PROJECT SUMMARY The treatment of rheumatoid arthritis (RA) has changed substantially in the last two decades with the development of new biologic and targeted therapies which modulate the immune system. It is well accepted that these agents do not increase risk of developing new cancers, however, their safety in patients with RA who have concomitant cancer is controversial given their immunomodulatory potential which could increase the risk of cancer progression or recurrence, and result in the development of other adverse events such as infections. Decision making in complex situations, as is the case for patients with RA and cancer who need treatment for their arthritis, can be challenging in the face of uncertainty. The potential effects of biologic and targeted RA therapies on cancer progression and survival in patients with cancer are largely unknown, precluding development of risk models and tools that can aid in these complex decisions. We are proposing this study to fill current gaps in knowledge in several areas. First, we will perform secondary data analyses of the Surveillance, Epidemiology and End Results (SEER), Texas Cancer Registry (TCR) Medicare linked files, Optum Clinformatics Data Mart, and The University of Texas MD Anderson Cancer Center electronic health records. We will examine the association of use of biologic and targeted therapies in patients with RA and concomitant cancer, with survival across various cancer types. Second, using the same datasets, we will evaluate other safety outcomes including serious infections, unplanned hospitalizations and new primary malignancies. Third, in order to understand the informational needs of patients with RA and concomitant cancer, we will conduct cognitive interviews of patients with both diseases to assess their beliefs with respect to the potential harms and benefits of biologic and targeted therapies for RA, and their preferences. Lastly, we will conduct interviews with rheumatologists and oncologists to ascertain their beliefs and decision-making data needs for choosing RA therapies in patients with concomitant cancer. Our ultimate goal is to use the information gained with this study to develop a risk prediction model and decision tool that can assist patients with RA and cancer, and their physicians, in making informed choices about RA treatment. Results of this study will have a great impact as approximately 1.5 million people in the United States have RA, and one in three men and one in two women will develop cancer over their lifetime, facing complex therapeutic decisions about their treatments. Investigators in this proposal have an excellent track record of successful observational studies and our preliminary data demonstrates the feasibility of the proposed study objectives. The knowledge gained from this clinical observational study will lay the groundwork needed to design a future clinical study evaluating a treatment decision-making aid.