Abstract
Current HIV guidelines recommend monitoring CD4 counts every 3-4 months. In the era of highly active antiretroviral therapy (HAART) and HIV PCR, this retrospective study reexamines the required frequency of the CD4 assay. Predictor variables, including age, previous CD4 count, HIV viral load (VL), time interval since last VL and CD4 count (TINT), and antiretroviral history, were abstracted. A recursive partitioning-based regression tree analysis was used to determine if the absolute current CD4 count was above or below the age appropriate Pneumocystis jiroveci pneumonia (PCP) prophylaxis cutoff. We analyzed concurrently obtained VLs and CD4 count including 601 results from 43 HIV-infected children aged 1-<6 years (Group I) and 1,364 results from 93 children/adolescents 6-<23 years (Group II). Using 75% of observations to build a predictive model (learning dataset), the ability to correctly predict the range of the outcome variable in the remaining 25% of observations (training dataset) was 93% in Group I and 97% in Group II. Predictor variables included age, recent VL and CD4 count, and TINT. A total of 1,000 repeats of this model building using randomly selected observations showed a correct predictive ability of 89.6% [standard error (SE) 2.3%] in Group I and 95.6% (SE 1%) in Group II. The ability of a classification tree to determine if the current CD4 count is above or below the age-specific cutoff for PCP prophylaxis is very good and allows less frequent CD4 assays. The principles underlying this modeling-based approach have broad applicability and cost saving implications.