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. 2014 Mar 4;123(15):2412–2415. doi: 10.1182/blood-2013-10-532374

Table 1.

Univariable and multivariable logistic regression modeling for CR incidence

Factor Univariable analysis Multivariable analysis
OR P value P value
MD Anderson Cancer Center data set*
 miR-10a-5p 1.33 .014 .019
 miR-10b-5p 1.32 .004 .117
NPM1 mutation 10.50 <.001 .005
 Age 0.94 .032 .115
 Unfavorable PG 0.16 .013 .221
 CN-AML 7.36 .001 .704
CALGB/ALLIANCE data set
 miR-10a-5p 1.06 .23 .01§
NPM1 mutation 3.68 <.001
 miR-10b-5p 1.08 .18 .92
BAALC expression 0.18 <.001 .001

BAALC, brain and acute leukemia cytoplasmic; OR, odds ratio; PG, prognostic group.

*

Cytogenetically heterogeneous de novo adult AML patients (n = 54). All patients were treated with idarubicin 12 mg/m2 daily on days 1 to 3 and cytarabine 1500 mg/m2 continuous infusion for 4 days.

Unfavorable cytogenetic prognostic group defined by the presence of complex karyotype [≥3 cytogenetic abnormalities excluding t(15;17), t(8;21), or inv16 cases], −7, −5, t(6;9), and inv3 cases.

Older (≥60 years) de novo CN-AML patients (n = 183). Multivariable logistic regression models for the CALGB/ALLIANCE data set were constructed to analyze factors related to the probability of achieving CR using a limited backward-selection procedure.

§

Interaction.