Optimizing treatment combinations in individuals with multiple chronic conditions Depression is prevalent in individuals with other chronic conditions, leads to worse prognoses related to those comorbid conditions, and is itself a major cause of morbidity. Certain SSRI antidepressant drugs, which are among the most widely used medications in the United States, can interact with medications used to treat other chronic conditions, including certain antiplatelet agents used to treat acute coronary syndromes in patients with coronary artery disease;tamoxifen, used to treat breast cancer;and warfarin, used to prevent stroke in patients with atrial fibrillation. However, the clinical consequences of most drug-drug interactions (DDIs) are not well understood because these cannot be easily studied in pre-marketing trials, particularly in patients with multiple chronic conditions. Observational studies in large, longitudinal, electronic healthcare databases have emerged as a promising source for investigating outcomes related to DDIs. We have previously developed a modular program that can be used with electronic healthcare databases to rapidly assess outcomes related to drug treatment. The program implements a propensity-score matched new user cohort design to compare outcomes of different treatments. In this project, we will adapt the existing module to accommodate DDI exposures. We will apply the new module to rapidly investigate clinical outcomes related to DDIs in patients with depression and other chronic conditions requiring drug therapy. We will then make the program publicly available so that it can be applied to study DDIs in other multiple chronic conditions settings. Specifically, we will:
Aim 1. Modify existing semi-automated programs for rapid DDI assessment in secondary electronic healthcare data.
Aim 2. Apply DDI programs to rapidly evaluate clinical outcomes related to potential DDIs in three multiple chronic condition settings involving depression: - Coronary artery disease and depression: We will determine the optimal combination of antiplatelet agent and antidepressant for patients with coronary artery disease and depression. - Breast cancer and depression: We will determine the best choice of antidepressant among with breast cancer treated with tamoxifen. - Atrial fibrillation and depression: We will identify the optimal combination of anticoagulant and antidepressant agent for patients with atrial fibrillation and depression.
Aim 3. Develop dissemination materials and make DDI programs publicly available for application to other multiple chronic condition settings.

Public Health Relevance

Depression commonly occurs in individuals with other chronic conditions and certain antidepressant drugs can interact with medications for other chronic conditions, reducing the effectiveness of those medications or increasing the chance of side effects. This project will generate evidence about optimal treatment decisions for patients with multiple chronic conditions involving depression. The methods will be made publicly available so that they can be used to study optimal treatment decisions in other multiple chronic condition settings.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Project (R01)
Project #
1R01HS023122-01
Application #
8727769
Study Section
Special Emphasis Panel (ZHS1-HSR-X (01))
Program Officer
Ricciardi, Richard
Project Start
2014-06-01
Project End
2015-11-30
Budget Start
2014-06-01
Budget End
2015-11-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Bykov, Katsiaryna; Schneeweiss, Sebastian; Donneyong, Macarius M et al. (2017) Impact of an Interaction Between Clopidogrel and Selective Serotonin Reuptake Inhibitors. Am J Cardiol 119:651-657
Hennessy, S; Leonard, C E; Gagne, J J et al. (2016) Pharmacoepidemiologic Methods for Studying the Health Effects of Drug-Drug Interactions. Clin Pharmacol Ther 99:92-100