Comparison of the performance of Aptima HIV-1 Quant Dx Assay with Abbott RealTime HIV Assay for viral load monitoring using plasma and Dried Blood Spots collected in Kenya.

INTRODUCTION: HIV-1 viral Load (VL) testing is recommended for the monitoring of antiretroviral treatment. Dried Blood Spots (DBS) are an effective sample type in resource limited settings, where safe phlebotomy and reliable shipping are hard to guarantee. In HIV high burden countries, high throughput assays can improve access to testing services. The Hologic Aptima HIV-1 Quant Dx Assay (Aptima Assay) is a high throughput assay that runs on the CE-IVD approved Panther platform. The objectives of this study were to assess the performance characteristics of Aptima for VL monitoring using plasma and venous DBS specimens and to determine the stability of HIV-1 RNA in DBS. MATERIALS AND METHODS: This was a cross-sectional study of 2227 HIV infected adults visiting health facilities in Nairobi and Busia, Kenya. Each provided a venous blood sample; plasma was prepared from 1312 samples while paired DBS samples and plasma were prepared from the remaining 915 samples. The agreement between the Aptima assay and the Abbott RealTime HIV-1 Assay (Abbott RT) was analysed by comparing the HIV-1 VL in both assays at the medical decision point of 1000 copies/mL. To assess stability of HIV-1 RNA in DBS, VL in DBS spotted on day 0 were compared with that from the same DBS card after 21 days of storage at room temperature. RESULTS: Overall, 436 plasma samples had quantifiable results in both Aptima and Abbott RT. The agreement between the two assays at 1000 copies/mL was 97.48% with a Pearson's correlation coefficient (r) of 0.9589 and gave a mean bias of 0.33 log copies/mL on Bland-Altman analysis. For fresh DBS, the agreement in both assays was 94.64% at 1000 copies/mL, with an r of 0.8692 and a mean bias of 0.35 log copies/mL. The overall agreement between DBS tested in Aptima on day 0 versus day 21 was 95.71%, with a mean bias of -0.154. CONCLUSION: The Aptima HIV-1 Quant Dx assay is an accurate test for VL monitoring of HIV-1 using DBS and plasma sample types in Kenya.

Prevalence and factors associated with HIV-1 drug resistance mutations in treatment-experienced patients in Nairobi, Kenya: A cross-sectional study.

ABSTRACT: An estimated 1.5 million Kenyans are HIV-seropositive, with 1.1 million on antiretroviral therapy (ART), with the majority of them unaware of their drug resistance status. In this study, we assessed the prevalence of drug resistance to nucleoside reverse transcriptase inhibitors (NRTIs), nucleoside reverse transcriptase inhibitors (NNRTIs), and protease inhibitors, and the variables associated with drug resistance in patients failing treatment in Nairobi, Kenya.This cross-sectional study utilized 128 HIV-positive plasma samples obtained from patients enrolled for routine viral monitoring in Nairobi clinics between 2015 and 2017. The primary outcome was human immunodeficiency virus type 1 (HIV-1) drug resistance mutation counts determined by Sanger sequencing of the polymerase (pol) gene followed by interpretation using Stanford's HIV Drug Resistance Database. Poisson regression was used to determine the effects of sex, viral load, age, HIV-subtype, treatment duration, and ART-regimen on the primary outcome.HIV-1 drug resistance mutations were found in 82.3% of the subjects, with 15.3% of subjects having triple-class ART resistance and 45.2% having dual-class resistance. NRTI primary mutations M184 V/I and K65R/E/N were found in 28.8% and 8.9% of subjects respectively, while NNRTI primary mutations K103N/S, G190A, and Y181C were found in 21.0%, 14.6%, and 10.9% of subjects. We found statistically significant evidence (P = .013) that the association between treatment duration and drug resistance mutations differed by sex. An increase of one natural-log transformed viral load unit was associated with 11% increase in drug resistance mutation counts (incidence rate ratio [IRR] 1.11; 95% CI 1.06-1.16; P < .001) after adjusting for age, HIV-1 subtype, and the sex-treatment duration interaction. Subjects who had been on treatment for 31 to 60 months had 63% higher resistance mutation counts (IRR 1.63; 95% CI 1.12-2.43; P = .013) compared to the reference group (<30 months). Similarly, patients on ART for 61 to 90 months were associated with 133% higher mutation counts than the reference group (IRR 2.33; 95% CI 1.59-3.49; P < .001). HIV-1 subtype, age, or ART-regimen were not associated with resistance mutation counts.Drug resistance mutations were found in alarmingly high numbers, and they were associated with viral load and treatment time. This finding emphasizes the importance of targeted resistance monitoring as a tool for addressing the problem.