Consequences of prior use of full-dose ritonavir as single protease inhibitor as part of combination antiretroviral regimens on the future therapy choices in HIV-1-infected children

Key Factors Influencing the Emergence of Human Immunodeficiency Virus Drug Resistance in Low- and Middle-Income Countries

The emergence and spread of human immunodeficiency virus (HIV) drug resistance from antiretroviral roll-out programs remain a threat to long-term control of the HIV-AIDS epidemic in low- and middle-income countries (LMICs). The patterns of drug resistance and factors driving emergence of resistance are complex and multifactorial. The key drivers of drug resistance in LMICs are reviewed here, and recommendations are made to limit their influence on antiretroviral therapy efficacy.

Factors Associated with the Development of Drug Resistance Mutations in HIV-1 Infected Children Failing Protease Inhibitor-Based Antiretroviral Therapy in South Africa

OBJECTIVE

Limited data are available from the developing world on antiretroviral drug resistance in HIV-1 infected children failing protease inhibitor-based antiretroviral therapy, especially in the context of a high tuberculosis burden. We describe the proportion of children with drug resistance mutations after failed protease inhibitor-based antiretroviral therapy as well as associated factors.

METHODS

Data from children initiated on protease inhibitor-based antiretroviral therapy with subsequent virological failure referred for genotypic drug resistance testing between 2008 and 2012 were retrospectively analysed. Frequencies of drug resistance mutations were determined and associations with these mutations identified through logistic regression analysis.

RESULTS

The study included 65 young children (median age 16.8 months [IQR 7.8; 23.3]) with mostly advanced clinical disease (88.5% WHO stage 3 or 4 disease), severe malnutrition (median weight-for-age Z-score -2.4 [IQR -3.7;-1.5]; median height-for-age Z-score -3.1 [IQR -4.3;-2.4]), high baseline HIV viral load (median 6.04 log10, IQR 5.34;6.47) and frequent tuberculosis co-infection (66%) at antiretroviral therapy initiation. Major protease inhibitor mutations were found in 49% of children and associated with low weight-for-age and height-for-age (p = 0.039; p = 0.05); longer duration of protease inhibitor regimens and virological failure (p = 0.001; p = 0.005); unsuppressed HIV viral load at 12 months of antiretroviral therapy (p = 0.001); tuberculosis treatment at antiretroviral therapy initiation (p = 0.048) and use of ritonavir as single protease inhibitor (p = 0.038). On multivariate analysis, cumulative months on protease inhibitor regimens and use of ritonavir as single protease inhibitor remained significant (p = 0.008; p = 0.033).

CONCLUSION

Major protease inhibitor resistance mutations were common in this study of HIV-1-infected children, with the timing of tuberculosis treatment and subsequent protease inhibitor dosing strategy proving to be important associated factors. There is an urgent need for safe, effective, and practicable HIV/tuberculosis co-treatment in young children and the optimal timing of treatment, optimal dosing of antiretroviral therapy, and alternative tuberculosis treatment strategies should be urgently addressed.

Viral load versus CD4⁺ monitoring and 5-year outcomes of antiretroviral therapy in HIV-positive children in Southern Africa: a cohort-based modelling study

OBJECTIVES

Many paediatric antiretroviral therapy (ART) programmes in Southern Africa rely on CD4⁺ to monitor ART. We assessed the benefit of replacing CD4⁺ by viral load monitoring.

DESIGN

A mathematical modelling study.

METHODS

A simulation model of HIV progression over 5 years in children on ART, parameterized by data from seven South African cohorts. We simulated treatment programmes with 6-monthly CD4⁺ or 6- or 12-monthly viral load monitoring. We compared mortality, second-line ART use, immunological failure and time spent on failing ART. In further analyses, we varied the rate of virological failure, and assumed that the rate is higher with CD4⁺ than with viral load monitoring.

RESULTS

About 7% of children were predicted to die within 5 years, independent of the monitoring strategy. Compared with CD4⁺ monitoring, 12-monthly viral load monitoring reduced the 5-year risk of immunological failure from 1.6 to 1.0% and the mean time spent on failing ART from 6.6 to 3.6 months; 1% of children with CD4⁺ compared with 12% with viral load monitoring switched to second-line ART. Differences became larger when assuming higher rates of virological failure. When assuming higher virological failure rates with CD4⁺ than with viral load monitoring, up to 4.2% of children with CD4⁺ compared with 1.5% with viral load monitoring experienced immunological failure; the mean time spent on failing ART was 27.3 months with CD4⁺ monitoring and 6.0 months with viral load monitoring. Conclusion: Viral load monitoring did not affect 5-year mortality, but reduced time on failing ART, improved immunological response and increased switching to second-line ART.