Table 3.

Modeling the ability of MRI to predict disability change over 5 years

	All subjects (n=200)	BWH (n=100)	UCSF (n=100)
BPF	−2.37 (−4.71, −0.02) p=0.048*	3.30 (−4.03, 10.64) p=0.37	−0.72 (−6.18, 7.63) p=0.84
T2LV	0.16 (−0.10, 0.42) p=0.23	0.38 (−0.23, 0.98) p=0.22	0.17 (−0.12, 0.46) p=0.25
Age	−0.009 (−0.031, 0.012) p=0.39	−0.011 (−0.044, 0.023) p=0.53	0.009 (−0.024, 0.042) p=0.60
Sex	−0.19 (−0.59, 0.21) p=0.35	−0.16 (−0.78, 0.46) p=0.61	−0.11 (−0.62, 0.41) p=0.67

Key: These estimates with 95% confidence intervals are unstandardized regression coefficients from a linear regression with 5-year change in Expanded Disability Status Scale score as the outcome and these four predictors in the model together. BWH = Brigham and Women’s Hospital; UCSF = University of California, San Francisco; BPF = brain parenchymal fraction; T2LV = global cerebral T2 hyperintense lesion volume (the cube root-transformed T2LV was used);

^*p<0.05.