Multicenter clinical evaluation of alinity m HCV assay performance.
J Clin Virol
; 129: 104531, 2020 08.
Article
in En
| MEDLINE
| ID: mdl-32688330
ABSTRACT
BACKGROUND:
Nucleic acid testing is essential for the detection and quantification of HCV RNA in the diagnosis of HCV infection and treatment monitoring. The Alinity m HCV assay was recently developed by Abbott Molecular for rapid detection and quantification of HCV RNA on the fully automated, continuous, random-access Alinity m analyzer.OBJECTIVES:
Our study assessed the performance of the new Alinity m HCV assay for detection and quantification of HCV RNA in a large series of patient samples of various genotypes. This international, multicentric study evaluated the linearity, precision, and reproducibility of the Alinity m HCV assay and its performance in comparison to three other HCV assays currently used in clinical practice.RESULTS:
The Alinity m HCV assay demonstrated high linearity (correlation coefficient râ¯=â¯1.00), precision (coefficients of variation [CV] 6.6-13.5 %) and reproducibility (CV 1.7-4.3 % across three control lots). At a concentration near the lower limit of detection, the Alinity m HCV assay exhibited >98 % detectability. The Alinity m HCV assay showed excellent correlation with comparator HCV assays in serum (nâ¯=â¯406) and plasma (nâ¯=â¯1401) samples (correlation coefficients ≥0.96, bias 0.01 to 0.14 Log10 IU/mL). More than 95 % of the quantified results with the Alinity m HCV assay were less than mean bias ± 1.96 SD different from those of the comparator assays.CONCLUSIONS:
The newly developed Alinity m HCV assay is sensitive, reproducible, and accurately quantifies HCV RNA levels in serum and plasma samples from patients with chronic HCV infection, with no impact of HCV genotype on assay performance.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Hepatitis C
/
Hepacivirus
Type of study:
Clinical_trials
/
Diagnostic_studies
Limits:
Humans
Language:
En
Journal:
J Clin Virol
Journal subject:
VIROLOGIA
Year:
2020
Document type:
Article