Inclusive Trial Designs in Acute Spinal Cord Injuries: Prediction–Based Stratiﬁcation of Clinical Walking Outcome and Projected Enrolment Frequencies

Neurorehabilitation and Neural Repair, 2022 · DOI: 10.1177/15459683221078302 · Published: April 1, 2022

Spinal Cord Injury Rehabilitation Research Methodology & Design

Simple Explanation

Clinical trials for spinal cord injury (SCI) are challenging due to the low incidence and heterogeneous nature of the condition. Selecting the right patients for these trials is crucial but difficult. This study uses a statistical method (URP–CTREE) to divide SCI patients into groups with similar recovery patterns, allowing for more inclusive trial designs. By identifying these homogeneous groups, researchers can better predict patient outcomes and improve the efficiency of clinical trials for SCI.

Study Duration

6 Months

Participants

958 acute cervical SCI patients

Evidence Level

Not specified

Key Findings

1
The URP–CTREE model identified seven distinct patient cohorts with varying walking function recovery after cervical SCI.
2
Lower Extremity Motor Score (LEMS), pin prick sensation, and age were key predictors of walking function at 6 months post-injury.
3
The study demonstrated that the URP–CTREE approach can broaden inclusion criteria for clinical trials while maintaining patient homogeneity.

Research Summary

This study introduces a method to improve the design of clinical trials for spinal cord injury (SCI) by stratifying patients into homogeneous groups based on predicted walking outcomes. Using an unbiased recursive partitioning technique (URP–CTREE), the researchers identified distinct recovery profiles and estimated patient enrollment frequencies for different outcome cohorts. The findings suggest that URP–CTREE enables more inclusive trial designs by revealing outcome cohort distributions and improving patient recruitment strategies in SCI research.

Practical Implications

Improved Clinical Trial Design

The URP–CTREE method can be used to design more efficient and inclusive clinical trials for SCI by identifying homogeneous patient subgroups.

Personalized Rehabilitation Strategies

Understanding the distinct recovery profiles of different SCI patient cohorts can inform personalized rehabilitation strategies tailored to individual patient needs.

Enhanced Patient Recruitment

The ability to project potential patient enrollment by cohort can improve recruitment strategies and shorten study duration in SCI clinical trials.

Study Limitations

1
The classification into study, validation and reference groups, based on data availability, may have introduced bias as data completeness varies with injury severity of patients.
2
Although the total number of patients analysed in the different cohorts is high, the stratiﬁcation led in some nodes to rather small numbers, lowering statistical power and validity.
3
Further, the assessments in EMSCI do not cover all variables (e.g. weight or secondary complications) which may inﬂuence outcome.

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