Dimitris K Agrafiotis1,2, Eric Yang1,2, Gary S Littman3, Geert Byttebier4, Laura Dipietro5, Allitia DiBernardo1, Juan C Chavez6, Avrielle Rykman7, Kate McArthur8, Karim Hajjar8,9, Kennedy R Lees8, Bruce T Volpe10, Michael Krams1, Hermano I Krebs5. 1. Janssen Research & Development, Titusville, New Jersey, United States of America. 2. Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States of America. 3. GSL Statistical Consulting, Ardmore, Pennsylvania, United States of America. 4. Bioconstat Bvba, Gent, Belgium. 5. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America. 6. Biogen-Idec, Cambridge, Massachusetts, United States of America. 7. Burke Medical Research Institute, White Plains, New York, United States of America. 8. Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom. 9. Department of Neurology, University of Duisburg-Essen, Essen, Germany. 10. Feinstein Institute for Medical Research, Manhasset, New York, United States of America.
Abstract
OBJECTIVE: One of the greatest challenges in clinical trial design is dealing with the subjectivity and variability introduced by human raters when measuring clinical end-points. We hypothesized that robotic measures that capture the kinematics of human movements collected longitudinally in patients after stroke would bear a significant relationship to the ordinal clinical scales and potentially lead to the development of more sensitive motor biomarkers that could improve the efficiency and cost of clinical trials. MATERIALS AND METHODS: We used clinical scales and a robotic assay to measure arm movement in 208 patients 7, 14, 21, 30 and 90 days after acute ischemic stroke at two separate clinical sites. The robots are low impedance and low friction interactive devices that precisely measure speed, position and force, so that even a hemiparetic patient can generate a complete measurement profile. These profiles were used to develop predictive models of the clinical assessments employing a combination of artificial ant colonies and neural network ensembles. RESULTS: The resulting models replicated commonly used clinical scales to a cross-validated R2 of 0.73, 0.75, 0.63 and 0.60 for the Fugl-Meyer, Motor Power, NIH stroke and modified Rankin scales, respectively. Moreover, when suitably scaled and combined, the robotic measures demonstrated a significant increase in effect size from day 7 to 90 over historical data (1.47 versus 0.67). DISCUSSION AND CONCLUSION: These results suggest that it is possible to derive surrogate biomarkers that can significantly reduce the sample size required to power future stroke clinical trials.
OBJECTIVE: One of the greatest challenges in clinical trial design is dealing with the subjectivity and variability introduced by human raters when measuring clinical end-points. We hypothesized that robotic measures that capture the kinematics of human movements collected longitudinally in patients after stroke would bear a significant relationship to the ordinal clinical scales and potentially lead to the development of more sensitive motor biomarkers that could improve the efficiency and cost of clinical trials. MATERIALS AND METHODS: We used clinical scales and a robotic assay to measure arm movement in 208 patients 7, 14, 21, 30 and 90 days after acute ischemic stroke at two separate clinical sites. The robots are low impedance and low friction interactive devices that precisely measure speed, position and force, so that even a hemiparetic patient can generate a complete measurement profile. These profiles were used to develop predictive models of the clinical assessments employing a combination of artificial ant colonies and neural network ensembles. RESULTS: The resulting models replicated commonly used clinical scales to a cross-validated R2 of 0.73, 0.75, 0.63 and 0.60 for the Fugl-Meyer, Motor Power, NIH stroke and modified Rankin scales, respectively. Moreover, when suitably scaled and combined, the robotic measures demonstrated a significant increase in effect size from day 7 to 90 over historical data (1.47 versus 0.67). DISCUSSION AND CONCLUSION: These results suggest that it is possible to derive surrogate biomarkers that can significantly reduce the sample size required to power future stroke clinical trials.
Authors: Christoph M Kanzler; Mike D Rinderknecht; Anne Schwarz; Ilse Lamers; Cynthia Gagnon; Jeremia P O Held; Peter Feys; Andreas R Luft; Roger Gassert; Olivier Lambercy Journal: NPJ Digit Med Date: 2020-05-29
Authors: Caio B Moretti; Dylan J Edwards; Taya Hamilton; Mar Cortes; Avrielle Rykman Peltz; Johanna L Chang; Alexandre C B Delbem; Bruce T Volpe; Hermano I Krebs Journal: Bioelectron Med Date: 2021-12-29
Authors: Caio B Moretti; Taya Hamilton; Dylan J Edwards; Avrielle Rykman Peltz; Johanna L Chang; Mar Cortes; Alexandre C B Delbe; Bruce T Volpe; Hermano I Krebs Journal: Bioelectron Med Date: 2021-12-29