Interferon-γ-Inducible Protein 10 (IP-10) as a Screening Tool to Optimize Human Immunodeficiency Virus RNA Monitoring in Resource-Limited Settings

Abstract

Background: Achieving effective antiretroviral treatment (ART) monitoring is a key determinant to ensure viral suppression and reach the UNAIDS 90-90-90 targets. The gold standard for detecting virological failure is plasma human immunodeficiency virus (HIV) RNA (viral load [VL]) testing; however, its availability is very limited in low-income countries due to cost and operational constraints.

Methods: HIV-1-infected adults on first-line ART attending routine visits at the Manhiça District Hospital, Mozambique, were previously evaluated for virologic failure. Plasma levels of interferon-γ-inducible protein 10 (IP-10) were quantified by enzyme-linked immunosorbent assay. Logistic regression was used to build an IP-10-based model able to identify individuals with VL >150 copies/mL. From the 316 individuals analyzed, 253 (80%) were used for model training and 63 (20%) for validation. Receiver operating characteristic curves were employed to evaluate model prediction.

Results: From the individuals included in the training set, 34% had detectable VL. Mean age was 41 years, 70% were females, and median time on ART was 3.4 years. IP-10 levels were significantly higher in subjects with detectable VL (108.2 pg/mL) as compared to those with undetectable VL (38.0 pg/mL) (P < .0001, U test). IP-10 univariate model demonstrated high classification performance (area under the curve = 0.85 [95% confidence interval {CI}, .80-.90]). Using a cutoff value of IP-10 ≥44.2 pg/mL, the model identified detectable VL with 91.9% sensitivity (95% CI, 83.9%-96.7%) and 59.9% specificity (95% CI, 52.0%-67.4%), values confirmed in the validation set.

Conclusions: IP-10 is an accurate biomarker to screen individuals on ART for detectable viremia. Further studies should evaluate the benefits of IP-10 as a triage approach to monitor ART in resource-limited settings.

Keywords: cytokines; global health; implementation research; scale-up viral load; sub-Saharan Africa.