We compared the performance of five assays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection on nasopharyngeal swab samples: Roche "cobas," Luminex "ARIES," MiRXES "Fortitude," Altona "RealStar," and Thermo Fisher Scientific "TaqPath." A total of 94 nasopharyngeal swab samples were obtained from 80 confirmed coronavirus disease 2019 cases in the first 2 weeks of illness (median, 7 days; range, 2-14 days) and 14 healthy controls. After collection, all samples were transported to the hospital clinical laboratory within 24 h. These samples were tested on all five assays within 3 days of sample receipt. Of the 94 samples, 69 yielded the same result on all platforms, resulting in an agreement of 73.4% (69 of 94). Of these, 14 were the healthy control swabs which all tested negative, demonstrating good specificity across all platforms. The ARIES assay had the lowest detection rate (68.8%), followed by Fortitude (85.0%), RealStar (86.3%), cobas (95.0%), and TaqPath (100%). Statistically significant differences were observed for ARIES, Fortitude, and RealStar when compared against the best performing TaqPath using McNemar's χ 2 test. A consensus result was established based on the results obtained by the cobas, Fortitude, RealStar, and TaqPath. Six discrepancies had failed to reach a consensus and were adjudicated using the Cepheid Xpert Xpress SARS-CoV-2. Overall, the TaqPath and cobas assays were the most sensitive at detecting their designated SARS-CoV-2 gene targets. On the other hand, the ARIES assay was the least sensitive, thus warranting the need for assay re-optimization before go-live at the testing laboratory.

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The HIV genotypic resistance test (GRT) is a standard of care for the clinical management of HIV/AIDS patients. In recent decades, population or Sanger sequencing has been the foundation for drug resistance monitoring in clinical settings. However, the advent of high-throughput or next-generation sequencing has caused a paradigm shift towards the detection and characterization of low-abundance covert mutations that would otherwise be missed by population sequencing. This is clinically significant, as these mutations can potentially compromise the efficacy of antiretroviral therapy, causing poor virologic suppression. Therefore, it is important to develop a more sensitive method so as to reliably detect clinically actionable drug-resistant mutations (DRMs). Here, we evaluated the diagnostic performance of a laboratory-developed, high-throughput, sequencing-based GRT using 103 archived clinical samples that were previously tested for drug resistance using population sequencing. As expected, high-throughput sequencing found all the DRMs that were detectable by population sequencing. Significantly, 78 additional DRMs were identified only by high-throughput sequencing, which is statistically significant based on McNemar’s test. Overall, our results complement previous studies, supporting the notion that the two methods are well correlated, and the high-throughput sequencing method appears to be an excellent alternative for drug resistance testing in a clinical setting.