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

Author:

Arnaout Ramy123,Lee Rose A124,Lee Ghee Rye5,Callahan Cody6,Cheng Annie1,Yen Christina F24,Smith Kenneth P12,Arora Rohit12,Kirby James E12

Affiliation:

1. Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

2. Harvard Medical School, Boston, Massachusetts, USA

3. Division of Clinical Informatics, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

4. Division of Infectious Diseases, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

5. Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

6. Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

Abstract

Abstract 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 log10 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 cross-comparison of SARS-CoV-2 detection methods.

Funder

National Institute of Allergy and Infectious Diseases

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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