Pretherapeutic identification of high‐risk acute myeloid leukemia (AML) patients from immunophenotypic, cytogenetic, and clinical parameters

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Abstract
BACKGROUND The goal of this study concerned the pretherapeutic identification of high‐risk acute myeloid leukemia (AML) patients by data pattern analysis from flow cytometric immunophenotype, cytogenetic, and clinical data. METHODS Sixty‐seven parameters of AML patients at diagnosis were classified for predictive information by algorithmic data sieving using iteratively self optimizing triple matrix data pattern analysis (http://www.biochem.mpg.de/valet/classif1.html). RESULTS Pretherapeutic predictive values for nonsurvival within five years and two years were 100.0% and 83.2%, respectively, compared to 13.9% and 47.4% for the prediction of survival at five years and two years, respectively. At diagnosis, five‐year nonsurvivors showed increased patient age and higher concentration of cells in the analyzed specimen, as well as increased levels of % CD2, CD4, CD13, CD36, and CD45 positive AML blasts. Two‐year nonsurvivors were characterized by a data pattern of increased patient age and levels of % CD4, CD7, CD11b, CD24, CD45, TH126, and HLA‐DR positive AML blasts and decreased levels of % CD1, CD65, CD95, and TC25 positive AML blasts. Cytogenetic abnormalities were not selected for the optimized discriminatory data patterns. CONCLUSIONS The comparatively accurate pretherapeutic identification of high‐risk AML patients may prove useful for the development of individualized therapy protocols in stratified clinical patients groups. Cytometry Part B (Clin. Cytometry) 53B:4–10, 2003.

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