Real-time adherence monitoring for HIV antiretroviral therapy

Jessica E Haberer, Josh Kahane, Isaac Kigozi, Nneka Emenyonu, Peter Hunt, Jeffrey Martin, David R Bangsberg, Jessica E Haberer, Josh Kahane, Isaac Kigozi, Nneka Emenyonu, Peter Hunt, Jeffrey Martin, David R Bangsberg

Abstract

Current adherence assessments typically detect missed doses long after they occur. Real-time, wireless monitoring strategies for antiretroviral therapy may provide novel opportunities to proactively prevent virologic rebound and treatment failure. Wisepill, a wireless pill container that transmits a cellular signal when opened, was pilot tested in ten Ugandan individuals for 6 months. Adherence levels measured by Wisepill, unannounced pill counts, and self-report were compared with each other, prior standard electronic monitoring, and HIV RNA. Wisepill data was initially limited by battery life and signal transmission interruptions. Following device improvements, continuous data was achieved with median (interquartile range) adherence levels of 93% (87-97%) by Wisepill, 100% (99-100%) by unannounced pill count, 100% (100-100%) by self-report, and 92% (79-98%) by prior standard electronic monitoring. Four individuals developed transient, low-level viremia. After overcoming technical challenges, real-time adherence monitoring is feasible for resource-limited settings and may detect suboptimal adherence prior to viral rebound.

Figures

Fig. 1
Fig. 1
The Wisepill device
Fig. 2
Fig. 2
Median adherence levels by multiple measures averaged over the two 3-month study periods. * MEMS data was recorded during the 3 months just prior to the initiation of this study
Fig. 3
Fig. 3
Adherence dot plots for the 14 days prior to detection of the transient, low-level viremia seen in four participants. a HIV RNA 627 copies/ml (6/15/09; first 3-month period); b HIV RNA 134 copies/ml (8/11/09; second 3-month period); c HIV RNA 58 copies/ml (8/18/09; second 3-month period); d HIV RNA 51 copies/ml (8/24/09; second 3-month period)

