Vu Phuong Linh Dang, Dinh Thi Thanh, Nguyen Hai Quan, Le Thanh Hai, Nyugen Van Lam, Pham Viet Hung
Hanoi University of Public Health
Background and Objectives: Over the past decades, there has been increased access to antiretroviral therapy (ART) in HIV infected children; however, HIV infected children suffer from significantly higher level of treatment failure (TF) compared to adult counterparts. There are currently two standard markers that have proved to be the best markers for treatment failure including CD4 T cell counts and HIV viral load. However, other biomedical markers might also to play a role in demonstrating a better prognosis of the response to treatment. Therefore, we monitored the changes of numbers of markers in relation to treatment response.
Methods: A nested case-control study was conducted with clinical data collected from 100 HIV-infected children at National Hospital of Pediatrics, Vietnam (2008-2012). The independent variables collected every 6 months included: age, gender, HBV vaccination, height, weight, opportunistic infection (1-4 clinical stage according to WHO guidelines), serum hemoglobin, platelet count, CD4 T cell count, CD4 percentage, HIV RNA viral load, liver enzyme alanine transaminase (ALT), serum aspartate aminotransferase (AST), creatinine, cholesterol, triglyceride, lymphocyte percentage, numbers of red blood cell and white blood cell, total immunoglobulin. The data were collected and managed by Epidata 3.1 and analyzed by Stata 12.0.20 for descriptive statistic, statistical inference, and survival analysis.
Results:The results showed that certain factors including height, weight, vaccination against Hepatitis B, and platelet levels were significantly different before treatment was started between those patients whose subsequent treatment failed and those where treatment was successful,. In addition, the age at which treatment was started, CD4 percentage, opportunistic infection, HAZ (height for age), IgG and IgA were found to significantly predict treatment outcome most frequently, implying the importance of clinical markers in the treatment response by Cox regression analysis.