Skip to main content
. 2020 Mar 30;11(3):207. doi: 10.1038/s41419-020-2388-1

Table 3.

Factors affecting CR by logistic regression analysis.

Parameters Logistic regression model
P value OR 95% CI
Lower Higher
Univariate logistic regression
Age (≥18 vs. <18 years) 0.999 0.000
Gender (male vs. female) 0.711 0.625 0.052 7.530
Number of previous chemotherapies (≥4 vs. <4) 0.418 2.800 0.232 33.779
Refractory disease (yes vs. no) 0.418 0.357 0.030 4.309
Relapsed disease (yes vs. no) 0.999 0.000 0.000
Bone marrow blasts (≥5% vs. <5%) 0.999 0.000
Extramedullary disease (yes vs. no) 0.711 0.625 0.052 7.530
CNSL (yes vs. no) 0.920 0.880 0.072 10.753
BCR/ABL1 (positive vs. negative) 0.920 0.880 0.072 10.753
SH2B3 mutation (positive vs. negative) 0.321 0.283 0.023 3.425
PAX5 mutation (positive vs. negative) 0.236 0.220 0.018 2.688
WBC ( ≥ 30 × 109/L vs. <30 × 109/L) 0.998 0.000 0.000
Lymphodepletion regimens (Flu + Cy vs. non-Flu + Cy) 0.920 0.880 0.072 10.753
CAR-T cells (anti-CD19 + CD22 vs. anti-CD19) 0.277 0.250 0.021 3.041
Multivariate logistic regression
No independent factor

Factors affecting CR were determined by univariate and multivariate logistic regression analysis with Forward Stepwise (Conditional) method. P value <0.05 was considered significant.

CR complete remission, CNSL central nervous system leukemia, WBC white blood cell, OR odds ratio, CI confidence interval, Flu fludarabine, Cy cyclophosphamide, CAR-T chimeric antigen receptor T cells.