Comparison of clinical outcomes of several risk stratification tools in newly diagnosed AML patients: A real-world evidence in our current therapeutic era.

ABSTRACT

BACKGROUND OF THE STUDY AML classification tools have been developed to stratify the risk at AML diagnosis. There is a need to evaluate these tools in the current therapeutic era. COHORT CHARACTERISTICS In this retrospective study, we compared five classifiers ELN 2017, ELN 2022, ALFA classifier, Papaemmanuil et al. classifier, and Lindsley et al. classifier, in a real-life cohort of 281 patients newly diagnosed for AML in Nice University Hospital. In our cohort median age was 68 years old, sex ratio was M/F 56%/44%, performance status was lower than 2 in 73.1% of patients, AML subtype was "De novo" in 71.5%, "secondary" in 22.4%, and "therapy-related" in 6.0% of patients. Intensive chemotherapy was used in 53.0% of patients, and non-intensive chemotherapy in 40.6% of patients. Molecular analysis was available in a large majority of patients and the main mutations found were NPM1 (22.7%), DNMT3A (17.4%), TP53 (13.1%), TET2 (12.4%), and FLT3-ITD (12.4%). RESULTS: In our findings, the comparison of overall survival between the three prognostic groups in the global cohort was statistically significant in all classifiers ELN 2017 p < 0.0001, ELN 2022 p < 0.0001, ALFA classifier p < 0.0001, Papaemmanuil classifier p < 0.0001, Lindsley classifier p = 0.001. ELN 2017, ELN 2022, ALFA classifier, Papaemmanuil classifier, and Lindsley classifier were calculated respectively in 99%, 99%, 89%, 90%, and 89% of patients. CONCLUSIONS: Using Akaike's information criteria (AIC) to compare all five classifiers, ELN 2022 is the best classifier into younger and older patients and for prognosis.