References

    1. Kerr T, Walsh J, Lloyd-Smith E, et al. Measuring adherence to highly active antiretroviral therapy: implications for research and practice. Curr HIV/AIDS Rep. 2005;2(4):200–205. doi: 10.1007/s11904-005-0017-3.
    1. Parienti JJ, Das-Douglas M, Massari V, et al. Not all missed doses are the same: sustained NNRTI treatment interruptions predict HIV rebound at low-to-moderate adherence levels. PLoS One. 2008;3(7):e2783. doi: 10.1371/journal.pone.0002783.
    1. Bangsberg DR, Deeks SG. Spending more to save more: interventions to promote adherence. Ann Intern Med. 2010;152(1):54–56.
    1. Boyce JM, Cooper T, Dolan MJ. Evaluation of an electronic device for real-time measurement of alcohol-based hand rub use. Infect Control Hosp Epidemiol. 2009;30(11):1090–1095. doi: 10.1086/644756.
    1. Walji MF, Coker O, Valenza JA, et al. A persuasive toothbrush to enhance oral hygiene adherence. AMIA Annu Symp Proc. 2008; 1167.
    1. United Nations International Telecommunication Union. Measuring the information society – the ICT development index 2009. . Accessed 10 May 2010.
    1. Kahn JG, Yang JS, Kahn JS. “Mobile” health needs and opportunities in developing countries. Health Aff. 2010;29(2):252–258. doi: 10.1377/hlthaff.2009.0965.
    1. Schumacher W, Frick E, Kauselmann M, et al. Fully automated quantification of human immunodeficiency virus (HIV) type 1 RNA in human plasma by the COBAS AmpliPrep/COBAS TaqMan system. J Clin Virol. 2007;38(4):304–312. doi: 10.1016/j.jcv.2006.12.022.
    1. Oyugi JH, Byakika-Tusiime J, Ragland K, et al. Treatment interruptions predict resistance in HIV-positive individuals purchasing fixed-dose combination antiretroviral therapy in Kampala, Uganda. AIDS. 2007;21(8):965–971. doi: 10.1097/QAD.0b013e32802e6bfa.
    1. Oyugi JH, Byakika-Tusiime J, Charlebois ED, et al. Multiple validated measures of adherence indicate high levels of adherence to generic HIV antiretroviral therapy in a resource-limited setting. J Acquir Immune Defic Syndr. 2004;36(5):1100–1102. doi: 10.1097/00126334-200408150-00014.
    1. Byakika-Tusiime J, Crane J, Oyugi JH, et al. Longitudinal antiretroviral adherence in HIV + Ugandan parents and their children initiating HAART in the MTCT-Plus family treatment model: role of depression in declining adherence over time. AIDS Behav. 2009;13(Suppl 1):82–91. doi: 10.1007/s10461-009-9546-x.
    1. Simoni JM, Kurth AE, Pearson CR, et al. Self-report measures of antiretroviral therapy adherence: a review with recommendations for HIV research and clinical management. AIDS Behav. 2006;10(3):227–245. doi: 10.1007/s10461-006-9078-6.
    1. Hart JE, Jeon CY, Ivers LC, et al. Effect of directly observed therapy for highly active antiretroviral therapy on virologic, immunologic, and adherence outcomes: a meta-analysis and systematic review. J Acquir Immune Defic Syndr. 2010;54(2):167–179.
    1. Amico KR, Harman JJ, Johnson BT, et al. Efficacy of antiretroviral therapy adherence interventions: a research synthesis of trials, 1996 to 2004. J Acquir Immune Defic Syndr. 2006;41(3):285–297. doi: 10.1097/01.qai.0000197870.99196.ea.
    1. Murtaugh CM, Pezzin LE, McDonald MV, et al. Just-in-time evidence-based e-mail “reminders” in home health care: impact on nurse practices. Health Serv Res. 2005;40(3):849–864. doi: 10.1111/j.1475-6773.2005.00388.x.
    1. Intille SS. Ubiquitous computing technology for just-in-time motivation of behavior change. Stud Health Technol Inform. 2004;107(Pt 2):1434–1437.
    1. Holden RJ, Karsh BT. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43(1):159–172. doi: 10.1016/j.jbi.2009.07.002.
    1. Davis F. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13:319–339. doi: 10.2307/249008.
    1. Venkatesh V, Morris MG, David GB, et al. User acceptance of information technology: toward a unified view. MIS Q. 2003;27:425–478.
    1. Fishbein M, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley; 1975.
    1. Wendel CS, Mohler MJ, Kroesen K, et al. Barriers to use of electronic adherence monitoring in an HIV clinic. Ann Pharmacother. 2001;35(9):1010–1015. doi: 10.1345/aph.10349.
    1. Havlir DV, Bassett R, Levitan D, et al. Prevalence and predictive value of intermittent viremia with combination HIV therapy. JAMA. 2001;286(2):171–179. doi: 10.1001/jama.286.2.171.
    1. Podsadecki TJ, Vrijens BC, Tousset EP, et al. Decreased adherence to antiretroviral therapy observed prior to transient human immunodeficiency virus type 1 viremia. J Infect Dis. 2007;196(12):1773–1778. doi: 10.1086/523704.
    1. Bangsberg DR, Hecht FM, Charlesbois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS. 2000;14(4):357–366. doi: 10.1097/00002030-200003100-00008.
    1. Bangsberg DR, Perry S, Charlesbois ED, et al. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. AIDS. 2001;15(9):1181–1183. doi: 10.1097/00002030-200106150-00015.
    1. Hogg RS, Heath K, Bangsberg D, et al. Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up. AIDS. 2002;16(7):1051–1058. doi: 10.1097/00002030-200205030-00012.
    1. Bisson GP, Gross R, Bellamy S, et al. Pharmacy refill adherence compared with CD4 count changes for monitoring HIV-infected adults on antiretroviral therapy. PLoS Med. 2008;5(5):e109. doi: 10.1371/journal.pmed.0050109.

Source: PubMed

Подписаться