Prospective trajectories of depression predict mortality in cancer patients.

TitleProspective trajectories of depression predict mortality in cancer patients.
Publication TypeJournal Article
Year of PublicationForthcoming
AuthorsSanghvi, DEnna, Chen, MShuquan, Bonanno, GA
JournalJournal of Behavioral Medicine
ISSN Number1573-3521
KeywordsCancer, depression, Latent growth mixture modeling, Mortality

An ever-growing body of empirical evidence has demonstrated the relationship between depression and cancer. The objective of this study was to examine whether depression trajectories predict mortality risk above and beyond demographics and other general health-related factors. Participants (n = 2,345) were a part of the Health and Retirement Study. The sample consisted of patients who were assessed once before their cancer diagnosis and thrice after. Depressive symptoms and general health-related factors were based on self-reports. Mortality risk was determined based on whether the patient was alive or not at respective time points. Latent Growth Mixture Modeling was performed to map trajectories of depression, assess differences in trajectories based on demographics and general health-related factors, and predict mortality risk. Four trajectories of depression symptoms emerged: resilient (69.7%), emerging (13.5%), recovery (9.5%), and chronic (7.2%). Overall, females, fewer years of education, higher functional impairment at baseline, and high mortality risk characterized the emerging, recovery, and chronic trajectories. In comparison to the resilient trajectory, mortality risk was highest for the emerging trajectory and accounted for more than half of the deaths recorded for the participants in emerging trajectory. Mortality risk was also significantly elevated, although to a lesser degree, for the recovery and chronic trajectories. The data highlights clinically relevant information about the depression-cancer association that can have useful implications towards cancer treatment, recovery, and public health.

Citation Key13898
PubMed ID38615300
PubMed Central ID3847538
Grant ListU01-AG009740 / AG / NIA NIH HHS / United States