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: Convalescent plasma (CP) therapy for COVID-19 provides virus neutralising antibodies that may ameliorate the outcome of SARS-CoV-2 infections. The effectiveness of CP likely depends on its antiviral neutralising potency and is determined using in vitro neutralising antibody assays. STUDY DESIGN AND METHODS: We evaluated abilities of three immunoassays for anti-spike antibodies (EUROimmun, Ortho, Roche), a pseudotype-based neutralisation assay and two assays that quantify ACE2 binding of spike protein (GenScript and haemagglutination-based HAT assay) to predict neutralising antibody titres in 113 convalescent plasma donations. Assay outputs were analysed through linear regression and calculation of sensitivities and specificities by ROC analysis. RESULTS: Median values of plasma samples containing neutralising antibodies produced conversion factors for assay unitage of x6.5 (pseudotype), x19 (GenScript), x3.4 (HAT assay), x0.08 (EUROimmun), x1.64 (Roche) and x0.10 (Ortho). All selected assays were sufficient in identifying the high titre donations based on ROC analysis; area over curve ranged from 91.7% for HAT and GenScript assay to 95.6% for pseudotype assay. However, their ability to predict the actual neutralising antibody levels varied substantially as shown by linear regression correlation values (from 0.27 for Ortho to 0.61 for pseudotype assay). DISCUSSION: Combined, the study data demonstrates that all selected assays were effective in identifying donations with high neutralising antibody levels and are potentially suitable as surrogate assays for donation selection for convalescent plasma therapy.
["Diagnosis", "Treatment"]