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. 2014 Nov 25;17(1):19227.
doi: 10.7448/IAS.17.1.19227. eCollection 2014.

Measuring adherence to antiretroviral therapy in children and adolescents in western Kenya

Rachel C Vreeman  1 , Winstone M Nyandiko  2 , Hai Liu  3 , Wanzhu Tu  3 , Michael L Scanlon  4 , James E Slaven  3 , Samuel O Ayaya  2 , Thomas S Inui  5
Affiliations

Measuring adherence to antiretroviral therapy in children and adolescents in western Kenya

Rachel C Vreeman et al. J Int AIDS Soc. .

Abstract

Introduction: High levels of adherence to antiretroviral therapy (ART) are central to HIV management. The objective of this study was to compare multiple measures of adherence and investigate factors associated with adherence among HIV-infected children in western Kenya.

Methods: We evaluated ART adherence prospectively for six months among HIV-infected children aged ≤14 years attending a large outpatient HIV clinic in Kenya. Adherence was reported using caregiver report, plasma drug concentrations and Medication Event Monitoring Systems (MEMS®). Kappa statistics were used to compare adherence estimates with MEMS®. Logistic regression analyses were performed to assess the association between child, caregiver and household characteristics with dichotomized adherence (MEMS® adherence ≥90% vs. <90%) and MEMS® treatment interruptions of ≥48 hours. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated.

Results: Among 191 children, mean age at baseline was 8.2 years and 55% were female. Median adherence by MEMS® was 96.3% and improved over the course of follow-up (p<0.01), although 49.5% of children had at least one MEMS® treatment interruption of ≥48 hours. Adherence estimates were highest by caregiver report, and there was poor agreement between MEMS® and other adherence measures (Kappa statistics 0.04-0.37). In multivariable logistic regression, only caregiver-reported missed doses in the past 30 days (OR 1.25, 95% CI 1.14-1.39), late doses in the past seven days (OR 1.14, 95% CI 1.05-1.22) and caregiver-reported problems with getting the child to take ART (OR 1.10, 95% CI 1.01-1.20) were significantly associated with dichotomized MEMS® adherence. The caregivers reporting that ART made the child sick (OR 1.12, 95% CI 1.01-1.25) and reporting difficulties in the community that made giving ART more difficult (e.g. stigma) (OR 1.14, 95% CI 1.02-1.27) were significantly associated with MEMS® treatment interruptions in multivariable logistic regression.

Conclusions: Non-adherence in the form of missed and late doses, treatment interruptions of more than 48 hours and sub-therapeutic drug levels were common in this cohort. Adherence varied significantly by adherence measure, suggesting that additional validation of adherence measures is needed. Few factors were consistently associated with non-adherence or treatment interruptions.

Keywords: adherence; best practice; paediatric HIV; resource-limited setting.

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Figures

Figure 1
Figure 1
Values: Mean adherence by multiple measures with 95% confident intervals
See this image and copyright information in PMC

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