Streamlining SARS-CoV-2 confirmatory testing to reduce false positive results.

BACKGROUND: Confirmatory testing of SARS-CoV-2 results is essential to reduce false positives, but comes at a cost of significant extra workload for laboratories and increased turnaround time. A balance must be sought. We analysed our confirmatory testing pathway to produce a more refined approach in preparation for rising case numbers. METHODS: Over a 10-week low prevalence period we performed confirmatory testing on all newly positive results. Turnaround time was measured and results were analysed to identify a threshold that could be applied as a cut-off for future confirmatory testing and reduce overall workload for the laboratory. RESULTS: Between 22/06/20 and 31/08/20 confirmatory testing was performed on 108 newly positive samples, identifying 32 false positive results (30 %). Turnaround time doubled, increasing by an extra 17 h. There was a highly statistically significant difference between initial Relative Light Unit (RLU) of results that confirmed compared to those that did not, 1176 vs 721 (P < 0.00001). RLU = 1000 was identified as a suitable threshold for confirmatory testing in our laboratory: with RLU ≥ 1000, 55/56 (98 %) confirmed as positive, whereas with RLU < 1000 only 12/38 (32 %) confirmed. CONCLUSIONS: False positive SARS-CoV-2 tests can be identified by confirmatory testing, yet this may significantly delay results. Establishing a threshold for confirmatory testing streamlines this process to focus only on samples where it is most required. We advise all laboratories to follow a similar process to identify thresholds that trigger confirmatory testing for their own assays, increasing accuracy while maintaining efficiency for when case numbers are high.

Specificity and positive predictive value of SARS-CoV-2 nucleic acid amplification testing in a low-prevalence setting.

OBJECTIVES: When the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is low, many positive test results are false positives. Confirmatory testing reduces overdiagnosis and nosocomial infection and enables real-world estimates of test specificity and positive predictive value. This study estimates these parameters to evaluate the impact of confirmatory testing and to improve clinical diagnosis, epidemiological estimation and interpretation of vaccine trials. METHODS: Over 1 month we took all respiratory samples from our laboratory with a patient's first detection of SARS-CoV-2 RNA (Hologic Aptima SARS-CoV-2 assay or in-house RT-PCR platform), and repeated testing using two platforms. Samples were categorized by source, and by whether clinical details suggested COVID-19 or corroborative testing from another laboratory. We estimated specificity and positive predictive value using approaches based on maximum likelihood. RESULTS: Of 19 597 samples, SARS-CoV-2 RNA was detected in 107; 52 corresponded to first-time detection (0.27% of tests on samples without previous detection). Further testing detected SARS-CoV-2 RNA once or more ('confirmed') in 29 samples (56%), and failed to detect SARS-CoV-2 RNA ('not confirmed') in 23 (44%). Depending upon assumed parameters, point estimates for specificity and positive predictive value were 99.91-99.98% and 61.8-89.8% respectively using the Hologic Aptima SARS-CoV-2 assay, and 97.4-99.1% and 20.1-73.8% respectively using an in-house assay. CONCLUSIONS: Nucleic acid amplification testing for SARS-CoV-2 is highly specific. Nevertheless, when prevalence is low a significant proportion of initially positive results fail to confirm, and confirmatory testing substantially reduces the detection of false positives. Omitting additional testing in samples with higher prior detection probabilities focuses testing where it is clinically impactful and minimizes delay.