Melissa S Y Thong1, Floortje Mols2,3, Lonneke V van de Poll-Franse2,3,4, Mirjam A G Sprangers5, Carin C D van der Rijt6, Andrea M Barsevick7, Hans Knoop5,8, Olga Husson9. 1. Department of Medical Psychology, Amsterdam Public Health Research Institute, Academic Medical Center University of Amsterdam, P.O. Box 22660, 1100 DD, Amsterdam, Netherlands. s.y.thong@amc.uva.nl. 2. Netherlands Comprehensive Cancer Organisation, Utrecht, Netherlands. 3. CoRPS-Center of Research on Psychology in Somatic Diseases, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, Netherlands. 4. Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, Netherlands. 5. Department of Medical Psychology, Amsterdam Public Health Research Institute, Academic Medical Center University of Amsterdam, P.O. Box 22660, 1100 DD, Amsterdam, Netherlands. 6. Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands. 7. Department of Medical Oncology, Thomas Jefferson University, Philadelphia, PA, USA. 8. Expert Center for Chronic Fatigue, Department of Medical Psychology, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, Netherlands. 9. Department of Medical Psychology, Radboud University Medical Center, Nijmegen, Netherlands.
Abstract
PURPOSE: Little research has been done to identify possible cancer-related fatigue (CRF) subtypes and to classify cancer survivors accordingly. We aimed to identify CRF subtypes in a large population-based sample of (long term) stage I-III colorectal cancer survivors. We also identified factors associated with the CRF subtypes. METHODS: Respondents completed the Multidimensional Fatigue Inventory and other validated questionnaires on anxiety and reduced positive affect (anhedonia), sleep quality, and lifestyle factors (body mass index and physical activity). Latent class analysis was used to derive the CRF subtypes. Factors associated with the derived CRF subtypes were determined with multinomial logistic regression. RESULTS: Three CRF classes were identified: class 1 (no fatigue and distress, n = 644, 56%), class 2 (low fatigue, moderate distress, n = 256, 22%), and class 3 (high fatigue, moderate distress, n = 256, 22%). Multinomial logistic regression results show that survivors in class 3 were more likely to be female, were treated with radiotherapy, have comorbid diabetes mellitus, and be overweight/obese than survivors in class 1 (reference). Survivors in classes 2 and 3 were also more likely to have comorbid heart condition, report poorer sleep quality, experience anhedonia, and report more anxiety symptoms when compared with survivors in class 1. CONCLUSIONS: Three distinct classes of CRF were identified which could be differentiated with sleep quality, anxiety, anhedonia, and lifestyle factors. IMPLICATIONS FOR CANCER SURVIVORS: The identification of CRF subtypes with distinct characteristics suggests that interventions should be targeted to the CRF subtype.
PURPOSE: Little research has been done to identify possible cancer-related fatigue (CRF) subtypes and to classify cancer survivors accordingly. We aimed to identify CRF subtypes in a large population-based sample of (long term) stage I-III colorectal cancer survivors. We also identified factors associated with the CRF subtypes. METHODS: Respondents completed the Multidimensional Fatigue Inventory and other validated questionnaires on anxiety and reduced positive affect (anhedonia), sleep quality, and lifestyle factors (body mass index and physical activity). Latent class analysis was used to derive the CRF subtypes. Factors associated with the derived CRF subtypes were determined with multinomial logistic regression. RESULTS: Three CRF classes were identified: class 1 (no fatigue and distress, n = 644, 56%), class 2 (low fatigue, moderate distress, n = 256, 22%), and class 3 (high fatigue, moderate distress, n = 256, 22%). Multinomial logistic regression results show that survivors in class 3 were more likely to be female, were treated with radiotherapy, have comorbid diabetes mellitus, and be overweight/obese than survivors in class 1 (reference). Survivors in classes 2 and 3 were also more likely to have comorbid heart condition, report poorer sleep quality, experience anhedonia, and report more anxiety symptoms when compared with survivors in class 1. CONCLUSIONS: Three distinct classes of CRF were identified which could be differentiated with sleep quality, anxiety, anhedonia, and lifestyle factors. IMPLICATIONS FOR CANCER SURVIVORS: The identification of CRF subtypes with distinct characteristics suggests that interventions should be targeted to the CRF subtype.
Entities:
Keywords:
Cancer; Fatigue subtypes; Latent class analysis; Population-based; Survivors
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