questionnaires evaluating perpetuating factors (see Supporting Table 1). The initial session lasted approximately 90 minutes. Subsequent sessions were conducted via FaceTime for the iPad and lasted approximately 45 minutes. These sessions followed a basic format of problem recognition, solution generation, implementation, and progress evaluation. Depending on participants’ progress in meeting therapy goals, therapists had the option of scheduling sessions at 1- or 2-week intervals. A final session summarized progress and ways to maintain therapeutic gains. The intervention was conducted over 18 weeks. The therapists were 2 doctoral students in clinical psychology at the University of South Florida who were trained in CBT-TTF. They were supervised on a weekly basis by Dr. Hans Knoop via a conference call. Training involved the therapists reviewing the CBT-TTF therapy manual and then rehearing intervention elements in modeling and role-playing sessions with Dr. Knoop, who determined their readiness to meet with participants. Fidelity checks were completed by a postdoctoral fellow in clinical psychology who determined whether patients received modules as indicated.
WLC
Participants assigned to this condition continued to receive care under the direction of their Moffitt oncologist. Upon completion of the follow-up assessment, participants were offered the opportunity to receive CBT-TTF in the same manner as described previously.
Measures
Demographic and clinical characteristics
Demographic information (eg, age, sex, race, ethnicity, marital status, and education) was collected via self-report at baseline. The Charlson Comorbidity Index was used to evaluate self-reported comorbidities.14 Clinical information abstracted via medical record review included CML diagnosis date, current TKI therapy, current TKI start date, and previous TKI therapy.
Fatigue
Fatigue was measured with the Fatigue subscale of the Functional Assessment of Chronic Illness Therapy–Fatigue (FACIT-F). The Fatigue subscale consists of 13 items asking about fatigue in the past 7 days. Items are summed to produce a score ranging from 0 to 52, with lower scores indicating greater fatigue. The FACIT-F has extensive reliability and validity data15,16 and has demonstrated sensitivity to change in previous intervention studies designed to reduce fatigue in patients with cancer.17–19 A difference of 3 points on the Fatigue subscale indicates a clinically important difference,15 which was examined as a secondary outcome.
Quality of life
Quality of life was measured with the total score of the Functional Assessment of Cancer Therapy–General (FACT-G) scale. The FACT-G consists of 4 subscales: Physical Well-Being (PWB), Functional Well-Being (FWB), Emotional Well-Being (EWB), and Social Well-Being (SWB). Scores on the 4 subscales are summed to produce a total score ranging from 0 to 108, with higher scores indicating better quality of life. The FACT-G has extensive reliability and validity data and has demonstrated sensitivity to change in patients with cancer.15,18 A difference of 4 points on the FACT-G total score indicates a clinically important difference,15 which was examined as a secondary outcome.
Statistical Analyses
Sample size calculation
The a priori study recruitment goal was 48 participants (ie, 32 randomized to CBT-TTF and 16 randomized to WLC), which allowed the detection of between-group differences of 0.88 standard deviation (SD) units at follow-up with a power of 0.80 at α = .05 (2-tailed), a difference smaller than that observed by Gielissen et al7 (ie, d = 1.04). A sample of 48 also allowed the detection of a within-group change of 0.51 SD units, which corresponded to the threshold for potential efficacy described previously.
Evaluation of sample characteristics and study outcomes
To calculate the participation rate, the number of individuals who provided informed consent was divided by the number of individuals who were approached and met all eligibility criteria. The study would be considered acceptable if this rate was ≥50%. To calculate the retention rate, the number of participants who completed baseline and follow-up assessments was divided by the number who provided informed consent and remained eligible throughout the study. To determine the CBT-TTF completion rate, the number of participants who completed at least 10 sessions was divided by the total number randomized to CBT-TTF. The study would be considered feasible if retention and completion rates were both greater than 70%. Independent sample t tests and chi-square tests were used to compare demographic and clinical variables between groups. It was determined a priori that variables significant at P < .10 would be included as covariates in outcomes analyses. Intent-to-treat, mixed model analyses were conducted to evaluate longitudinal changes in continuous outcome variables as a function of group assignment. Mixed model analyses included all participants who were randomly assigned and completed at least 1 assessment. Cohen’s d effect sizes were calculated by the division of group differences in outcomes at follow-up by the pooled SD of both groups at follow-up. Effect size magnitudes were interpreted as follows: small (0.2–0.5), medium (0.5–0.8), or large (>0.8).20 A chi square analysis was used to determine group differences in clinically significant improvements in fatigue and quality of life among participants who completed questionnaires at both time points. Analyses were conducted in SAS 9.4.
