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.

Figure 1.

Comparison of interferon-γ–inducible protein 10 (IP-10) levels in antiretroviral therapy–treated individuals with and without detectable viral load (VL >150 copies/mL). Box as interquartile range (IQR), middle line as median, whiskers as Tukey values (1.5 × IQR) and dots as outliers. Nonparametric U test significance is indicated as “****” for P < .0001.

Figure 2.

Performance of univariate and multivariate interferon-γ–inducible protein 10 (IP-10) models in predicting detectable viral load. A, Comparison between receiver operating characteristic (ROC) curves for univariate IP-10 model (line with circles) and multivariate model (line with triangles) including IP-10 and CD4 T-cell count. IP-10 univariate model cutoff points (pg/mL) (B) and multivariate model score cutoff points (C) with their respective sensitivity and specificity values.

Figure 3.

Accuracy of the interferon-γ–inducible protein 10 model for identifying patients with detectable viral load according to the observed prevalence of individuals on antiretroviral therapy with detectable viremia. A, Positive predictive value (PPV) estimated for sensitivity (Se) = 91.9% and 3 different specificity (Sp) scenarios according to the estimated confidence interval (Sp = 59.9% [95% confidence interval, 52.0%–67.4%]). B, Negative predictive value (NPV) estimated for specificity = 59.9% and 3 different sensitivity scenarios according to the estimated confidence interval (Se = 91.9% [95% CI, 83.9%–96.7%]). Dashed/dotted line indicates PPV and NPV at the prevalence of detectable VL observed in the cross-sectional resistance study [16].