The diagnostic accuracy of isothermal nucleic acid point-of-care tests for human coronaviruses: A systematic review and meta-analysis

Abstract

Many recent studies reported coronavirus point-of-care tests (POCTs) based on isothermal amplification. However, the performances of these tests have not been systematically evaluated. Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy was used as a guideline for conducting this systematic review. We searched peer-reviewed and preprint articles in PubMed, BioRxiv and MedRxiv up to 28 September 2020 to identify studies that provide data to calculate sensitivity, specificity and diagnostic odds ratio (DOR). Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was applied for assessing quality of included studies and Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) was followed for reporting. We included 81 studies from 65 research articles on POCTs of SARS, MERS and COVID-19. Most studies had high risk of patient selection and index test bias but low risk in other domains. Diagnostic specificities were high (> 0.95) for included studies while sensitivities varied depending on type of assays and sample used. Most studies (n = 51) used reverse transcription loop-mediated isothermal amplification (RT-LAMP) to diagnose coronaviruses. RT-LAMP of RNA purified from COVID-19 patient samples had pooled sensitivity at 0.94 (95% CI: 0.90-0.96). RT-LAMP of crude samples had substantially lower sensitivity at 0.78 (95% CI: 0.65-0.87). Abbott ID Now performance was similar to RT-LAMP of crude samples. Diagnostic performances by CRISPR and RT-LAMP on purified RNA were similar. Other diagnostic platforms including RT- recombinase assisted amplification (RT-RAA) and SAMBA-II also offered high sensitivity (> 0.95). Future studies should focus on the use of un-bias patient cohorts, double-blinded index test and detection assays that do not require RNA extraction.

Figure 1

The preferred reporting items for a systematic review and meta-analysis (PRISMA) flow diagram.

Figure 2

Quality assessment of diagnostic accuracy studies 2 (QUADAS-2) finding per domain for 81 studies included in this systematic review.

Figure 3

The forest plot of sensitivity, specificity and diagnostic odds ratio (DOR) of human coronavirus nucleic acid point-of-care tests (POCTs) on purified RNA samples (A) and on crude patient samples (B). Rows shows first author name, and performance (sensitivity, specificity and DOR) of each study. Different studies from the same research articles are labelled with different letter [a], [b], [c], etc. Blue parentheses after first author names indicates the types of coronaviruses diagnosed and publication years of the studies. All rows without blue parentheses show studies on COVID-19 diagnosis published in 2020. Red dots indicate those studies that were only available as pre-prints (not peer-reviewed). The far right blue texts indicate the types of diagnostic assays used in the studies. The far left yellow boxes prefacing the author names denote the studies having no QUADAS-2 domain with high risk bias or high concern of applicability but have unclear bias or concerns in some QUADAS-2 domain. Green boxes denote that the study has low risk of bias and low concern of applicability in all QUADAS-2 domains. All rows without yellow or green box show studies with high risk of bias or high concern of applicability in at least one QUADAS-2 domain.

Figure 4

Hierarchical subgrouping of studies for meta-analysis. (A) subgrouping of all qualified studies. (B) subgrouping of only qualified studies that provide Ct values of positive samples. “n” indicates the number of studies in a subgroup. Pooled diagnosis results from subgroups in white boxes were used for calculating pooled sensitivity, specificity and DOR. Subgroups in grey boxes were not used for sensitivity, specificity, nor DOR calculation.