RESULTS
The participant flow through the study is shown in Figure 1. Participants were recruited between October 2015 and September 2017. In total, 48 of 82 eligible patients (59%) who were approached signed a consent form. Consenters did not differ from refusers by race (P = .20), ethnicity (P = .37), or sex (P = .94). As for the retention rate, 41 of 46 consented patients (89%) who remained eligible throughout the study completed both baseline and follow-up assessments. As for the completion rate, 22 of 28 patients (79%) randomized to CBT-TTF received at least 10 sessions. Thus, the study was determined to be acceptable and feasible.
Figure 1.
Participant flow through the study. CBT-TTF indicates cognitive behavioral therapy for targeted therapy–related fatigue; CNBR, cannot be reached; IEAC, ineligible after consent; LTFU, lost to follow-up; T2, time 2; TTF, targeted therapy–related fatigue.
Sociodemographic and clinical characteristics of the sample are shown in Table 1. The majority of the participants were male, white, non-Hispanic, married, and college graduates and reported an annual household income of $40,000 per year or more. On average, patients had been diagnosed with CML 5.2 years previously and had been on their current TKI for 2.5 years. A plurality of patients were receiving dasatinib (36%), which was followed by nilotinib (25%), bosutinib (20%), imatinib (12%), and ponatinib (7%). There was a trend for patients in the CBT-TTF group to be younger than those in the WLC group (P = .09); therefore, age was included as a covariate in later analyses. There were no other significant differences in sociodemographic or clinical characteristics between the CBT-TTF and WLC groups (see Table 1).
TABLE 1.
Sociodemographic and Clinical Characteristics of the Sample
| Overall (n = 44) | CBT-TTF (n = 29) | WLC (n = 15) | P | |
|---|---|---|---|---|
| Age, mean (SD) [range], y | 55 (13) [29−82] | 53 (13) [29−82] | 60 (12) [39−78] | .09 |
| Sex: female, No. (%) | 21 (48) | 14 (48) | 7 (47) | .92 |
| Race: white, No. (%) | 38 (86) | 26 (90) | 12 (80) | .38 |
| Ethnicity: non-Hispanic, No. (%) | 44 (100) | 29 (100) | 14 (100) | 1.00 |
| Education: college graduate, No. (%) | 24 (55) | 16 (55) | 8 (53) | .91 |
| Marital status: married, No. (%) | 35 (80) | 24 (83) | 11 (73) | .46 |
| Annual household income ≥ $40,000, No. (%) | 24 (67) | 16 (70) | 8 (62) | .62 |
| Comorbidity index score, mean (SD) [range] | 5.6 (1.4) [3−10] | 5.7 (1.1) [3−7] | 5.5 (2.0) [3−10] | .74 |
| Years since diagnosis, mean (SD) [range] | 5.2 (5.3) [4.5 mo to 25.0 y] | 6.0 (5.8) [6.7 mo to 25.0 y] | 3.7 (3.9) [4.5 mo to 13.0 y] | .18 |
| Current TKI therapy, No. (%) | .43 | |||
| Imatinib | 5 (11) | 2 (7) | 3 (20) | |
| Nilotinib | 11 (25) | 6 (21) | 5 (33) | |
| Dasatinib | 16 (36) | 13 (45) | 3 (20) | |
| Ponatinib | 3 (7) | 2 (7) | 1 (7) | |
| Bosutinib | 9 (20) | 6 (21) | 3 (20) | |
| Years on current TKI therapy, mean (SD) [range] | 2.5 (2.7) [3 mo to 12.9 y] | 2.5 (2.5) [3.8 mo to 8.3 y] | 2.5 (3.1) [3 mo to 12.9 y] | 1.00 |
| Previous TKI therapies, No. (%) | ||||
| Imatinib | 19 (40) | 15 (52) | 4 (27) | .11 |
| Nilotinib | 13 (27) | 8 (28) | 5 (33) | .69 |
| Dasatinib | 13 (27) | 10 (34) | 3 (20) | .14 |
| Ponatinib | 2 (4) | 2 (7) | 0 (0) | .30 |
| Bosutinib | 5 (10) | 4 (14) | 1 (7) | .48 |
Abbreviations: CBT-TTF, cognitive behavioral therapy for targeted therapy–related fatigue; SD, standard deviation; TKI, tyrosine kinase inhibitor; WLC, waitlist control.
