Author:

Keywords:

Adult, Algorithms, Antiretroviral Therapy, Highly Active, CD4 Lymphocyte Count, Cluster Analysis, Electronics, Female, HIV Infections, HIV-1, Humans, Male, Middle Aged, Prospective Studies, RNA, Viral, Time Factors, Treatment Outcome, Treatment Refusal, Viral Load, Science & Technology, Life Sciences & Biomedicine, Immunology, Infectious Diseases, Virology, DRUG REGIMEN, AIDS, ADHERENCE, INFECTION, 1103 Clinical Sciences, 3202 Clinical sciences

Abstract:

Adherence to highly active antiretroviral therapy (HAART) is crucial, but which aspects of drug-taking behavior are important remain largely unknown. In a prospective observational study, 43 HIV-1-infected patients taking HAART underwent electronic event monitoring (EEM). Taking adherence was defined as the percentage of doses taken compared with the number prescribed, dosing adherence was defined as the percentage of days on which all doses were taken, and timing adherence was defined as the percentage of doses taken within 1 hr of the time prescribed. Drug holidays were defined as periods of no drug intake for >24 hr. Cluster analysis, including the four EEM parameters, was used and refined to construct an algorithm to discriminate patients. Patients were categorized as nonadherent if they had a taking adherence of < /90%, or a dosing adherence of < /75% and at least 1 drug holiday, or a timing adherence of < /80% and at least 1 drug holiday, or >6 drug holidays per 100 days. All four EEM parameters differed significantly (p < / 0.0001) between the two groups. Adherent patients had a better outcome, as shown by a larger drop in viral load (p = 0.011) and rise in CD4+ cell count (p = 0.035), showing that the algorithm-based categorization is clinically relevant.