Utility of a cognitive-behavioral model to predict fatigue following breast cancer treatment

Abstract

The objective of the current study was twofold: (a) to determine whether subgroups of breast cancer patients could be identified on the basis of their distinct trajectory or pattern of fatigue following treatment for early stage cancer using growth mixture modeling and (b) to examine whether the subgroups could be distinguished on the basis of a cognitive-behavioral model. Growth mixture modeling and a prospective longitudinal design were used to examine the course of fatigue after treatment for early stage breast cancer. Women (n = 261; mean age = 55.2 years) provided fatigue ratings for 6 months following treatment. A low-fatigue group (n = 85) and a high-fatigue group (n = 176) were extracted. Women who were not married, had a lower income, had a higher body mass index, engaged in greater fatigue catastrophizing, and were lower in exercise participation were more likely to be in the high-fatigue group. Only body mass index and catastrophizing remained significant predictors in multivariate analysis. Findings suggest considerable heterogeneity in the experience of fatigue following treatment and support the utility of a cognitive-behavioral model in predicting the course of posttreatment fatigue.

Copyright 2007 APA.

Figures

Figure 1

One-class and two-class growth mixture models of fatigue across the 6-month period following the end of treatment.