Predictors of Early Mortality, Response, and Survival in Newly Diagnosed Acute Myeloid Leukemia (AML) Using a Contemporary Academic Cohort

Background Recent advances have led to higher response rates and improved survival in patients with newly diagnosed AML. However, early death, lack of response, and long term leukemia-free survival remain important challenges. Early mortality in AML has been reported to be as high as 20-30%. Similar to relapse risk, disease related factors (along with patient and treatment factors) may also contribute significantly to early mortality. Here we investigated predictors of early (4- and 8-week) mortality, response, relapse-free survival, and overall survival in a contemporary cohort from a single large academic medical center. Methods We analyzed all newly diagnosed patients with AML presenting to and treated at our institution from January 2012 to January 2020. For 4- and 8-week mortality and overall response rate (CR/CRi), logistic regression models were generated to identify factors associated with these outcomes. Kaplan-Meier methods were used to determine the median of the time to event outcomes. Cox proportional hazards modelswere used to identify any association with each of the variables and survival outcomes. Multivariate models were performed for all the outcomes, the models included variables with p