Low-cost enumeration of CD4+ T cells using a density-based negative selection method (RosetteSep) for the monitoring of HIV-infected individuals in non-OECD countries

Cytometry A. 2008 Jan;73(1):28-35. doi: 10.1002/cyto.a.20494.

Abstract

The CD4 count is the best surrogate marker for monitoring HIV. The reference method for assessing CD4 counts (flow cytometry, FCM), as expensive technique, is not widely used in non-OECD countries. To make HIV-monitoring available to more patients in these countries, we modified a commercially available density-based negative selection assay (RosetteSep) to make it applicable for low-cost cell enumeration. For evaluation (Step 1), blood taken from 25 HIV patients and 29 healthy donors was assayed with the modified negative selection method (MNS) and compared with FCM. For validation (Step 2), this method was performed in blind quintuplicates on 12 HIV+ blood samples according to FDA guidelines. Association of MNS with the FCM is given by regression models for both steps: Step 1: slope = 1.091, intercept = -46.5. Step 2: slope = 1.074, intercept = -38.3 (Step 2). The imprecision of MNS assessed during Step 2 was 21.2% (intraserial) and 18.8% (interserial). The results suggest that MNS is capable of providing an approximate CD4 count. At a cost of 0.30, it is affordable to patients living in resource-restrained areas. The technique has the potential to deliver an accurate, precise, low-cost test to monitor HIV+ patients.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • AIDS Serodiagnosis / economics
  • AIDS Serodiagnosis / methods
  • CD4-Positive T-Lymphocytes / cytology*
  • Cell Separation / economics*
  • Cell Separation / instrumentation*
  • Developing Countries
  • Equipment Design / economics
  • Flow Cytometry / economics*
  • Flow Cytometry / instrumentation*
  • HIV Infections / blood*
  • HIV Infections / diagnosis*
  • HIV Seropositivity / blood*
  • HIV Seropositivity / diagnosis*
  • Humans
  • Models, Statistical
  • Regression Analysis
  • Reproducibility of Results