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AIDS Res Hum Retroviruses. 2013 Jul;29(7):985-92. doi: 10.1089/AID.2013.0025. Epub 2013 Apr 27.

Extensive drug resistance in HIV-infected Cambodian children who are undetected as failing first-line antiretroviral therapy by WHO 2010 guidelines.

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Division of Infectious Diseases, Alpert Medical School, Brown University, Providence, RI 02906, USA.


Antiretroviral therapy in resource-limited settings is monitored clinically and immunologically according to WHO guidelines. Frequent misclassification of virologic failure is reported, mostly in adults, leading to early therapy switch or late failure diagnosis. Pediatric treatment monitoring and resistance data upon first-line failure are limited, particularly when the 2010-WHO pediatric guidelines are used without routine viral load monitoring. We previously reported high treatment failure misclassification rates by pediatric 2010 guidelines in Cambodian children on first-line therapy. Here we determine the extent and patterns of resistance, with yearly viral load and 6-monthly CD4. Drug resistance mutations were determined using the IAS-USA 2011 list. Predicted resistance interpretation was determined with Stanford Database tools. Fifty-one children with available genotypes met inclusion criteria. All but one (subtype B) were CRF01_AE. The most common regimen was stavudine, lamivudine, and nevirapine (96%), taken for a median of 2.2 years. Resistance was seen in 98%; 96% to nucleoside and nonnucleoside reverse transcriptase inhibitors (NRTIs and NNRTIs); 51% with ≥4 mutations. The most common NRTI mutations were 184V/I and 67N and the most common NNRTI mutations were 181C/Y/I/V and 190A/S. A total of 22% had multiresistant mutations and 18% had predicted high-level resistance to subsequent therapy options didanosine, abacavir, etravirine, and tenofovir. In 98% of Cambodian children misclassified as nonfailing first-line therapy by 2010 guidelines, 51% had extensive drug resistance to current and 18% to subsequent antiretroviral therapy. Affordable routine viral load monitoring allowing for early and more accurate treatment failure diagnosis is desperately needed in resource-limited settings.

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