Multimethod assessment of baseline depression and relationship to hepatitis C treatment discontinuation. (July 2018) - Weiss, Jeffrey J; Prieto, Sarah; Bräu, Norbert; Dieterich, Douglas T; Marcus, Sue M; Stivala, Alicia; Gorman, Jack M
Objective: The primary study objective is to determine which measures of depression are associated with early discontinuation of hepatitis C virus infection treatment and to determine which measure best characterizes the depression that develops during treatment. Methods: Seventy-eight treatment-naïve subjects who initiated pegylated interferon/ribavirin treatment for hepatitis C virus infection were included. Baseline depression was assessed with the Structured Interview for the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV), the Hamilton Depression Rating Scale, and the Beck Depression Inventory-II. The latter two measures were repeated at treatment weeks 12 and 24. Results: Depression scores, as measured by the three instruments, lacked adequate consistency. Baseline depression as measured by the Beck Depression Inventory-II, but not by the other scales, was associated with early treatment discontinuation at weeks 12 and 24. Changes in depression during treatment were restricted to somatic symptoms. Of those who completed treatment, those who were not depressed at baseline tended to demonstrate significant depression increases during treatment. Conclusion: The Beck Depression Inventory-II is recommended to assess depression prior to hepatitis C virus infection treatment. Somatic symptoms of depression should be monitored during treatment. Baseline depression as measured by the Beck Depression Inventory-II was associated with early treatment discontinuation. The Beck Depression Inventory-II, Structured Interview for DSM-IV, and Hamilton Depression Rating Scale yielded results that were not consistent with each other in this sample. Future research should focus on standardizing depression assessment in medically ill populations to identify measures that predict treatment discontinuation.