Page 95 - 2021_06-Haematologica-web

Quizartinib with low-intensity treatment in AML
Categorical variables were tabulated with their frequencies, and continuous variables were summarized with descriptive statistics. The Fisher exact test, Wilcoxon rank-sum test, and logistic regres- sion model were applied to evaluate the association of response and covariates. The log-rank test and Cox proportional hazards models were used to evaluate the association between overall sur- vival or relapse-free survival with covariates. Survival probabilities were calculated by the Kaplan-Meier method. Comparisons of survival endpoints between the two treatment cohorts are descriptive in nature only as the study was not powered to iden- tify statistical significance. The statistical computations were per- formed using SAS 9.4 (SAS Institute Inc., Cary NC, USA), S-Plus software v8.2 (TIBCO, Palo Alto, CA, USA), and GraphPad Prism 7 (GraphPad Software, Inc., La Jolla, CA, USA).
Results
Patients’ characteristics
A total of 73 patients were treated (Figure 1); 34 patients were treated frontline and 39 in a first salvage setting. Fifteen patients received quizartinib/AZA, and 19 received quizartinib/LDAC as frontline treatment. The median age was 75 years (range, 64-82 years) and 70 years (range, 58- 80 years), respectively (Table 1). Most patients in both cohorts had adverse-risk genetics according to the European LeukemiaNet 2017 classification. All patients were assessed for mutations, using an 81-gene panel, before the start of treatment. The most frequent co-exist- ing mutations were DNMT3A (32%), RUNX1 (29%), NPM1 (27%), TET2 (18%), and TP53 (6%).
Figure 1. CONSORT flow diagram. AZA: azacitidine; LDAC: low-dose cytarabine; ITT: intention-to-treat.
haematologica | 2021; 106(8)
2123