Results of intent-to-treat analyses of primary and secondary outcomes are shown in Table 2. As for the primary outcome of fatigue severity, participants randomized to CBT-TTF demonstrated significantly greater improvements than those randomized to WLC (P < .001). The effect size for fatigue severity was large (d = 1.07). As for secondary outcomes, more CBT-TTF participants (85%) experienced clinically significant improvements in fatigue than WLC participants (29%; P < .001). Significantly greater improvements in the CBT-TTF group were also observed for overall quality of life (P = .005). The effect size for quality of life was also large (d = 1.15). More CBT-TTF participants (88%) experienced clinically significant improvements in quality of life than WLC participants (54%; P < .016). As for the quality-of-life subscales, greater improvements in the CBT-TTF group than the WLC group were observed for FWB (d = 1.06; P = .003) and EWB (d = 1.12; P < .001) but not PWB (d = 0.45; P = .151) or SWB (d = 0.60; P = .800). The same pattern of results was found with and without the first 2 nonrandomized pilot participants who were assigned to CBT-TTF. Thus, the results include these participants.
TABLE 2.
Changes in Primary and Secondary Outcomes by Group
| CBT-TTF | WLC | ||||||
|---|---|---|---|---|---|---|---|
| Baseline (n = 29) |
Follow-Up (n = 27)a |
Baseline (n = 15) |
Follow-Up (n = 14)b |
Group Difference at Follow-Up | d | P | |
| FACIT-F for fatigue | |||||||
| Severity, mean (SD) | 28.03 (6.92) | 15.70 (8.69) | 24.53 (7.05) | 24.71 (8.18) | 9.01 | 1.07 | <.001 |
| Clinically significant improvement, No. (%) | 23 (85) | 4 (29) | <.001 | ||||
| FACT-G for QOL | |||||||
| PWB, mean (SD) | 16.48 (4.76) | 20.67 (4.02) | 17.00 (6.00) | 18.62 (5.45) | 2.06 | 0.45 | .151 |
| FWB, mean (SD) | 14.14 (4.76) | 20.26 (6.07) | 13.27 (4.76) | 14.46 (3.84) | 5.80 | 1.06 | .003 |
| EWB, mean (SD) | 15.07 (4.84) | 20.30 (4.04) | 17.73 (3.35) | 15.85 (3.87) | 4.45 | 1.12 | <.001 |
| SWB, mean (SD) | 18.35 (5.21) | 22.33 (5.04) | 15.83 (5.57) | 19.29 (5.23) | 3.04 | 0.60 | .800 |
| Total score, mean (SD) | 64.04 (15.05) | 84.25 (15.37) | 63.83 (14.44) | 68.22 (10.59) | 16.03 | 1.15 | .005 |
| Clinically significant improvement, No. (%) | 23 (88) | 7 (54) | .016 | ||||
Abbreviations: CBT-TTF, cognitive behavioral therapy for targeted therapy–related fatigue; EWB, Emotional Well-Being; FACIT-F, Functional Assessment of Chronic Illness Therapy–Fatigue; FACT-G, Functional Assessment of Cancer Therapy–General; FWB, Functional Well-Being; PWB, Physical Well-Being; QOL, quality of life; SD, standard deviation; SWB, Social Well-Being; WLC, waitlist control.
Unadjusted values are shown. P values refer to the group × time interaction in mixed models adjusted for age.
n = 26 for QOL.
n = 13 for symptomatology.
DISCUSSION
The goal of the current pilot study was to evaluate the acceptability, feasibility, and preliminary efficacy of an internet-assisted cognitive behavioral intervention for targeted therapy–related fatigue in comparison with a waitlist control group. Results suggest that the intervention was acceptable, as indicated by a consent rate of 59%. The intervention was highly feasible, as indicated by an 89% retention rate and a 79% completion rate. Notably, the intervention was also highly efficacious and resulted in large improvements in fatigue severity and quality of life, including overall quality of life, FWB, and EWB. More than triple the number of patients randomized to CBT-TTF demonstrated clinically significant improvements in fatigue in comparison with the WLC patients (85% vs 29%). A future article will focus on the tailoring of the intervention in this study as well as effects on process outcomes and mediating variables.
