title: Toward Inclusive Trial Protocols in Heterogeneous Neurological Disorders: Prediction-Based Stratification of Participants With Incomplete Cervical Spinal Cord Injury.
abstract: BACKGROUND
  Several novel drug- and cell-based potential therapies for spinal cord injury (SCI) have either been applied or will be considered for future clinical trials. Limitations on the number of eligible patients require trials be undertaken in a highly efficient and effective manner. However, this is particularly challenging when people living with incomplete SCI (iSCI) represent a very heterogeneous population in terms of recovery patterns and can improve spontaneously over the first year after injury.
  
  
  OBJECTIVE
  The current study addresses 2 requirements for designing SCI trials: first, enrollment of as many eligible participants as possible; second, refined stratification of participants into homogeneous cohorts from a heterogeneous iSCI population.
  
  
  METHODS
  This is a retrospective, longitudinal analysis of prospectively collected SCI data from the European Multicenter study about Spinal Cord Injury (EMSCI). We applied conditional inference trees to provide a prediction-based stratification algorithm that could be used to generate decision rules for the appropriate inclusion of iSCI participants to a trial.
  
  
  RESULTS
  Based on baseline clinical assessments and a defined subsequent clinical endpoint, conditional inference trees partitioned iSCI participants into more homogeneous groups with regard to the illustrative endpoint, upper extremity motor score. Assuming a continuous endpoint, the conditional inference tree was validated both internally as well as externally, providing stable and generalizable results.
  
  
  CONCLUSIONS
  The application of conditional inference trees is feasible for iSCI participants and provides easily implementable, prediction-based decision rules for inclusion and stratification. This algorithm could be utilized to model various trial endpoints and outcome thresholds.
authors: Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland ltanadini@paralab.balgrist.ch.
authors: Lorenzo G
authors: LG
authors: Tanadini
authors: Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
authors: Torsten
authors: T
authors: Hothorn
authors: Craig H. Neilsen Foundation, Encino, CA, USA.
authors: Linda A T
authors: LA
authors: Jones
authors: Craig Hospital, Englewood, CO, USA Department of Physical Medicine and Rehabilitation, University of Colorado Denver, Aurora, CO, USA.
authors: Daniel P
authors: DP
authors: Lammertse
authors: Trauma Center Bayreuth, Bayreuth, Germany EMSCI Study Group.
authors: Rainer
authors: R
authors: Abel
authors: EMSCI Study Group Trauma Center Murnau, Murnau, Germany.
authors: Doris
authors: D
authors: Maier
authors: EMSCI Study Group Spinal Cord Injury Center, Heidelberg University Hospital, Heidelberg, Germany.
authors: Rüdiger
authors: R
authors: Rupp
authors: EMSCI Study Group Spinal Cord Injury Center, Heidelberg University Hospital, Heidelberg, Germany.
authors: Norbert
authors: N
authors: Weidner
authors: Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland EMSCI Study Group.
authors: Armin
authors: A
authors: Curt
authors: ICORD, University of British Columbia and Vancouver Coastal Health, Vancouver, Canada.
authors: John D
authors: JD
authors: Steeves
mesh_terms: D000465:Algorithms; D066193:Cervical Cord / Q000293:injuries; D002986:Clinical Trials as Topic; D023381:Endpoint Determination; D006801:Humans; D008137:Longitudinal Studies; D009422:Nervous System Diseases / Q000628:therapy; D011446:Prospective Studies; D012107:Research Design; D012189:Retrospective Studies; D013119:Spinal Cord Injuries / Q000628:therapy*
keywords: clinical trial design; inclusion exclusion criteria; unbiased recursive partitioning; upper extremity motor score