An analysis of electronically monitored adherence to antiretroviral medications

Abstract

Medication adherence studies increasingly collect data electronically, often using Medication Event Monitoring System (MEMS) caps. Analyses typically focus on summary adherence measures, although more complete analyses are possible using adaptive statistical methods. These methods were used to describe individual-subject adherence patterns for MEMS data from a clinical trial. Subjects were adaptively clustered into groups with similar adherence patterns and clusters were compared on a variety of subject characteristics. There were seven different adherence clusters: consistently high, consistently moderately high, consistently moderate, consistently moderately low, consistently low, deteriorating starting early, and deteriorating late. Compared to other subjects, subjects with consistently high and consistently moderately high adherence were more likely to be male, White, and older and to maintain during study participation a CD4 cell count over 500 and an HIV viral load of at most 400 copies/ml. These results demonstrate the effectiveness of adaptive methods for comprehensive analysis of MEMS data. © 2010 Springer Science+Business Media, LLC.