Improved HIV-1 Viral Load Monitoring Capacity Using Pooled Testing With Marker-Assisted Deconvolution
Tao Liu1, Joseph W Hogan, Michael J Daniels
1*Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, RI; †Academic Model Providing Access to Healthcare (AMPATH), Eldoret, Kenya; Departments of ‡Statistics and Data Sciences; §Integrative Biology, University of Texas at Austin, Austin, TX; ‖Division of Infectious Diseases, the Alpert Medical School of Brown University, Providence, RI; and ¶Department of Medicine, School of Medicine, College of Health Sciences, Moi University, Eldoret, Kenya.
Objective:
Improve pooled viral load (VL) testing to increase HIV treatment monitoring capacity, particularly relevant for resource-limited settings.
Design:
We developed marker-assisted mini-pooling with algorithm (mMPA), a new VL pooling deconvolution strategy that uses information from low-cost, routinely collected clinical markers to determine an efficient order of sequential individual VL testing and dictates when the sequential testing can be stopped.
Methods:
We simulated the use of pooled testing to ascertain virological failure status on 918 participants from 3 studies conducted at the Academic Model Providing Access to Healthcare in Eldoret, Kenya, and estimated the number of assays needed when using mMPA and other pooling methods. We also evaluated the impact of practical factors, such as specific markers used, prevalence of virological failure, pool size, VL measurement error, and assay detection cutoffs on mMPA, other pooling methods, and single testing.
Results:
Using CD4 count as a marker to assist deconvolution, mMPA significantly reduces the number of VL assays by 52% [confidence interval (CI): 48% to 57%], 40% (CI: 38% to 42%), and 19% (CI: 15% to 22%) compared with individual testing, simple mini-pooling, and mini-pooling with algorithm, respectively. mMPA has higher sensitivity and negative/positive predictive values than mini-pooling with algorithm, and comparable high specificity. Further improvement is achieved with additional clinical markers, such as age and time on therapy, with or without CD4 values. mMPA performance depends on prevalence of virological failure and pool size but is insensitive to VL measurement error and VL assay detection cutoffs.
Conclusions:
mMPA can substantially increase the capacity of VL monitoring.