Delivery of the intervention over FaceTime for the iPad may have increased the acceptability and feasibility of the intervention. Patients commented favorably on the convenience of conducting sessions remotely. Many patients lived an hour or more away from the cancer center and/or held a full-time job, and these would have been significant barriers to an in-person intervention. Remote delivery of CBT-TTF is consistent with the increasing use of telemedicine in cancer care delivery21 and suggests a high dissemination potential for the intervention. Recent work by Abrahams et al6 suggests that CBT for fatigue in cancer survivors is efficacious when the intervention content is delivered via a website with minimal counselor support, further highlighting the dissemination potential of CBT for fatigue.
Large improvements in fatigue and overall quality of life due to CBT-TTF are noteworthy. The magnitude of the improvement in fatigue demonstrated in the current study (d = 1.07) is consistent with previously published studies of CBT for fatigue in cancer survivors (d = 1.05)7 and breast cancer survivors (d = 1.00).6 There is notable consistency in the magnitude of the current findings in patients on active treatment (ie, an ongoing precipitating factor for fatigue) and previous findings in patients with cancer who have completed treatment (ie, the precipitating factor for fatigue is no longer active). This study shows that despite active treatment, fatigue can be reduced substantially. These findings are important in light of a growing group of patients who are on treatment for long periods of time.
The large improvements in fatigue observed in patients treated with CBT for fatigue stand in contrast to the more modest gains reported by studies of other interventions. For example, meta-analyses have reported that exercise interventions improve cancer-related fatigue by 0.30 to 0.42 SDs.22,23 Pharmacological interventions have demonstrated nonsignificant improvements in fatigue of 0.08 SDs.22 Taken together, these findings suggest that CBT for fatigue may be more efficacious than other currently available interventions for cancer-related fatigue.
CBT-TTF did not evince statistically significant improvements in PWB or SWB. Nevertheless, PWB and SWB improved by 0.45 and 0.60 SDs, respectively, which corresponded to small to medium effect sizes.20 This pattern of results suggests that the study may have been underpowered to detect more modest improvements in these outcomes and that a larger randomized trial of CBT-TTF is warranted.
The study is characterized by several strengths, including a novel and clinically important research question, a randomized design, a manualized treatment with appropriate fidelity checks, innovative intervention delivery via the internet, high retention rates, and intent-to-treat analyses. Study limitations should also be noted, however. Limitations include a relatively small sample that consisted primarily of non-Hispanic white patients. Thus, it is unclear whether the improvements in fatigue due to CBT-TTF observed in this study are generalizable to racial and ethnic minority patient populations. Moreover, a WLC group was used in this pilot study rather than a time and attention control group. Smaller improvements in fatigue and other outcomes may be observed with respect to a time and attention control group. Future studies should address these limitations.
In summary, this pilot study suggests that internet-assisted CBT-TTF is a promising intervention for fatigue due to targeted therapies. Additional research is needed to confirm these findings in larger samples and among other patient populations treated with targeted therapy (eg, lung cancer and renal cell carcinoma). This line of research may provide new opportunities for improving patient quality of life after a cancer diagnosis.
Supplementary Material
FUNDING SUPPORT
This study was funded by the National Cancer Institute (R21 CA191594, R25 CA191314, and P30 CA076292); the views expressed are those of the authors and do not necessarily represent those of the National Cancer Institute. This work was also supported in part by the Population Research, Interventions, and Measurement Core Facility at the H. Lee Moffitt Cancer Center and Research Institute, a National Cancer Institute–designated comprehensive cancer center.
Footnotes
Additional supporting information may be found in the online version of this article.
CONFLICT OF INTEREST DISCLOSURES
Heather S. L. Jim reports consulting for RedHill BioPharma and Janssen Scientific Affairs. Javier Pinilla-Ibarz reports consulting for Novartis, Takeda, Pfizer, and Bristol-Myers Squibb. Kendra Sweet reports involvement in speakers bureaus for Jazz Pharma, Celgene, and Novartis; involvement in advisory boards for Novartis, Agios, Astellas, Bristol-Myers Squibb, and AbbVie; consulting for Pfizer; and grants from Incyte outside the submitted work. The other authors made no disclosures.
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