Identifying the subtypes of cancer-related fatigue: results from the population-based PROFILES registry.
Từ khóa
trừu tượng
OBJECTIVE
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.
CONCLUSIONS
The identification of CRF subtypes with distinct characteristics suggests that interventions should be targeted to the CRF subtype.
