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Published on: June 21, 2024
Higher stress and symptom severity are associated with worse depressive symptom profiles in patients receiving
Kate Oppegaard1, Joosun Shin1, Carolyn S Harris1
1School of Nursing, University of California, San Francisco, CA, USA.
Purpose:
In a sample of oncology patients, identify subgroups of patients with distinct depressive symptom profiles and evaluate for differences in demographic and clinical characteristics, levels of stress and resilience, and the severity of common co-occurring symptoms.
Methods:
Patients (n = 1327) had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; and were scheduled to receive at least two additional cycles of chemotherapy. Demographic and clinical characteristics, stress, resilience, and co-occurring symptoms were evaluated at enrollment. Depressive symptoms were evaluated using the Center for Epidemiological Studies-Depression (CES-D) scale a total of six times over two cycles of chemotherapy. Latent profile analysis (LPA) was used to identify subgroups of patients (i.e., latent classes) with distinct depressive symptom profiles using the six CES-D scores.
Results:
Based on the findings from the LPA, 47.3% of the patients were classified as "None"; 33.6% as "Subsyndromal"; 13.8% as "Moderate"; and 5.3% as "High". Compared to None class, patients in the Subsyndromal, Moderate, and High classes had a lower functional status, a higher comorbidity burden, and a self-reported diagnosis of depression or back pain. Those patients with higher levels of depressive symptoms reported higher levels of stress, lower levels of resilience, and increased severity of co-occurring symptoms.
Conclusions:
Inter-individual variability in depressive symptoms was associated with demographic and clinical characteristics, multiple types of stress and levels of resilience, as well as with the increased severity of multiple co-occurring symptoms. The risk factors associated with worse depressive symptom profiles can assist clinicians to identify high risk patients and initiate more timely supportive care interventions.
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