Flow cytometry is widely used for immunophenotyping cases of leukemia and lymphoma (reviewed in 18, 33, 42, 58, 63, 64, 93). However, there are few established criteria for how data should be analyzed to arrive at a diagnosis or classification of these disorders. Moreover, although several publications describe typical phenotypes associated with different diseases 110), in general, less attention has been given to how raw data from the flow cytometer are converted into phenotypic information. Many publications describing immunophenotypic characterization of hematologic neoplasms employ arbitrary criteria of ''percentage of positive cells'' for determining antigen expression, without providing clear or detailed descriptions of the methods used for the calculations (12). Other work emphasizes the importance of examination of visual displays of multiparameter list mode data for gathering information about neoplastic cells .
As part of the U.S.-Canadian Consensus Project in Leukemia/Lymphoma Immunophenotyping, our committee was charged with establishing consensus practices for data analysis and interpretation. We thus embarked in the task of assessing how best to evaluate raw data as collected by the flow cytometer to determine the antigens expressed by the leukemia or lymphoma cells, and how to draw conclusions about the nature of the neoplasms from the immunophenotypic data.