4.7 Article

The Limit of Detection Matters: The Case for Benchmarking Severe Acute Respiratory Syndrome Coronavirus 2 Testing

Journal

CLINICAL INFECTIOUS DISEASES
Volume 73, Issue 9, Pages E3042-E3046

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/cid/ciaa1382

Keywords

SARS-CoV-2; viral load; limit of detection; cycle threshold; antigen detection

Funding

  1. National Institute of Allergy and Infectious Diseases, NIH [F32 AI124590]

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This study models the relationship between the clinical sensitivity of different testing methods and their limit of detection (LoD), showing that a 10-fold increase in LoD will decrease the sensitivity of the method by approximately 13%. Therefore, the LoD of the testing method significantly impacts the clinical performance of SARS-CoV-2 tests, with methods having the highest LoDs potentially missing the majority of infected patients.
Background. Resolving the coronavirus disease 2019 (COVID-19) pandemic requires diagnostic testing to determine which individuals are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The current gold standard is to perform reverse-transcription polymerase chain reaction (PCR) on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of approximately 100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss infected patients. However, the relative clinical sensitivity of these assays remains unknown. Methods. Here we model the clinical sensitivities of assays based on their LoD. Cycle threshold (Ct) values were obtained from 4700 first-time positive patients using the Abbott RealTime SARS-CoV-2 Emergency Use Authorization test. We derived viral loads from Ct based on PCR principles and empiric analysis. A sliding scale relationship for predicting clinical sensitivity was developed from analysis of viral load distribution relative to assay LoD. Results. Ct values were reliably repeatable over short time testing windows, providing support for use as a tool to estimate viral load. Viral load was found to be relatively evenly distributed across log 10 bins of incremental viral load. Based on these data, each 10-fold increase in LoD is expected to lower assay sensitivity by approximately 13%. Conclusions. The assay LoD meaningfully impacts clinical performance of SARS-CoV-2 tests. The highest LoDs on the market will miss a majority of infected patients. Assays should therefore be benchmarked against a universal standard to allow crosscomparison of SARS-CoV-2 detection methods.

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