Evaluation of GeneXpert and advanced biological laboratories UltraGene HCV diagnostic detection and performance against Roche real time PCR in Myanmar.

BACKGROUND: Developing countries experience limited access to HCV laboratory tests for different reasons. Providing near to real-time HCV testing and results especially to at-risk populations including those in rural settings for timely initiation to treatment is key. Within a rural Myanmar setting, we compared HCV diagnostic detection and quantification of the GeneXpert, and Advanced Biological Laboratories UltraGene-HCV assays against the gold standard and reference method Roche real-time HCV in Myanmar. METHODS: Blood samples from 158 high-risk individuals were assessed using three different methods at baseline. Results were checked for normality and log transformed. Log differences and bias between methods were calculated and correlated. Pearson's correlation coefficient was used to determine the association of HCV viral loads across all methods. The level of agreement with the standard method (Roche real time HCV) was assessed using Bland-Altman analyses. RESULTS: There was a strong positive correlation coefficient between all three methods with GeneXpert and Roche having the strongest, r = 0.96, (p<0.001). Compared to Roche, ABL (mean difference, 95 % limits of agreement; -0.063 and -1.4 to 1.3 Log10IU/mL) and GeneXpert (mean difference, 95 % limits of agreement; -0.28 and -0.7 to 1.8 Log10IU/mL) showed a good level of agreement with the GeneXpert being slightly superior. CONCLUSION: We demonstrate the excellent performance and no-inferiority, in terms of levels of agreements of both GeneXpert and ABL compared to the Roche platform and supporting the use of the POC assays as alternative a cost-effective methods in HCV detection and diagnosis in developing and low resource settings countries.

Comparison of HIV-1 drug resistance profiles generated from novel software applications for routine patient care.

INTRODUCTION: Clinical laboratories performing routine HIV-1 genotyping antiviral drug resistance (DR) testing need reliable and up-to-date information systems to provide accurate and timely test results to optimize antiretroviral treatment in HIV-1-infected patients. MATERIALS AND METHODS: Three software applications were used to compare DR profiles generated from the analysis of HIV-1 protease (PR) and reverse transcriptase (RT) gene sequences obtained by Sanger sequencing assay in 100 selected clinical plasma samples from March 2013 through May 2014. Interpretative results obtained from the Trugene HIV-1 Genotyping assay (TG; Guidelines v17.0) were compared with a newly FDA-registered data processing module (DPM v1.0) and the research-use-only ViroScore-HIV (VS) software, both of which use the latest versions of Stanford HIVdb (SD v7.0) and geno2pheno (G2P v3.3) interpretive algorithms (IA). Differences among the DR interpretive algorithms were compared according to drug class (NRTI, NNRTI, PI) and each drug. HIV-1 tropism and integrase inhibitor resistance were not evaluated (not available in TG). RESULTS: Overall, only 17 of the 100 TG sequences obtained yielded equivalent DR profiles among all 3 software applications for every IA and for all drug classes. DPM and VS generated equivalent results with >99.9% agreement. Excluding AZT, DDI, D4T and rilpivirine (not available in G2P), ranges of agreement in DR profiles among the three IA (using the DPM) are shown in Table 1. CONCLUSIONS: Substantial discrepancies (<75% agreement) exist among the three interpretive algorithms for ETR, while G2P differed from TG and SD for resistance to TDF and TPV/r. Use of more than one DR interpretive algorithm using well-validated software applications, such as DPM v1.0 and VS, would enable clinical laboratories to provide clinically useful and accurate DR results for patient care needs.