Predictors and biomarkers of treatment gains in a clinical stroke trial targeting the lower extremity.

Author(s): Burke E(1), Dobkin BH(1), Noser EA(1), Enney LA(1), Cramer SC(2).

Affiliation(s): Author information: (1)Departments of Anatomy and Neurobiology (E.B., S.C.C.) and Neurology (S.C.C.), University of California, Irvine; Department of Neurology, University of California, Los Angeles (B.H.D.); Department of Neurology, University of Texas, Houston (E.A.N.); and Neurosciences Therapy Area Unit, GlaxoSmithKline, Research Triangle Park, NC (L.A.E.). (2)Departments of Anatomy and Neurobiology (E.B., S.C.C.) and Neurology (S.C.C.), University of California, Irvine; Department of Neurology, University of California, Los Angeles (B.H.D.); Department of Neurology, University of Texas, Houston (E.A.N.); and Neurosciences Therapy Area Unit, GlaxoSmithKline, Research Triangle Park, NC (L.A.E.). scramer@uci.edu.

Publication date & source: 2014, Stroke. , 45(8):2379-84

BACKGROUND AND PURPOSE: Behavioral measures are often used to distinguish subgroups of patients with stroke (eg, to predict treatment gains, stratify clinical trial enrollees, or select rehabilitation therapy). In studies of the upper extremity, measures of brain function using functional magnetic resonance imaging (fMRI) have also been found useful, but this approach has not been examined for the lower extremity. The current study hypothesized that an fMRI-based measure of cortical function would significantly improve prediction of treatment-induced lower extremity behavioral gains. Biomarkers of treatment gains were also explored. METHODS: Patients with hemiparesis 1 to 12 months after stroke were enrolled in a double-blind, placebo-controlled, randomized clinical trial of ropinirole+physical therapy versus placebo+physical therapy, results of which have previously been reported (NCT00221390).(15) Primary end point was change in gait velocity. Enrollees underwent baseline multimodal assessment that included 19 measures spanning 5 assessment categories (medical history, impairment, disability, brain injury, and brain function), and also underwent reassessment 3 weeks after end of therapy. RESULTS: In bivariate analysis, 8 baseline measures belonging to 4 categories (medical history, impairment, disability, and brain function) significantly predicted change in gait velocity. Prediction was strongest, however, using a multivariate model containing 2 measures (leg Fugl-Meyer score and fMRI activation volume within ipsilesional foot sensorimotor cortex). Increased activation volume within bilateral foot primary sensorimotor cortex correlated positively with treatment-induced leg motor gains. CONCLUSIONS: A multimodal model incorporating behavioral and fMRI measures best predicted treatment-induced changes in gait velocity in a clinical trial setting. Results also suggest potential use of fMRI measures as biomarkers of treatment gains.