Table 2.

Regularized logistic regression feature selection and beta estimates in predicting ≥50% intracranial large artery stenosis

Feature*	Model 1 β-estimate per unit	Model 2 β-estimate per unit	Model 3 β-estimate per unit
bNGF	0.019	—	—
CCL2	0.055	0.003	0.001
CCL5	−0.065	—	—
CCL11	0.031	0.020	—
CXCL9	0.170	0.013	0.032†
CXCL12a	−0.083	—	—
EGF	−0.329	−0.174	−0.157
HGF	0.134	0.047	0.045†
IFNb	−0.022	—	—
IL1RA	0.052	0.026	0.009
Leptin	0.042	0.030	—
PDGFBB	0.121	—	—
Resistin	0.153	0.060	0.069†
SCF	0.132	0.092	0.088†
sFasL	−0.059	—	—
sICAM1	−0.122	—	−0.017
VEGF-A	0.084	0.050	0.024†
VEGF-D	−0.044	—	—
Age (years)	n/a	n/a	0.042
Hypertension	n/a	n/a	0.495
Diabetes mellitus	n/a	n/a	0.348

bNGF = beta nerve growth factor; CCL = C-C motif chemokine ligand; CXCL = C-X-C motif chemokine ligand; EGF = epidermal growth factor; HGF = hepatocyte growth factor; IL1RA = interleukin 1 receptor antagonist; PDGFBB = platelet derived growth factor-BB; SCF = stem cell factor; sFasL = soluble Fas ligand; sICAM1 = soluble intercellular adhesion molecule-1; VEGF = vascular endothelial growth factor

^*Immune markers were log 2 transformed and standardized.

Features constrained from regression model are denoted by “—”.

Features included in z-score derivation are denoted by “†”.

Model 1 includes only immune markers.

Model 2 additionally includes age, sex, race, ethnicity.

Model 3 additionally includes hypertension, hyperlipidemia, diabetes mellitus, and smoking history.