Purpose of the Study
Pediatric human immunodeficiency virus (HIV) infection may have unique pathogenic features that preclude routine extrapolation of laboratory monitoring results from adult studies. This present study was designed to evaluate the prognostic value of plasma HIV RNA and CD4+ T lymphocyte count for HIV disease progression in infants and children.
Data from a “cohort” of 566 infants and children were analyzed. Assays were performed with standard techniques. Clinical trial endpoints consisted of time to first HIV disease progression or death.
Baseline plasma RNA levels were high relative to adult levels, and both baseline RNA and CD4+ T-cell counts were independently predictive of subsequent clinical course. For each log10 reduction in baseline RNA with treatment was associated with a risk reduction of approximately 50%. Disease progression predictive power was enhanced by the combined use of plasma HIV RNA and CD4+ T-cell counts. Plasma RNA <10 000 copies/mL, or CD4+ T-cell counts >500/μL (for children <6.5 years of age) or greater >200/μL (for children >6.5 years of age) were associated with a 2-year disease progression rate of >5%.
Two key laboratory markers, plasma HIV RNA and CD4+ T-cell counts, are independent predictors of clinical course among HIV-infected pediatric patients. The linear, age-independent relationship between plasma RNA and relative risk of disease progression strongly supports therapeutic efforts to achieve plasma virus levels as low as possible, and to maintain these levels as long as possible.
For some time it has been assumed from adult data that low T-cell numbers and high virus levels were bad for HIV-infected patients. This paper quantitatively assesses the impact of these two predictive markers and clearly indicates that they are independent predictors of clinical course. Increasingly, these “surrogate” markers of disease progression are being used as primary endpoints in clinical trials because of the type of data presented in this paper. The impact of this method of analysis is that results of clinical trials will be available more quickly with more rapid availability of novel treatment regimens being made available.