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:

Monoclonal antibodies targeting the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 spike protein are important outpatient treatment options in coronavirus disease 2019 to mitigate progression of disease and prevent hospitalization. The impact of different RBD mutations on the efficacy of the available monoclonal antibodies and processes for incorporating this impact into treatment algorithms are ill defined. Herein, we synthesize the data surrounding the impact of key RBD mutations on the efficacy of US Food and Drug Administration Emergency Use Authorized monoclonal antibodies and describe our approach at Michigan Medicine at monitoring mutation frequency in circulating virus and developing an algorithm that incorporates these data into outpatient treatment pathways.
["Treatment"]