Laura B Oswald1, Kelly A Hyland2, Sarah L Eisel3, Aasha I Hoogland3, Hans Knoop4, Ashley M Nelson5, Javier Pinilla-Ibarz6, Kendra Sweet6, Paul B Jacobsen7, Heather S L Jim3. 1. Department of Health Outcomes and Behavior, Moffitt Cancer Center, 12902 Magnolia Dr., MRC-SCM, Tampa, FL, 33612, USA. Laura.Oswald@moffitt.org. 2. Department of Psychology, University of South Florida, Tampa, FL, USA. 3. Department of Health Outcomes and Behavior, Moffitt Cancer Center, 12902 Magnolia Dr., MRC-SCM, Tampa, FL, 33612, USA. 4. Department of Medical Psychology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands. 5. Department of Psychiatry, Harvard Medical School/Massachusetts General Hospital, Boston, MA, USA. 6. Department of Malignant Hematology, Moffitt Cancer Center, Tampa, FL, USA. 7. Division of Cancer Control and Population Science, National Cancer Institute, Bethesda, MD, USA.
Abstract
PURPOSE: Tyrosine kinase inhibitors (TKIs) substantially improve survival for patients with chronic myeloid leukemia (CML), but fatigue associated with TKIs can negatively impact patients' quality of life and adherence. This study sought to identify correlates of fatigue (e.g., sociodemographic characteristics, clinical characteristics, health behaviors) among patients with CML taking TKIs who reported moderate to severe fatigue. METHODS: Adults with CML experiencing at least moderate fatigue were recruited for a pilot trial of a cognitive behavioral intervention to improve fatigue. Data collected pre-intervention were used to explore concurrent correlates of fatigue in univariate and multivariable models. RESULTS: Participants (N = 44, 48% female) were M = 55.6 years old (SD = 12.6) and had been diagnosed with CML M = 5.2 years prior (SD = 5.3). Participants had been taking their current TKI for M = 2.5 years (SD = 2.7). Most participants (64%) had previously been treated with ≥ 1 other TKI. More than three-quarters of participants (77%) reported severe fatigue. In univariate models, worse fatigue was associated with higher BMI (r = -0.36, p = 0.018), prior treatment with other TKI(s) (r = - 0.34, p = 0.024), worse sleep disturbance (r = - 0.51, p < 0.001), and less physical activity (r = 0.31, p = 0.043). In a multivariable model, significant univariate correlates accounted for 39% of the variance in fatigue. Worse fatigue remained significantly correlated with higher BMI (β = - 0.33, p = 0.009) and more disturbed sleep (β = - 0.45, p < 0.001). CONCLUSION: Results may inform future research aiming to identify fatigued patients with CML at risk for experiencing more severe fatigue during TKI therapy. Identifying predictors of fatigue severity could aid clinicians in identifying which patients will benefit from referrals to supportive therapy. TRIAL REGISTRATION: NCT02592447, October 30, 2015.
PURPOSE: Tyrosine kinase inhibitors (TKIs) substantially improve survival for patients with chronic myeloid leukemia (CML), but fatigue associated with TKIs can negatively impact patients' quality of life and adherence. This study sought to identify correlates of fatigue (e.g., sociodemographic characteristics, clinical characteristics, health behaviors) among patients with CML taking TKIs who reported moderate to severe fatigue. METHODS: Adults with CML experiencing at least moderate fatigue were recruited for a pilot trial of a cognitive behavioral intervention to improve fatigue. Data collected pre-intervention were used to explore concurrent correlates of fatigue in univariate and multivariable models. RESULTS: Participants (N = 44, 48% female) were M = 55.6 years old (SD = 12.6) and had been diagnosed with CML M = 5.2 years prior (SD = 5.3). Participants had been taking their current TKI for M = 2.5 years (SD = 2.7). Most participants (64%) had previously been treated with ≥ 1 other TKI. More than three-quarters of participants (77%) reported severe fatigue. In univariate models, worse fatigue was associated with higher BMI (r = -0.36, p = 0.018), prior treatment with other TKI(s) (r = - 0.34, p = 0.024), worse sleep disturbance (r = - 0.51, p < 0.001), and less physical activity (r = 0.31, p = 0.043). In a multivariable model, significant univariate correlates accounted for 39% of the variance in fatigue. Worse fatigue remained significantly correlated with higher BMI (β = - 0.33, p = 0.009) and more disturbed sleep (β = - 0.45, p < 0.001). CONCLUSION: Results may inform future research aiming to identify fatigued patients with CML at risk for experiencing more severe fatigue during TKI therapy. Identifying predictors of fatigue severity could aid clinicians in identifying which patients will benefit from referrals to supportive therapy. TRIAL REGISTRATION: NCT02592447, October 30, 2015.
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