Predictors of attrition in a cohort study of HIV infection and methamphetamine dependence

Abstract

Longitudinal cohort studies of HIV and substance use disorders play an important role in understanding these conditions, but high rates of attrition can threaten their integrity and generalizability. This study aimed to identify factors associated with attrition in a 5-year observational cohort study of 469 individuals with and without HIV infection and methamphetamine (MA) dependence. Rates of attrition in our four study groups were approximately 24% in HIV−MA−, 15% in HIV+MA−, 56% in HIV−MA+, and 47% in HIV+MA+ individuals. Predictors of attrition in the overall cohort included history of MA, alcohol, and other substance dependence, learning impairment, reduced cognitive reserve, and independence in activities of daily living (all ps < 0.05), but varied somewhat by clinical group. Of particular note, enrollment in a neuroimaging sub-study was associated with significantly boosted rates of retention in the MA groups. Results from this investigation highlight the complexity of the clinical factors that influence retention in cohort studies of HIV-infected MA users and might guide the development and implementation of targeted retention efforts.

• Longitudinal research
• methamphetamine dependence
• study attrition
• study retention

Acknowledgements

The Translational Methamphetamine AIDS Research Center (TMARC) group is affiliated with the University of California, San Diego (UCSD) and the Sanford-Burnham Medical Research Institute. The TMARC is comprised of: Director: Igor Grant, MD; Co-Directors: Ronald J. Ellis, MD, PhD, Cristian Achim, MD, PhD, and Scott Letendre, MD; Center Manager: Steven Paul Woods, PsyD.; Aaron Carr (Assistant Center Manager); Clinical Assessment and Laboratory Core: Scott Letendre, MD (PI), Ronald J. Ellis, MD, PhD, Rachel Schrier, PhD.; Neuropsychiatric Core: Robert K. Heaton, PhD (PI), J. Hampton Atkinson, MD, Mariana Cherner, PhD, Thomas Marcotte, PhD, Erin E. Morgan, PhD; Neuroimaging Core: Gregory Brown, PhD (PI), Terry Jernigan, PhD, Anders Dale, PhD, Thomas Liu, PhD, Miriam Scadeng, PhD, Christine Fennema-Notestine, PhD, Sarah L. Archibald, MA; Neurosciences and Animal Models Core: Cristian Achim, MD, PhD, Eliezer Masliah, MD, Stuart Lipton, MD, PhD; Participant Unit: J. Hampton Atkinson, MD, Jenn Marquie, MPH (Unit Manager); Data Management and Information Systems Unit: Anthony C. Gamst, PhD, Clint Cushman (Unit Manager); Statistics Unit: Ian Abramson, PhD (PI), Florin Vaida, PhD, Reena Deutsch, PhD, Anya Umlauf, MS; Project 1: Arpi Minassian, PhD (PI), William Perry, PhD, Mark Geyer, PhD, Brook Henry, PhD; Project 2: Amanda B. Grethe, PhD (PI), Martin Paulus, MD, Ronald J. Ellis, MD, PhD; Project 3: Sheldon Morris, MD, MPH (PI), David M. Smith, MD, MAS, Igor Grant, MD; Project 4: Svetlana Semenova, PhD (PI), Athina Markou, PhD; Project 5: Marcus Kaul, PhD (PI).

Declaration of interest

The authors report no conflicts of interest. This research was supported by National Institutes of Health grants T32-DA31098, P01-DA12065, P50-DA026306, L30-DA032120, and P30-MH62512. The views expressed in this article are those of the authors and do not reflect the official policy or position of the Department of the Navy, Department of Defense, nor the United States Government.