Table 3.

Stepwise linear regression of EDSS in multiple sclerosis

	Model summary+predictors	Regression coefficient	95% CI	P values
MRI metrics
EDSS score	Adj.R2=0.185
	NABV, cm3	−0.0041	(−0.0077 to −0.00043)	0.029
	Age, years	0.081	(0.044 to 0.12)	< 0.001
	Female	−0.73	(−1.66 to 0.20)	0.125
MRI metrics+network measures
EDSS score	Adj.R2=0.205
	NABV, cm3	−0.0021	(−0.0061 to 0.0019)	0.297
	Edge density, %	−0.13	(−0.26 to −0.0014)	0.047
	Age, years	0.087	(0.051 to 0.12)	< 0.001
	Female	−0.60	(−1.53 to 0.33)	0.202
	Adj.R2=0.221
	NABV, cm3	−0.0037	(−0.0073 to −0.00016)	0.041
	Global efficiency	−0.0026	(−0.0048 to −0.00058)	0.013
	Age, years	0.072	(0.036 to 0.11)	< 0.001
	Female	−0.52	(−1.44 to 0.40)	0.266
	Adj.R2=0.206
	NABV, cm3	−0.0041	(−0.076 to −0.00049)	0.026
	mLE	−0.0019	(−0.0038 to −0.000044)	0.045
	Age, years	0.073	(0.036 to 0.11)	< 0.001
	Female	−0.57	(−1.50 to 0.37)	0.231
	Adj.R2=0.229
	NABV, cm3	−0.0016	(−0.005 to 0.007)	0.551
	mCC	−0.029	(−0.051 to −0.0075)	0.008
	Age, years	0.078	(−0.0042 to 0.0022)	< 0.001
	Female	−0.30	(−1.26 to 0.66)	0.534
Final model
EDSS score	Adj.R2=0.259
	Edge density, %	−0.17	(−0.28 to −0.060)	0.003
	Global efficiency	−0.0031	(−0.0051 to −0.0011)	0.003
	Age, years	0.081	(0.047 to 0.12)	< 0.001

P values in bold denote statistical significance at p<0.05.

EDSS, Expanded Disability Status Scale; NABV, normal-appearing brain volume; mCC, mean clustering coefficient; mLE, mean local efficiency.