A Statistical Analysis of Effects of Treatment Adherence on Medical End Points

• Activity Number: 603
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): Sayan Dasgupta*+ and Denise Esserman and Michael R. Kosorok and Donna M. Evon
• Companies: The University of North Carolina at Chapel HIll and The University of North Carolina at Chapel HIll and The University of North Carolina-Chapel Hill and The University of North Carolina at Chapel HIll
• Keywords: Sustained Virologic Response ; Epidemiology ; Adherence ; Temporal Process Regression

Abstract

In medicine, adherence describes the extent to which a patient continues the agreed mode of treatment under limited supervision when faced with conflicting demands, and most commonly it refers to medication or drug adherence. Worldwide, non-adherence is a major obstacle to the effective delivery of healthcare and it often results in poor drug therapy outcomes. In this paper we assess the effect of drug adherence, measured by Medication Event Monitoring System (MEMS) caps in the study of Viral Resistance to Antiviral Therapy for Chronic Hepatitis C. The primary end point in this study is the sustained virologic response (SVR) measured six months post treatment in a group of 401 subjects on a treatment regime of the combined Ribavirin-Peginterferon drug therapy for a total of 24 weeks. We use Temporal Process Regression (Fine et. al., 2004) to model adherence as a longitudinal predictor of SVR. We show that adherence in this setting has a significant effect on SVR and we show that this analysis can be served as an archetype for more statistically efficient analyses of treatment-adherence in medical studies, where the common theme till now has been to report summary statistics.