Abstract

Estimates of incidence of switching to second-line antiretroviral therapy (ART) among children with HIV are necessary to inform the need for paediatric second-line formulations. We aimed to quantify the cumulative incidence of switching to second-line ART among children in an international cohort collaboration. In this international cohort collaboration study, we pooled individual patient-level data for children younger than 18 years who initiated ART (two or more nucleoside reverse-transcriptase inhibitors [NRTI] plus a non-NRTI [NNRTI] or boosted protease inhibitor) between 1993 and 2015 from 12 observational cohort networks in the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) Global Cohort Collaboration. Patients who were reported to be horizontally infected with HIV and those who were enrolled in trials of treatment monitoring, switching, or interruption strategies were excluded. Switch to second-line ART was defined as change of one or more NRTI plus either change in drug class (NNRTI to protease inhibitor or vice versa) or protease inhibitor change, change from single to dual protease inhibitor, or addition of a new drug class. We used cumulative incidence curves to assess time to switching, and multivariable proportional hazards models to explore patient-level and cohort-level factors associated with switching, with death and loss to follow-up as competing risks. At the data cutoff of Sept 16, 2015, 182 747 children with HIV were included in the CIPHER dataset, of whom 93 351 were eligible, with 83 984 (90·0%) from sub-Saharan Africa. At ART initiation, the median patient age was 3·9 years (IQR 1·6-6·9) and 82 885 (88·8%) patients initiated NNRTI-based and 10 466 (11·2%) initiated protease inhibitor-based regimens. Median duration of follow-up after ART initiation was 26 months (IQR 9-52). 3883 (4·2%) patients switched to second-line ART after a median of 35 months (IQR 20-57) of ART. The cumulative incidence of switching at 3 years was 3·1% (95% CI 3·0-3·2), but this estimate varied widely depending on the cohort monitoring strategy, from 6·8% (6·5-7·2) in settings with routine monitoring of CD4 (CD4% or CD4 count) and viral load to 0·8% (0·6-1·0) in settings with clinical only monitoring. In multivariable analyses, patient-level factors associated with an increased likelihood of switching were male sex, older age at ART initiation, and initial NNRTI-based regimen (p<0·0001). Cohort-level factors that increased the likelihood of switching were higher-income country (p=0·0017) and routine or targeted monitoring of CD4 and viral load (p<0·0001), which was associated with a 166% increase in likelihood of switching compared with CD4 only monitoring (subdistributional hazard ratio 2·66, 95% CI 2·22-3·19). Our global paediatric analysis found wide variations in the incidence of switching to second-line ART across monitoring strategies. These findings suggest the scale-up of viral load monitoring would probably increase demand for paediatric second-line ART formulations. International AIDS Society-CIPHER.

Highlights

  • In 2017, an estimated 1·8 million children were living with HIV worldwide, of whom 52% had access to antiretroviral therapy (ART).[1]

  • The cumulative incidence of switching at 3 years was 3·1%, but this estimate varied widely depending on the cohort monitoring strategy, from 6·8% (6·5–7·2) in settings with routine monitoring of CD4 (CD4% or CD4 count) and viral load to 0·8% (0·6–1·0) in settings with clinical only monitoring

  • Patient-level factors associated with an increased likelihood of switching were male sex, older age at ART initiation, and initial NNRTI-based regimen (p

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Summary

Introduction

In 2017, an estimated 1·8 million children (younger than 15 years) were living with HIV worldwide, of whom 52% had access to antiretroviral therapy (ART).[1]. Achievement of this goal requires a comprehensive understanding of the durability of first-line ART regimens and patterns of switching to second-line ART across geo­ graphical regions and different country-income settings to ensure future treatment needs are met.[5]

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