Table 3

Stepwise linear regression of EDSS in multiple sclerosis

Model summary+predictorsRegression
coefficient
95% CIP values
MRI metrics
EDSS scoreAdj.R2=0.185
NABV, cm3 −0.0041(−0.0077 to −0.00043) 0.029
Age, years0.081(0.044 to 0.12) < 0.001
Female−0.73(−1.66 to 0.20)0.125
MRI metrics+network measures
EDSS scoreAdj.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, years0.087(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, years0.072(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, years0.073(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, years0.078(−0.0042 to 0.0022) < 0.001
Female−0.30(−1.26 to 0.66)0.534
Final model
EDSS scoreAdj.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, years0.081(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.