Abstract

Abstract The majority of studies on depression among cancer survivors report means or percentages which obscure the heterogeneity of women's responses to cancer. Trajectory analysis provides a more nuanced picture of different patterns of response. Purpose: To identify, in a large sample of breast cancer survivors, distinct groups of women exhibiting different patterns (trajectories) of depressive symptoms up to 24 months following a breast cancer diagnosis, and to identify characteristics associated with these patterns. Methods: 653 women within 8 months of initial breast cancer diagnosis completed questionnaires at baseline and 6, 12, and 18 months after baseline on contextual/patient characteristics, symptoms, and psychosocial variables. Chart reviews provided cancer and treatment-related data. The primary outcome was depressive symptomatology assessed by the Beck Depression Inventory (BDI). Finite mixture modeling was used to identify trajectories of depressive symptoms. Results: Based on a combination of the Bayesian Information Criterion and observation of trajectory distinctiveness, a 6-trajectory model was chosen. Almost half of the sample had a consistently very low (3.8%) or low (46%) level of depressive symptoms over time that was well below the traditional BDI cut-point of 10 thought to be indicative of clinically significant depression; 29.8% had a consistently borderline BDI score that hovered around 10; 12.1% had initially high BDI, but showed a decline over time; 7.2% showed an increased BDI over time; and a small but distinct group (1.2%) reported a chronically high BDI above 25. Women in the lower depressive symptom groups were older, had fewer physical symptoms (fatigue and pain), less rigorous chemotherapy, and lower levels of illness intrusiveness. Additional analyses also showed that to some degree, illness intrusiveness, pain, and social support scores over time paralleled BDI trajectories. Conclusions: Trajectory analysis allowed us to detect heterogeneity among women in reporting depressive symptoms following a breast cancer diagnosis. Our larger sample size identified more trajectories than other smaller studies. Mean levels of various characteristics at baseline and over time were identified that were significantly associated with each trajectory.

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