Bioinformatics Analysis Identifies EPAS1 as a Novel Prognostic Marker Correlated with Immune Infiltration in Acute Myeloid Leukemia

Table 5

Univariate and multivariate Cox regression analyses of prognostic covariates in AML patients.

Characteristics	HR	95% CI	value
Univariate analysis
WBC count (×10^9/L) (>20 vs. <=20)	1.161	0.760-1.772	0.49
PB blasts (%) (>70 vs. <=70)	1.230	0.806-1.878	0.338
BM blasts (%) (>20 vs. <=20)	1.165	0.758-1.790	0.486
Cytogenetic risk (favorable vs. poor & intermediate)	0.312	0.160-0.606	<0.001
Gender (male vs. female)	1.030	0.674-1.572	0.892
Age (>60 vs. <=60)	3.333	2.164-5.134	<0.001
Race (White vs. Asian & Black or African American)	1.200	0.485-2.966	0.693
FLT3 mutation (positive vs. negative)	0.787	0.496-1.248	0.309
IDH1 R132 mutation (positive vs. negative)	1.702	0.689-4.205	0.249
IDH1 R140 mutation (positive vs. negative)	0.884	0.442-1.769	0.727
IDH1 R172 mutation (positive vs. negative)	1.641	0.228-11.804	0.623
RAS mutation (positive vs. negative)	1.555	0.568-4.254	0.39
NPM1 mutation (positive vs. negative)	0.879	0.546-1.416	0.596
DNMT3A mutation (positive vs. negative)	1.404	0.731-2.696	0.308
RUNX1 mutation (positive vs. negative)	1.119	0.553-2.267	0.754
EPAS1 (high vs. low)	0.542	0.352-0.836	0.006
Multivariate analysis
Cytogenetic risk (favorable vs. poor & intermediate)	0.508	0.249-1.034	0.062
Age (>60 vs. <=60)	3.174	2.023-4.980	<0.001
EPAS1 (high vs. low)	0.577	0.364-0.915	0.019

HR: hazard ratio; CI: confidence intervals; PB: peripheral blood; BM: bone marrow.