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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Pooling strategies to reduce the cost of HIV-1 RNA load monitoring in a resource-limited setting
Clinical Infectious Diseases, Volume 52, No. 2, Year 2011
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Description
Background: Quantitative human immunodeficiency virus (HIV) RNA load testing surpasses CD4 cell count and clinical monitoring in detecting antiretroviral therapy (ART) failure; however, its cost can be prohibitive. Recently, the use of pooling strategies with a clinically appropriate viral load threshold was shown to be accurate and efficient for monitoring when the prevalence of virologic failure is low. Methods: We used laboratory request form information to identify specimens with a low pretest probability of virologic failure. Patients aged ≥15 years who were receiving first-line ART had individual viral load results available were eligible. Blood plasma, dried blood spots, and dried plasma spots were evaluated. Two pooling strategies were compared: minipools of 5 samples and a 10 ×10 matrix platform (liquid plasma specimens only). A deconvolution algorithm was used to identify specimens(s) with detectable viral loads. Results: The virologic failure rate in the study sample was <10%. Specimens included were liquid plasma specimens tested in minipools(n = 400), of which 300 were available for testing by matrix, and specimens tested with minipools only: dried blood spots (n = 100) and dried plasma spots (n = 185). Pooling methods resulted in 30.5%-60% fewer HIV RNA tests required to screen the study sample. For plasma pooling, the matrix strategy had the better efficiency, but minipools of 5 dried blood spotshad the best efficiency overall and were accurate at a.95% negative predictive value with minimal technical requirements. Conclusions: In resource-constrained settings, a combination of preselection of patients with low pretest probability of virologic failure and pooled testing can reduce the cost of virologic monitoring without compromising accuracy. © The Author 2011.
Authors & Co-Authors
Van Zyl, Gert Uves
South Africa, Stellenbosch
Stellenbosch University
Preiser, Wolfgang
South Africa, Stellenbosch
Stellenbosch University
Potschka, S.
Germany, Wurzburg
Julius-maximilians-universität Würzburg
Lundershausen, A. T.
Germany, Wurzburg
Julius-maximilians-universität Würzburg
Haubrich, R.
United States, La Jolla
University of California, San Diego
Smith, Davey M.
United States, La Jolla
University of California, San Diego
Statistics
Citations: 60
Authors: 6
Affiliations: 3
Identifiers
Doi:
10.1093/cid/ciq084
ISSN:
10584838
e-ISSN:
15376591
Research Areas
Infectious Diseases
Study Design
Cross Sectional Study
Study Approach
Quantitative