Diagnostic accuracy of digital RNA quantification versus real-time PCR for the detection of respiratory syncytial virus in nasopharyngeal aspirates from children with acute respiratory infection

Background: Virus-specific molecular assays such as real-time polymerase chain reaction (RT-PCR) are regularly used as the gold standard to diagnose viral respiratory tract infections, but simultaneous detection of multiple different pathogens is often challenging. A multiplex digital method of RNA quantification, nCounter (NanoString Technologies), can overcome this disadvantage and identify, in a single reaction, the presence of different respiratory viruses. Objectives: To evaluate the accuracy of nCounter to identify and quantify RSV-A and RSV-B in nasopharyngeal aspirates (NPA) of children (6-23-months-old) with acute respiratory infection. Study design: NPA was collected at enrolment in a prospective cross-sectional study conducted in Salvador, Brazil. A quantitative RT-PCR with a subgroup-specific primer and probeset for RSV-A and RSV-B was performed in parallel with a customized nCounter probeset containing viral targets in NPA. Results: Of 559 NPA tested, RSV was detected by RT-PCR in 139 (24.9%), by nCounter in 122 (21.8%) and by any method in 158 (28.3%) cases. Compared to the gold standard of qRT-PCR, sensitivity of nCounter was 74.3% (95%CI:63.3%-82.9% RSV-A) and 77.6% (95%CI:66.3%-85.9% RSV-B); specificity was 98.4% (95%CI:96.8%-99.2% RSV-A) and 97.8% (95%CI:96.0%-98.8% RSV-B); positive predictive value was 87.3% (95%CI:76.9%-93.4% RSV-A) and 82.5% (95%CI:71.4%-90.0% RSV-B) and negative predictive value was 96.1% (95%CI:94.1%-97.5% RSV-A), and 96.9% (95%CI:95.1%-98.2% RSV-B). Accuracy was 95.2% (95%CI:93.1%-96.7%) for RSV-A and 95.3% (95%CI:93.3%-96.9%) for RSV-B, while both methods significantly correlated for RSV-A (r = 0.44, p = 8 x 10(-5)) and RSV-B (r = 0.73, p = 3 x 10(-12)) quantification. Conclusions: nCounter is highly accurate in detecting RSV-A/B in NPA. Robustness and high-throughput multiplexing indicate its use in large-scale epidemiological studies.