You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

BACKGROUND: The COVID-19 pandemic has been accompanied by the largest mobilization of therapeutic convalescent plasma (CCP) in over a century. Initial identification of high titer units was based on dose-response data using the Ortho VITROS IgG assay. The proliferation of severe acute respiratory syndrome coronavirus 2 serological assays and non-uniform application has led to uncertainty about their interrelationships. The purpose of this study was to establish correlations and analogous cutoffs between multiple serological assays. METHODS: We compared the Ortho, Abbott, Roche, an anti-spike (S) ELISA, and a virus neutralization assay. Relationships relative to FDA-approved cutoffs under the CCP emergency use authorization were identified in convalescent plasma from a cohort of 79 donors from April 2020. RESULTS: Relative to the neutralization assay, the spearman r value of the Ortho Clinical, Abbott, Roche, anti-S ELISA assays was 0.65, 0.59, 0.45, and 0.76, respectively. The best correlative index for establishing high-titer units was 3.87 signal-to-cutoff (S/C) for the Abbott, 13.82 cutoff index for the Roche, 1:1412 for the anti-S ELISA, 1:219 by the neutralization assay, and 15.9 S/C by the Ortho Clinical assay. The overall agreement using derived cutoffs compared to a neutralizing titer of 1:250 was 78.5% for Abbott, 74.7% for Roche, 83.5% for the anti-S ELISA, and 78.5% for Ortho Clinical. DISCUSSION: Assays based on antibodies against the nucleoprotein were positively associated with neutralizing titers and the Ortho assay, although their ability to distinguish FDA high-titer specimens was imperfect. The resulting relationships help reconcile results from the large body of serological data generated during the COVID-19 pandemic.
["Diagnosis"]