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Research Article
Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models
Polychronis Kostoulas
School of Health Sciences, University of Thessaly, Karditsa, Greece
Corresponding Author
ORCiD: https://orcid.org/0000-0001-7051-1541
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The objective of this work was to estimate the diagnostic accuracy of RT-PCR and Lateral flow immunoassay tests (LFIA) for COVID-19, depending on the time post symptom onset. Based on the cross-classified results of RT-PCR and LFIA, we used Bayesian latent class models (BLCMs), which do not require a gold standard for the evaluation of diagnostics. Data were extracted from studies that evaluated LFIA (IgG and/or IgM) assays using RT-PCR as the reference method. The cross-classified results of LFIA and RT-PCR were analysed separately for the first, second and third week post symptom onset. The SeRT-PCR was 0.695 (95% probability intervals: 0.563; 0.837) for the first week and remained similar for the second and the third week. The SeIgG/M was 0.318 (0.229; 0.416) for the first week and increased steadily. It was 0.755 (0.673; 0.829) and 0.927 (0.881; 0.965) for the second and third week, respectively. Both tests had a high to absolute Sp, with point median estimates for SpRT-PCR being consistently higher. SpRT-PCR was 0.990 (0.980; 0.998) for the first week. The corresponding value for SpIgG/M was 0.962 (0.905; 0.998). Further, Sp estimates for each test did not differ between weeks. BLCMs provide a valid and efficient alternative for evaluating the rapidly evolving diagnostics for COVID-19, under various clinical settings and for different risk profiles.
Keywords
SARS-CoV-2, COVID-19, RT-PCR, IgG, IgM, Sensitivity, Specificity, Bayesian analysis, Latent class models.
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Dr. Erdachew Yitagesu
ORCiDcommented on 13 June, 2020
the right work at the right time. It will have value
View 1 reply
Mahmood Hachim
commented on 20 June, 2020
It is fantastic model . keep the god work
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This is a preprint. It has not completed peer review.
Research Article
Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models
Polychronis Kostoulas
School of Health Sciences, University of Thessaly, Karditsa, Greece
Corresponding Author
ORCiD: https://orcid.org/0000-0001-7051-1541
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 05 Jun, 2020
Community comments: 4
Metrics
Comments: 4
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The objective of this work was to estimate the diagnostic accuracy of RT-PCR and Lateral flow immunoassay tests (LFIA) for COVID-19, depending on the time post symptom onset. Based on the cross-classified results of RT-PCR and LFIA, we used Bayesian latent class models (BLCMs), which do not require a gold standard for the evaluation of diagnostics. Data were extracted from studies that evaluated LFIA (IgG and/or IgM) assays using RT-PCR as the reference method. The cross-classified results of LFIA and RT-PCR were analysed separately for the first, second and third week post symptom onset. The SeRT-PCR was 0.695 (95% probability intervals: 0.563; 0.837) for the first week and remained similar for the second and the third week. The SeIgG/M was 0.318 (0.229; 0.416) for the first week and increased steadily. It was 0.755 (0.673; 0.829) and 0.927 (0.881; 0.965) for the second and third week, respectively. Both tests had a high to absolute Sp, with point median estimates for SpRT-PCR being consistently higher. SpRT-PCR was 0.990 (0.980; 0.998) for the first week. The corresponding value for SpIgG/M was 0.962 (0.905; 0.998). Further, Sp estimates for each test did not differ between weeks. BLCMs provide a valid and efficient alternative for evaluating the rapidly evolving diagnostics for COVID-19, under various clinical settings and for different risk profiles.
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
Dr. Erdachew Yitagesu
ORCiDcommented on 13 June, 2020
the right work at the right time. It will have value
View 1 reply
Cord Heuer
replied on 16 June, 2020
A laudible first attempt to answer an acute topical question, albeit applied to a selected, probably non-typical population of individuals enrolled in this specific set 1-3 weeks after onset of signs. Hence results may hold for them but not necessarily for the target populaiton of to-be-tested people such as tracing contacts, asymptomatic probants and people in latent or post-shedding periods or variable age, sex and ethnicity.
View 1 reply
Polychronis Kostoulas
ORCiDreplied on 17 June, 2020
Thank you Cord for your kind words. As you rightly point out, evaluation of diagnostics should always be relevant to the target population and BLCMs is an efficient choice to do this. And we would be happy to analyze new data and provide Se/Sp estimates for the to-be-tested people (i.e. asymptomatic probants and people in latent post shedding periods) when such data are available.
Mahmood Hachim
commented on 20 June, 2020
It is fantastic model . keep the god work
Cord Heuer
replied on 16 June, 2020
A laudible first attempt to answer an acute topical question, albeit applied to a selected, probably non-typical population of individuals enrolled in this specific set 1-3 weeks after onset of signs. Hence results may hold for them but not necessarily for the target populaiton of to-be-tested people such as tracing contacts, asymptomatic probants and people in latent or post-shedding periods or variable age, sex and ethnicity.
View 1 reply
Polychronis Kostoulas
ORCiDreplied on 17 June, 2020
Thank you Cord for your kind words. As you rightly point out, evaluation of diagnostics should always be relevant to the target population and BLCMs is an efficient choice to do this. And we would be happy to analyze new data and provide Se/Sp estimates for the to-be-tested people (i.e. asymptomatic probants and people in latent post shedding periods) when such data are available.